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Yang Z, Zhang Y, Zheng J, Tao L, Song C, Gong L, Jin R, Liang X. Minimally invasive versus open liver resection for hepatocellular carcinoma with microvascular invasion: a propensity score-matching study. Surg Endosc 2025; 39:3492-3503. [PMID: 40251314 DOI: 10.1007/s00464-025-11717-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2024] [Accepted: 04/06/2025] [Indexed: 04/20/2025]
Abstract
BACKGROUND Microvascular invasion (MVI) is one of the major risk factors for postoperative recurrence of HCC. For HCC patients with MVI, few studies have examined the differences in prognosis between minimally invasive and open liver resection. MATERIALS AND METHODS A total of 171 HCC patients with MVI who underwent curative-intent hepatectomy from September 2017 to October 2022 at Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, were enrolled in this study. Patients were categorized into minimally invasive liver resection (MILR) group (Robotic or laparoscopic) and open liver resection (OLR) group. In order to balance the baseline characteristics between the two groups, 1:4 propensity score matching (PSM) was performed on the two groups. The survival parameters and perioperative parameters were compared between the two groups before and after PSM, respectively. RESULTS There was no significant difference in Recurrence Free Survival (RFS) and Overall Survival (OS) between the two groups before and after PSM. Subgroup analysis showed that there were no significant differences in OS and RFS between the two groups regarding anatomical resection, IWATE difficulty score, surgical margins, and postoperative adjuvant therapy. Perioperative parameters and the rate of major postoperative complications were comparable between the two groups. CONCLUSION Minimally invasive approach can provide a comparable long-term survival result compared with conventional open approach for patients with HCC associated with MVI.
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Affiliation(s)
- Zaibo Yang
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Department of Radiology, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310016, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Yewei Zhang
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
- School of Medicine, Shaoxing University, Shaoxing, 312000, Zhejiang, China
| | - Junhao Zheng
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Liye Tao
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Chao Song
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Linghan Gong
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China
- Zhejiang University Cancer Center, Hangzhou, 310058, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China
| | - Renan Jin
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China.
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China.
- Zhejiang University Cancer Center, Hangzhou, 310058, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China.
| | - Xiao Liang
- Zhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, No. 3 East Qingchun Road, Hangzhou, 310016, Zhejiang Province, China.
- Zhejiang Minimal Invasive Diagnosis and Treatment Technology Research Center of Severe Hepatobiliary Disease, Zhejiang Research and Development Engineering Laboratory of Minimally Invasive Technology and Equipment, Hangzhou, 310016, China.
- Zhejiang University Cancer Center, Hangzhou, 310058, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, 311121, China.
- School of Medicine, Shaoxing University, Shaoxing, 312000, Zhejiang, China.
- School of Basic Medical Sciences and Forensic Medicine, Hangzhou Medical College, Hangzhou, 310000, Zhejiang, China.
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Zhang Y, Liu H, Zhu L, Chong H, Fu H, Yu L, Li P, Qin J, Feng DD, Wang L. Modality-Aware Distillation Network for Microvascular Invasion Prediction of Hepatocellar Carcinoma From MRI Images. IEEE Trans Biomed Eng 2025; 72:1825-1836. [PMID: 40030752 DOI: 10.1109/tbme.2024.3523921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Microvascular invasion (MVI) of hepatocellular carcinoma (HCC) is a crucial histopathologic prognostic factor associated with cancer recurrence after liver transplantation or hepatectomy. Recently, clinicoradiologic characteristics are combined with medical images to enhance the HCC prediction. However, compared to medical imaging data, the clinicoradiologic characteristics (e.g., APOe4 genotyping) is not easy to collect or even unavailable, as it requires more efforts of clinicians and more medical instruments for collecting diverse measurements. This work explores how to transfer the knowledge of a teacher network learned from non-image clinical data and image data to a student network with only image data such that the student network can leverage the transferred clinical information to boost HCC classification with only imaging data as input. Specifically, we present a modality-aware distillation network (MD-Net) to transform non-image clinicoradiologic from the teacher network to the student network. The teacher network integrates non-image clinicoradiologic characteristics with two 3D MRI modality images via two MRI-clinical-fusion modules and a symmetric attention (SA) module, while the student network extracts features from two modality MRI data via two MRI-only modules and then refine these two MRI features via a SA module. A classification-level distillation and a feature-level distillation are jointly utilized to transfer the clinical information between teacher and student networks. Furthermore, we design a novel self-supervised task to predict clinicoradiologic characteristics from the imaging data to further enhance the downstream HCC classification. The experimental results from our collected dataset and a multi-modal sarcasm detection dataset have demonstrated the effectiveness of our approach. Specifically, we achieved an AUC score of 71.86% and 75.51% respectively, surpassing the performance of the state-of-the-art classification methods.
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Mu Z, Su J, Yi J, Fan R, Yin J, Li Y, Yao B. A non-invasive nomogram for the prediction of poor prognosis of hepatocellular carcinoma based on the novel marker Interleukin-41. BMC Cancer 2025; 25:941. [PMID: 40419967 PMCID: PMC12105370 DOI: 10.1186/s12885-025-14344-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2025] [Accepted: 05/16/2025] [Indexed: 05/28/2025] Open
Abstract
Death and tumor recurrence are both important adverse prognostic factors for hepatocellular carcinoma(HCC) patients. This article aims to discuss the risk factors for recurrence and death in patients with HCC after R0 resection, and to establish a nomogram model for predicting the recurrence and death of HCC patients.A total of 224 HCC patients after R0 resection were enrolled and divided into a training cohort (n = 149) and a validation cohort (n = 75) The risk factors for recurrence and death were determined based on cox regression analysis. A nomogram containing independent risk predictors was established and validated.The recurrence rate of 224 cases of HCC after R0 resection was 43.30%. The high expression of interleukin-41(IL41) (HR = 2.446, P = 0.000), intratumoral artery (HR = 1.862, P = 0.005), and MVI1 subgroup of microvascular invasion(MVI) grade (HR = 1.541, P = 0.031) are independent risk factors associated with recurrence after resection of HCC. The mortality rate was 15.63%. The high expression of IL-41 (HR = 4.679, P = 0.000), tumor size ≥ 5 cm (HR = 3.745, P = 0.001), and Aspartate transaminase(AST) concentration 45-90u/L (HR = 2.837, P = 0.015) are independent risk factors associated with mortality. Interleukin-41(IL-41), microvascular invasion(MVI), and intratumoral artery are independent risk factors for recurrence after resection of hepatocellular carcinoma. IL-41, tumor size, and Aspartate transaminase(AST) are independent risk factors for death after resection of hepatocellular carcinoma. We developed and validated two multivariate nomograms, and conducted validation. The nomogram models have achieved ideal results in predicting the recurrence and death of HCC patients.
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Affiliation(s)
- Zihan Mu
- Zonglian College, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Jiaojiao Su
- Zonglian College, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Jiuhua Yi
- Zonglian College, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Rui Fan
- Zonglian College, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Jiayuan Yin
- Zonglian College, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yazhao Li
- Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| | - Bowen Yao
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Lu JP, Feng JK, Zhao Y, Chen B, Li PP, He C, Gong L, Bao LL. Grading risk of microvascular invasion impacts survival in hepatocellular carcinoma patients undergoing adjuvant transarterial chemoembolization: A multicenter study. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2025; 51:110102. [PMID: 40300381 DOI: 10.1016/j.ejso.2025.110102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2025] [Revised: 04/10/2025] [Accepted: 04/24/2025] [Indexed: 05/01/2025]
Abstract
PURPOSE To investigate the influence of postoperative adjuvant transarterial chemoembolization (PA-TACE) on the prognosis of hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) following liver resection (LR), and explore whether grading risk of MVI can impact the survival of HCC patients undergoing PA-TACE. METHODS Patients who had HCC with MVI were consecutively enrolled. Overall survival (OS) and recurrence-free survival (RFS) were compared between the PA-TACE and LR groups. Univariate and multivariate analyses were performed to identify independent prognostic factors for these patients. Subgroup survival analysis was conducted using the grading risk of MVI. RESULTS The median OS and RFS of the PA-TACE group were significantly longer than the LR group. PA-TACE was associated with significantly better OS (P = 0.032) and RFS (P = 0.023) compared with LR alone. In subgroup analysis, there were no significant differences in prognosis between the PA-TACE and LR groups for HCC patients with low-risk MVI. For HCC patients with high-risk MVI, the PA-TACE group had significantly better prognosis than the LR group (for OS, P = 0.017; for RFS, P = 0.018). CONCLUSION PA-TACE should be performed selectively in HCC patients with high-risk MVI after curative liver resection. Nonetheless, for HCC patients with low-risk MVI, PA-TACE is not recommended.
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Affiliation(s)
- Jin-Pian Lu
- Department of General Surgery, Dongyang Hospital of Traditional Chinese Medicine, Jinhua, 322100, Zhejiang Province, China
| | - Jin-Kai Feng
- Department of Hepatobiliary Surgery, No.971 Hospital of the Chinese People's Liberation Army (PLA) Navy, Qingdao, 266071, Shandong Province, China
| | - Yang Zhao
- Medical Service Training Center, No.971 Hospital of the Chinese People's Liberation Army (PLA) Navy, Qingdao, 266071, Shandong Province, China
| | - Bin Chen
- Department of General Surgery, Dongyang Hospital of Traditional Chinese Medicine, Jinhua, 322100, Zhejiang Province, China
| | - Peng-Ping Li
- Department of General Surgery, The First People's Hospital of Xiaoshan District, Hangzhou, 311200, Zhejiang Province, China
| | - Chao He
- Department of General Surgery, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310006, Zhejiang Province, China
| | - Lin Gong
- Department of Hepatobiliary Surgery, No.971 Hospital of the Chinese People's Liberation Army (PLA) Navy, Qingdao, 266071, Shandong Province, China.
| | - Ling-Ling Bao
- Department of General Surgery, Dongyang Hospital of Traditional Chinese Medicine, Jinhua, 322100, Zhejiang Province, China.
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Hong Q, Li C, Li Z, Guo Z, Ashraf N, Li K. Noninvasive prediction model for predicting spontaneous tumor necrosis in hepatocellular carcinoma and prognostic study. Eur J Gastroenterol Hepatol 2025:00042737-990000000-00507. [PMID: 40207508 DOI: 10.1097/meg.0000000000002967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/11/2025]
Abstract
BACKGROUND AND OBJECTIVES In hepatocellular carcinoma (HCC), patients with spontaneous tumor necrosis have a high recurrence rate and poor prognosis. However, conventional preoperative imaging could not detect the presence of tumor necrosis. Accordingly, we developed and assessed a nomogram to forecast tumor necrosis. METHODS Clinical data were collected retrospectively from 495 patients with HCC who received a hepatectomy at Zhongnan Hospital of Wuhan University from 1 January 2015 to 31 May 2024. The patients (n = 495) were randomly divided in a 7 : 3 ratio into the training cohort (TC, n = 348) and the validation cohort (VC, n = 147). The logistic regression analyses were used to identify factors independently predicting tumor necrosis in the patients with TC. The Kaplan-Meier survival analysis was used for comparing and estimating survival rates. RESULTS Preoperative clinical tumor-node-metastasis stage, hemoglobin, systemic immune inflammation, alkaline phosphatase, and alpha-fetoprotein levels were identified as hazard factors for predicting tumor necrosis. The area under the receiver operating characteristic curve of the TC, VC, and the full cohort was 0.810, 0.758, and 0.795, respectively. The calibration curves demonstrated a high degree of concordance. The decision curve analysis showed the clinical significance of the nomogram. Both overall survival and recurrence-free survival of patients in the tumor necrosis group were poorer. CONCLUSION Our predictive model could effectively predict the risk of spontaneous tumor necrosis in patients with HCC, and tumor necrosis was related to a worse prognosis.
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Affiliation(s)
- Qingyong Hong
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University
| | - Chunmin Li
- Department of Hepatobiliary and Pancreatic Surgery, The Second Clinical College of Wuhan University, Zhongnan Hospital of Wuhan University
| | - Ziqiang Li
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University
| | - Zhidong Guo
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University
| | - Nadeem Ashraf
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University
| | - Kun Li
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University
- Department of Hepatobiliary and Pancreatic Surgery, Hubei Provincial Clinical Medicine Research Center for Minimally Invasive Diagnosis and Treatment of Hepatobiliary and Pancreatic Diseases, Zhongnan Hospital of Wuhan University, Wuhan, China
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Hwang YJ, Lee H, Hong SK, Yu SJ, Kim H. Membranous Overexpression of Fibronectin Predicts Microvascular Invasion and Poor Survival Outcomes in Patients with Hepatocellular Carcinoma. Gut Liver 2025; 19:275-285. [PMID: 39778882 PMCID: PMC11907257 DOI: 10.5009/gnl240254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 09/05/2024] [Accepted: 09/06/2024] [Indexed: 01/11/2025] Open
Abstract
Background/Aims Fibronectin (FN) has recently been identified as being overexpressed in patients with hepatocellular carcinoma (HCC) and deemed a promising biomarker of vascular invasion. The aim of this study was to examine the patterns of FN expression in HCC cells and their clinicopathological significance, such as their association with vascular invasion and angiogenesis patterns. Methods Immunohistochemical analysis of FN was conducted using tissue microarrays from 258 surgically resected HCCs and matched nontumorous liver tissues. Three distinct FN expression patterns were observed: cytoplasmic, membranous, and sinusoidal. Moderate or strong expression was considered FN-positive. Results Cytoplasmic or sinusoidal FN expression was significantly more common in HCC cells than in the adjacent liver tissue (p<0.001). FN expression was detected in the membranes of HCC cells and absent in nonneoplastic hepatocytes (p<0.001). Overall survival and disease-free survival in patients with HCC cells with membranous FN expression were significantly shorter than those in patients without membranous FN expression. Membranous FN expression in HCC was significantly associated with high serum alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) levels, infiltrative gross type, poor Edmondson-Steiner grade, major vessel invasion, microvascular invasion, macrotrabecular massive subtype, advanced T stage, and vessel-encapsulating tumor cluster pattern. Sinusoidal pattern of FN expression in HCC was significantly associated with high serum AFP and PIVKA-II levels, infiltrative gross type, large tumor size, microvascular invasion, macrotrabecular massive subtype, and vessel-encapsulating tumor cluster patterns. Conclusions Evaluating FN expression in HCC cells may be useful for identifying aggressive cases of HCC with vascular invasion via biopsy.
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Affiliation(s)
- Yoon Jung Hwang
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
- Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Hyejung Lee
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
| | - Suk Kyun Hong
- Department of Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Su Jong Yu
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine and Biomedical Research Institute, Center for Medical Innovation, Seoul National University Hospital, Seoul, Korea
| | - Haeryoung Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
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Wang L, Xu HX, Wang R, Zhang F, Deng D, Zhu X, Tan Q, Yang H. Advances in multi-omics studies of microvascular invasion in hepatocellular carcinoma. Eur J Med Res 2025; 30:165. [PMID: 40075448 PMCID: PMC11905518 DOI: 10.1186/s40001-025-02421-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Accepted: 03/01/2025] [Indexed: 03/14/2025] Open
Abstract
Microvascular invasion (MVI) represents a pivotal independent prognostic factor for the recurrence of hepatocellular carcinoma (HCC) after surgery. It contributes to early intervention for potentially recurrent HCC to enhance patient outcomes and increase survival rates. Traditionally, the diagnosis of MVI has relied on postoperative pathological analysis, and accurate preoperative detection methodologies are lacking. Recent research suggests that multi-omics strategies play a role in definitively diagnosing MVI before surgery and offering personalized selection for clinical decision-making in HCC management. This review meticulously examines a multi-omics approach for the preoperative prediction of MVI in HCC patients, aiming to innovate diagnostic paradigms to anticipate postsurgical recurrence, thereby facilitating earlier and more personalized therapeutic strategies.
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Affiliation(s)
- Lili Wang
- Department of Radiology, First Hospital of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
| | - Han Xin Xu
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China
| | - Rui Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People's Republic of China
| | - Fachang Zhang
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China
| | - Diandian Deng
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China
| | - Xiaoyang Zhu
- Second Clinical Medical School of Lanzhou University, Lanzhou, 730000, China
| | - Qi Tan
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China
| | - Heng Yang
- First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China
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Zheng G, Zheng M, Hu P, Zhu Y, Zhang W, Zhang F. Lasso-Based Nomogram for Predicting Early Recurrence Following Radical Resection in Hepatocellular Carcinoma. J Hepatocell Carcinoma 2025; 12:539-552. [PMID: 40099228 PMCID: PMC11911823 DOI: 10.2147/jhc.s510581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2024] [Accepted: 03/01/2025] [Indexed: 03/19/2025] Open
Abstract
Background Hepatocellular carcinoma (HCC) is a common malignancy with a high recurrence rate following curative resection. This study aimed to identify factors contributing to early recurrence (within 2 years) and develop a Lasso-based nomogram for individualized risk assessment. Methods We conducted a retrospective analysis of 206 hCC patients who underwent curative resection at Taizhou Hospital, Zhejiang Province, from January 2019 to August 2022. Patients were randomly divided into training (n=144) and validation (n=62) cohorts. Lasso regression was used to identify potential recurrence risk factors among 17 candidate predictors. A Cox proportional hazards model was constructed based on variables selected by Lasso. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results Five independent predictors of early HCC recurrence were identified: age, serum alanine aminotransferase (ALT) levels, cirrhosis, tumor diameter, and microvascular invasion (MVI). The nomogram demonstrated area under the curve (AUC) values for recurrence-free survival (RFS) of 0.828 (95% confidence interval [CI]: 0.753-0.904) at 1 year, 0.799 (95% CI: 0.718-0.880) at 2 years, and 0.742 (95% CI: 0.642-0.842) at 5 years in the training cohort. The corresponding AUCs in the validation cohort were 0.823 (95% CI: 0.686-0.960), 0.804 (95% CI: 0.686-0.922), and 0.857 (95% CI: 0.722-0.992) at 1, 2 and 5 years, respectively. Calibration curves and DCA confirmed the nomogram's high accuracy and clinical utility. Conclusion The Lasso-Cox regression nomogram effectively predicts HCC recurrence within two years post-hepatectomy, providing a valuable tool for personalized postoperative management to improve patient outcomes.
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Affiliation(s)
- Guoqun Zheng
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
| | - Minjie Zheng
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
| | - Peng Hu
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
| | - Yu Zhu
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
| | - Wenlong Zhang
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
| | - Fabiao Zhang
- Department of Hepatopancreatobiliary Surgery, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China
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Liang Y, Zhong D, Shang J, Yan H, Su Y, Chen Y, Yang Q, Huang X. Efficacy and safety of postoperative adjuvant HAIC with FOLFOX combining PD-1 inhibitors in HCC patients with microvascular invasion: a propensity score matching analysis. BMC Cancer 2025; 25:418. [PMID: 40055613 PMCID: PMC11887270 DOI: 10.1186/s12885-025-13793-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2024] [Accepted: 02/21/2025] [Indexed: 05/13/2025] Open
Abstract
PURPOSE To evaluate the efficacy and safety of postoperative adjuvant hepatic arterial infusion chemotherapy (PA-HAIC) plus programmed death-1 (PD-1) inhibitors versus PA-HAIC alone for hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI). METHODS This retrospective study included HCC patients with MVI who were treated with either PA-HAIC or PA-HAIC plus PD-1 inhibitors between February 2021 and February 2024. The differences in baseline characteristics, disease-free survival (DFS), and overall survival (OS) were compared between the two groups before and after propensity score-matching (PSM). The treatment-related adverse events (TRAEs) were compared among the two groups after PSM. Cox regression analysis was utilized to determine factors affecting DFS and OS. RESULTS A total of 102 patients were included in the study: 65 in the PA-HAIC group and 37 in the PA-HAIC plus PD-1 group. PSM analysis generated 32 matched pairs of patients in the two groups. The HCC patients in the PA-HAIC plus PD-1 group experienced significantly better DFS compared to those in the PA-HAIC group alone (HR: 0.412; P = 0.031). However, there was no significant difference in OS between the two groups (P = 0.124). Multivariate analysis identified the treatment option (PA-HAIC vs. PA-HAIC + PD-1) as an independent predictive factor for DFS of the patients. Furthermore, the results indicated no statistically significant difference in the incidence of TRAEs between the two groups (P < 0.05). CONCLUSION In comparison with PA-HAIC alone, PA-HAIC combined with PD-1 inhibitors could improve the DFS benefits with acceptable safety profiles in HCC patients with MVI.
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Affiliation(s)
- Yuxin Liang
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
- Department of Hepatobiliary-Pancreatic Surgery, Cell Transplantation Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Deyuan Zhong
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
- Department of Hepatobiliary-Pancreatic Surgery, Cell Transplantation Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Jin Shang
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongtao Yan
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuhao Su
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yahui Chen
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Qinyan Yang
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China.
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xiaolun Huang
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Center, School of Medicine, Sichuan Cancer Hospital & Institute, University of Electronic Science and Technology of China, Chengdu, China.
- Department of Liver Transplantation Center and HBP Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
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10
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Zeng Y, Wu H, Zhu Y, Li C, Du D, Song Y, Su S, Qin J, Jiang G. MRI-based intra-tumoral ecological diversity features and temporal characteristics for predicting microvascular invasion in hepatocellular carcinoma. Front Oncol 2025; 15:1510071. [PMID: 40098699 PMCID: PMC11911209 DOI: 10.3389/fonc.2025.1510071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Accepted: 02/10/2025] [Indexed: 03/19/2025] Open
Abstract
Objective To investigate the predictive value of radiomics models based on intra-tumoral ecological diversity (iTED) and temporal characteristics for assessing microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Material and Methods We retrospectively analyzed the data of 398 HCC patients who underwent dynamic contrast-enhanced MRI with Gd-EOB-DTPA (training set: 318; testing set: 80). The tumors were segmented into five distinct habitats using case-level clustering and a Gaussian mixture model was used to determine the optimal clusters based on the Bayesian information criterion to produce an iTED feature vector for each patient, which was used to assess intra-tumoral heterogeneity. Radiomics models were developed using iTED features from the arterial phase (AP), portal venous phase (PVP), and hepatobiliary phase (HBP), referred to as MiTED-AP, MiTED-PVP, and MiTED-HBP, respectively. Additionally, temporal features were derived by subtracting the PVP features from the AP features, creating a delta-radiomics model (MDelta). Conventional radiomics features were also extracted from the AP, PVP, and HBP images, resulting in three models: MCVT-AP, MCVT-PVP, and MCVT-HBP. A clinical-radiological model (CR model) was constructed, and two fusion models were generated by combining the radiomics or/and CR models using a stacking algorithm (fusion_R and fusion_CR). Model performance was evaluated using AUC, accuracy, sensitivity, and specificity. Results The MDelta model demonstrated higher sensitivity compared to the MCVT-AP and MCVT-PVP models. No significant differences in performance were observed across different imaging phases for either conventional radiomics (p = 0.096-0.420) or iTED features (p = 0.106-0.744). Similarly, for images from the same phase, we found no significant differences between the performance of conventional radiomics and iTED features (AP: p = 0.158; PVP: p = 0.844; HBP: p = 0.157). The fusion_R and fusion_CR models enhanced MVI discrimination, achieving AUCs of 0.823 (95% CI: 0.816-0.831) and 0.830 (95% CI: 0.824-0.835), respectively. Conclusion Delta radiomics features are temporal and predictive of MVI, providing additional predictive information for MVI beyond conventional AP and PVP features. The iTED features provide an alternative perspective in interpreting tumor characteristics and hold the potential to replace conventional radiomics features to some extent for MVI prediction.
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Affiliation(s)
- Yuli Zeng
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Huiqin Wu
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, Guangdong, China
| | - Yanqiu Zhu
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Chao Li
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Dongyang Du
- School of Computer Science, Inner Mongolia University, Inner Mongolia, China
| | - Yang Song
- Magnetic Resonance (MR) Scientific Marketing, Siemens Healthineers Ltd., Shanghai, China
| | - Sulian Su
- Department of Radiology, Xiamen Humanity Hospital of Fujian Medical University, Xiamen, Fujian, China
| | - Jie Qin
- Department of Radiology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Guihua Jiang
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, Guangdong, China
- Department of Radiology, Xiamen Humanity Hospital of Fujian Medical University, Xiamen, Fujian, China
- Guangzhou Key Laboratory of Molecular Functional Imaging and Artificial Intelligence for Major Brain Diseases, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, China
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11
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Wang C, Wu F, Wang F, Chong HH, Sun H, Huang P, Xiao Y, Yang C, Zeng M. The Association Between Tumor Radiomic Analysis and Peritumor Habitat-Derived Radiomic Analysis on Gadoxetate Disodium-Enhanced MRI With Microvascular Invasion in Hepatocellular Carcinoma. J Magn Reson Imaging 2025; 61:1428-1439. [PMID: 38997242 DOI: 10.1002/jmri.29523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/14/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) has a poor prognosis, often characterized by microvascular invasion (MVI). Radiomics and habitat imaging offer potential for preoperative MVI assessment. PURPOSE To identify MVI in HCC by habitat imaging, tumor radiomic analysis, and peritumor habitat-derived radiomic analysis. STUDY TYPE Retrospective. SUBJECTS Three hundred eighteen patients (53 ± 11.42 years old; male = 276) with pathologically confirmed HCC (training:testing = 224:94). FIELD STRENGTH/SEQUENCE 1.5 T, T2WI (spin echo), and precontrast and dynamic T1WI using three-dimensional gradient echo sequence. ASSESSMENT Clinical model, habitat model, single sequence radiomic models, the peritumor habitat-derived radiomic model, and the combined models were constructed for evaluating MVI. Follow-up clinical data were obtained by a review of medical records or telephone interviews. STATISTICAL TESTS Univariable and multivariable logistic regression, receiver operating characteristic (ROC) curve, calibration, decision curve, Delong test, K-M curves, log rank test. A P-value less than 0.05 (two sides) was considered to indicate statistical significance. RESULTS Habitat imaging revealed a positive correlation between the number of subregions and MVI probability. The Radiomic-Pre model demonstrated AUCs of 0.815 (95% CI: 0.752-0.878) and 0.708 (95% CI: 0.599-0.817) for detecting MVI in the training and testing cohorts, respectively. Similarly, the AUCs for MVI detection using Radiomic-HBP were 0.790 (95% CI: 0.724-0.855) for the training cohort and 0.712 (95% CI: 0.604-0.820) for the test cohort. Combination models exhibited improved performance, with the Radiomics + Habitat + Dilation + Habitat 2 + Clinical Model (Model 7) achieving the higher AUC than Model 1-4 and 6 (0.825 vs. 0.688, 0.726, 0.785, 0.757, 0.804, P = 0.013, 0.048, 0.035, 0.041, 0.039, respectively) in the testing cohort. High-risk patients (cutoff value >0.11) identified by this model showed shorter recurrence-free survival. DATA CONCLUSION The combined model including tumor size, habitat imaging, radiomic analysis exhibited the best performance in predicting MVI, while also assessing prognostic risk. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Cheng Wang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fei Wu
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fang Wang
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Huan-Huan Chong
- Department of Radiology, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, China
| | - Haitao Sun
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Peng Huang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuyao Xiao
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chun Yang
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, China
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
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12
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Altaf A, Khalil M, Akabane M, Rashid Z, Kawashima J, Zindani S, Ruzzenente A, Aldrighetti L, Bauer TW, Marques HP, Martel G, Popescu I, Weiss MJ, Kitago M, Poultsides G, Maithel SK, Pulitano C, Shen F, Cauchy F, Koerkamp BG, Endo I, Pawlik TM. Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning. HPB (Oxford) 2025; 27:402-413. [PMID: 39755480 DOI: 10.1016/j.hpb.2024.12.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Revised: 12/12/2024] [Accepted: 12/12/2024] [Indexed: 01/06/2025]
Abstract
BACKGROUND We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of perioperative outcomes on overall survival (OS). METHODS Using a multi-institutional database, TOLS for ICC was defined by employing novel machine learning (ML) models to identify perioperative factors most strongly predictive of OS ≥ 12 months. Subsequently, clinicopathologic factors associated with achieving TOLS were investigated. RESULTS A total of 1556 patients with ICC were included. The ML classification models demonstrated that the absence of post-hepatectomy liver failure, intraoperative blood loss <750 mL, absence of major infectious complications, and R0 resection were the perioperative outcomes associated with prolonged OS, thereby defining TOLS for ICC. On multivariable analysis, older age, ASA class >2, lymph node metastasis, receipt of neoadjuvant therapy, advanced T status, poor histological grade and microvascular invasion were independently associated with lower odds of achieving TOLS (all p-values<0.05). Overall, 60.2 % (n = 936) of the patients achieved TOLS, demonstrating markedly improved OS and recurrence-free survival (RFS) than individuals who did not (both p < 0.05). CONCLUSION A standardized definition of TOLS for ICC was established that may be used to evaluate hospital performance at the patient level and help optimize surgical outcomes for patients with ICC.
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Affiliation(s)
- Abdullah Altaf
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Mujtaba Khalil
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Miho Akabane
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Zayed Rashid
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Jun Kawashima
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Shahzaib Zindani
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | | | | | - Todd W Bauer
- Department of Surgery, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Hugo P Marques
- Department of Surgery, Curry Cabral Hospital, Lisbon, Portugal
| | | | - Irinel Popescu
- Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania
| | - Matthew J Weiss
- Department of Surgery, Northwell Health, Long Island, NY, USA
| | - Minoru Kitago
- Department of Surgery, Keio University, Tokyo, Japan
| | - George Poultsides
- Department of Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - Shishir K Maithel
- Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Carlo Pulitano
- Department of Surgery, Royal Prince Alfred Hospital, University of Sydney, Sydney, NSW, Australia
| | - Feng Shen
- Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - François Cauchy
- Department of Surgery, AP-HP, Beaujon Hospital, Clichy, France
| | - Bas G Koerkamp
- Department of Surgery, Erasmus University Medical Centre, Rotterdam, Netherlands
| | - Itaru Endo
- Department of Surgery, Yokohama City University School of Medicine, Yokohama, Japan
| | - Timothy M Pawlik
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
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13
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Yang G, Chen Y, Wang M, Wang H, Chen Y. Impact of microvascular invasion risk on tumor progression of hepatocellular carcinoma after conventional transarterial chemoembolization. Oncologist 2025; 30:oyae286. [PMID: 39475355 PMCID: PMC11884753 DOI: 10.1093/oncolo/oyae286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Accepted: 09/11/2024] [Indexed: 03/08/2025] Open
Abstract
OBJECTIVE To assess tumor progression in patients with hepatocellular carcinoma (HCC) without macrovascular invasion who underwent treatment with conventional transarterial chemoembolization (cTACE) based on microvascular invasion (MVI) risk within 2 years. METHODS This retrospective investigation comprised adult patients with HCC who had either liver resection or cTACE as their first treatment from January 2016 to December 2021. A predictive model for MVI was developed and validated using preoperative clinical and MRI data from patients with HCC treated with liver resection. The MVI predictive model was applied to patients with HCC receiving cTACE, and differences in tumor progression between the MVI high- and low-risk groups were examined throughout 2 years. RESULTS The MVI prediction model incorporated nonsmooth margin, intratumoral artery, incomplete or absent tumor capsule, and tumor DWI/T2WI mismatch. The area under the receiver operating characteristic curve (AUC) for the prediction model, in the training cohort, was determined to be 0.904 (95% CI, 0.862-0.946), while in the validation cohort, it was 0.888 (0.782-0.994). Among patients with HCC undergoing cTACE, those classified as high risk for MVI possessed a lower rate of achieving a complete response after the first tumor therapy and a higher risk of tumor progression within 2 years. CONCLUSIONS The MVI prediction model developed in this study demonstrates a considerable degree of accuracy. Patients at high risk for MVI who underwent cTACE treatment exhibited a higher risk of tumor progression within 2 years.
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Affiliation(s)
- Guanhua Yang
- The First School of Clinical Medicine, General Hospital of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yuxin Chen
- Department of Paediatrics, Division of Respiratory Medicine and Allergology, Sophia Children’s Hospital, Erasmus MC, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Minglei Wang
- The First School of Clinical Medicine, General Hospital of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Hongfang Wang
- The First School of Clinical Medicine, General Hospital of Ningxia Medical University, Yinchuan, People’s Republic of China
| | - Yong Chen
- Department of Interventional Radiology, General Hospital of Ningxia Medical University, Yinchuan, People’s Republic of China
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Kokudo T, Kokudo N. Evolving Indications for Liver Transplantation for Hepatocellular Carcinoma Following the Milan Criteria. Cancers (Basel) 2025; 17:507. [PMID: 39941874 PMCID: PMC11815920 DOI: 10.3390/cancers17030507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2024] [Revised: 01/28/2025] [Accepted: 01/30/2025] [Indexed: 02/16/2025] Open
Abstract
Background/Objectives: Since their introduction in the 1990s, the Milan criteria have been the gold standard of indication for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). Nevertheless, several institutions have reported wider indication criteria for LT with comparable survival outcomes. Methods: This paper summarizes the recent indications for LT for HCC through a literature review. Results: There are several criteria expanding the Milan criteria, which can be subdivided into the "based on tumor number and size only", "based on tumor number and size plus tumor markers", and "based on tumor differentiation" groups, with the outcomes being comparable to those of patients included within the Milan criteria. Besides the tumor size and number, which are included in the Milan criteria, recent criteria included biomarkers and tumor differentiation. Several retrospective studies have reported microvascular invasion (MVI) as a significant risk factor for postoperative recurrence, highlighting the importance of preoperatively predicting MVI. Several studies attempted to identify preoperative predictive factors for MVI using tumor markers or preoperative imaging findings. Patients with HCC who are LT candidates are often treated while on the waiting list to prevent the progression of HCC or to reduce the measurable disease burden of HCC. The expanding repertoire of chemotherapeutic regiments suitable for patients with HCC should be further investigated. Conclusions: There are several criteria expanding Milan criteria, with the outcomes being comparable to those of patients included within the Milan criteria.
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Affiliation(s)
- Takashi Kokudo
- National Center for Global Health and Medicine, Tokyo 162-8655, Japan;
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15
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Nong HY, Cen YY, Lu SJ, Huang RS, Chen Q, Huang LF, Huang JN, Wei X, Liu MR, Li L, Ding K. Predictive value of a constructed artificial neural network model for microvascular invasion in hepatocellular carcinoma: A retrospective study. World J Gastrointest Oncol 2025; 17:96439. [PMID: 39817122 PMCID: PMC11664629 DOI: 10.4251/wjgo.v17.i1.96439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 09/06/2024] [Accepted: 11/07/2024] [Indexed: 12/12/2024] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a significant risk factor for recurrence and metastasis following hepatocellular carcinoma (HCC) surgery. Currently, there is a paucity of preoperative evaluation approaches for MVI. AIM To investigate the predictive value of texture features and radiological signs based on multiparametric magnetic resonance imaging in the non-invasive preoperative prediction of MVI in HCC. METHODS Clinical data from 97 HCC patients were retrospectively collected from January 2019 to July 2022 at our hospital. Patients were classified into two groups: MVI-positive (n = 57) and MVI-negative (n = 40), based on postoperative pathological results. The correlation between relevant radiological signs and MVI status was analyzed. MaZda4.6 software and the mutual information method were employed to identify the top 10 dominant texture features, which were combined with radiological signs to construct artificial neural network (ANN) models for MVI prediction. The predictive performance of the ANN models was evaluated using area under the curve, sensitivity, and specificity. ANN models with relatively high predictive performance were screened using the DeLong test, and the regression model of multilayer feedforward ANN with backpropagation and error backpropagation learning method was used to evaluate the models' stability. RESULTS The absence of a pseudocapsule, an incomplete pseudocapsule, and the presence of tumor blood vessels were identified as independent predictors of HCC MVI. The ANN model constructed using the dominant features of the combined group (pseudocapsule status + tumor blood vessels + arterial phase + venous phase) demonstrated the best predictive performance for MVI status and was found to be automated, highly operable, and very stable. CONCLUSION The ANN model constructed using the dominant features of the combined group can be recommended as a non-invasive method for preoperative prediction of HCC MVI status.
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Affiliation(s)
- Hai-Yang Nong
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
- Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
- Guangxi Clinical Medical Research Center for Hepatobiliary Diseases, Affiliated Hospital of Youiiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
| | - Yong-Yi Cen
- Guangxi Clinical Medical Research Center for Hepatobiliary Diseases, Affiliated Hospital of Youiiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
- Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China
| | - Shan-Jin Lu
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Rui-Sui Huang
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Qiong Chen
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Li-Feng Huang
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Jian-Ning Huang
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Xue Wei
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Man-Rong Liu
- Department of Ultrasound, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Lin Li
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
| | - Ke Ding
- Department of Radiology, The Third Affiliated Hospital of Guangxi Medical University, Nanning 530031, Guangxi Zhuang Autonomous Region, China
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Liu Y, Zhou Y, Liao C, Li H, Zhang X, Gong H, Pu H. Correlation Between Dynamic Contrast-Enhanced CT Imaging Signs and Differentiation Grade and Microvascular Invasion of Hepatocellular Carcinoma. J Hepatocell Carcinoma 2025; 12:1-14. [PMID: 39807403 PMCID: PMC11725241 DOI: 10.2147/jhc.s489387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2024] [Accepted: 12/20/2024] [Indexed: 01/16/2025] Open
Abstract
Objective This study aimed to investigate how dynamic contrast-enhanced CT imaging signs correlate with the differentiation grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC), and to assess their predictive value for MVI when combined with clinical characteristics. Methods We conducted a retrospective analysis of clinical data from 232 patients diagnosed with HCC at our hospital between 2021 and 2022. All patients underwent preoperative enhanced CT scans, laboratory tests, and postoperative pathological examinations. Among the 232 patients, 89 were identified as MVI-positive and 143 as MVI-negative. Regarding tumor differentiation, 56 patients were well-differentiated, 145 moderately, and 31 poorly. Multivariate logistic regression analysis was employed to establish a prediction model for variables showing significant differences. Additionally, the diagnostic performance of various indicators were evaluated using ROC analysis. Results Among the qualitative data, significant differences (P<0.05) were observed between the MVI-positive and MVI-negative groups in 5 items such as peritumoral enhancement. In terms of quantitative data, the MVI-positive group exhibited higher maximum tumor length, AST, ALT, AFP levels and the ALBI score (P<0.05). Conversely, CT values in the arterial phase (AP), portal venous phase (PVP), and PT levels were lower in the MVI-positive group (P<0.05). Multivariate Logistic regression analysis identified ALBI score, PT level, CT value in PVP, and tumor capsule as independent risk factors for MVI occurrence (AUC: 0.71, 0.58, 0.66, and 0.60). The combined diagnostic AUC value was 0.82 (95% CI: 0.76-0.87). Significant differences were found among different differentiation grade groups in 10 items such as non-smooth tumor margin (P<0.05). Conclusion Preoperative dynamic contrast-enhanced CT examination in patients with HCC can be utilized to predict the presence of MVI. When combined with clinical characteristics, these imaging signs demonstrate good predictive performance for MVI status. Furthermore, this approach has significant implications for determining the differentiation grade of tumors.
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Affiliation(s)
- Yang Liu
- School of Medicine, University of Electronic Science and Technology, Sichuan, China
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Sichuan, People’s Republic of China
| | - Yunhui Zhou
- Department of Radiology, Chengdu Pidu District People’s Hospital, Sichuan, People’s Republic of China
| | - Cong Liao
- School of Medicine, University of Electronic Science and Technology, Sichuan, China
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Sichuan, People’s Republic of China
| | - Hang Li
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Sichuan, People’s Republic of China
| | - Xiaolan Zhang
- Shukun Technology Co., Ltd, Beijing, People’s Republic of China
| | - Haigang Gong
- School of Computer Science and Engineering, University of Electronic Science and Technology, Sichuan, People’s Republic of China
| | - Hong Pu
- School of Medicine, University of Electronic Science and Technology, Sichuan, China
- Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Sichuan, People’s Republic of China
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17
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Yang C, Liang Z, Zhao L, Li R, Ma P. Prediction of microvascular invasion in hepatocellular carcinoma using a preoperative serum C-reactive protein-based nomogram. Sci Rep 2025; 15:522. [PMID: 39748118 PMCID: PMC11696813 DOI: 10.1038/s41598-024-84835-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 12/27/2024] [Indexed: 01/04/2025] Open
Abstract
Microvascular invasion (MVI) diagnosis relies on postoperative pathological examinations, underscoring the urgent need for a novel diagnostic method. C-Reactive Protein (CRP), has shown significant relevance to hepatocellular carcinoma (HCC) prognosis. This study aims to explore the relationship between preoperative serum CRP levels and microvascular invasion in hepatocellular carcinoma and develop a nomogram model for predicting MVI. Patients were categorized into MVI-positive and MVI-negative groups for analysis. Serum CRP levels were compared between the two groups. And then use LASSO regression to screen variables and build a nomogram. CRP levels showed significant differences between the MVI-positive and MVI-negative groups. Multivariable logistic regression analysis identified CRP (OR = 4.85, P < 0.001), lnAFP (OR = 3.11, P < 0.001), WBC count (OR = 2.73, P = 0.003), and tumor diameter (OR = 2.38, P = 0.01) as independent predictors of MVI. A nomogram based on these variables showed good predictive performance in both the training and validation cohorts with dual validation. The clinical prediction nomogram model, which includes serum CRP levels, WBC count, tumor diameter, and serum AFP levels, showed good performance in predicting MVI in both the training and validation cohorts.
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Affiliation(s)
- Chaohao Yang
- Hepatopancreatobiliary Surgery Department, The first affiliated hospital of Zhengzhou university, Zhengzhou, 450001, China
| | - Zhiwei Liang
- Hepatopancreatobiliary Surgery Department, The first affiliated hospital of Zhengzhou university, Zhengzhou, 450001, China
| | - Longshuan Zhao
- Hepatopancreatobiliary Surgery Department, The first affiliated hospital of Zhengzhou university, Zhengzhou, 450001, China
| | - Renfeng Li
- Hepatopancreatobiliary Surgery Department, The first affiliated hospital of Zhengzhou university, Zhengzhou, 450001, China.
| | - Pengfei Ma
- Hepatopancreatobiliary Surgery Department, The first affiliated hospital of Zhengzhou university, Zhengzhou, 450001, China.
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Pei J, Wang L, Li H. Development of a Better Nomogram for Prediction of Preoperative Microvascular Invasion and Postoperative Prognosis in Hepatocellular Carcinoma Patients: A Comparison Study. J Comput Assist Tomogr 2025; 49:9-22. [PMID: 38663025 PMCID: PMC11801467 DOI: 10.1097/rct.0000000000001618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 02/26/2024] [Indexed: 01/19/2025]
Abstract
OBJECTIVE Personalized precision medicine can be facilitated by clinically available preoperative microvascular invasion (MVI) prediction models that are reliable and postoperative MVI pathological grade-related recurrence prediction models that are accurate. In this study, we aimed to compare different mathematical models to derive the best preoperative prediction and postoperative recurrence prediction models for MVI. METHODS A total of 143 patients with hepatocellular carcinoma (HCC) whose clinical, laboratory, imaging, and pathological data were available were included in the analysis. Logistic regression, Cox proportional hazards regression, LASSO regression with 10-fold cross-validation, stepwise regression, and random forest methods were used for variable screening and predictive modeling. The accuracy and validity of seven preoperative MVI prediction models and five postoperative recurrence prediction models were compared in terms of C-index, net reclassification improvement, and integrated discrimination improvement. RESULTS Multivariate logistic regression analysis revealed that a preoperative nomogram model with the variables cirrhosis diagnosis, alpha-fetoprotein > 400, and diameter, shape, and number of lesions can predict MVI in patients with HCC reliably. Postoperatively, a nomogram model with MVI grade, number of lesions, capsule involvement status, macrovascular invasion, and shape as the variables was selected after LASSO regression and 10-fold cross-validation analysis to accurately predict the prognosis for different MVI grades. The number and shape of the lesions were the most common predictors of MVI preoperatively and recurrence postoperatively. CONCLUSIONS Our study identified the best statistical approach for the prediction of preoperative MVI as well as postoperative recurrence in patients with HCC based on clinical, imaging, and laboratory tests results. This could expedite preoperative treatment decisions and facilitate postoperative management.
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Yang J, Dong X, Jin S, Wang S, Wang Y, Zhang L, Wei Y, Wu Y, Wang L, Zhu L, Feng Y, Gan M, Hu H, Ji W. Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma. Acad Radiol 2025; 32:146-156. [PMID: 39025700 DOI: 10.1016/j.acra.2024.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 06/26/2024] [Accepted: 07/02/2024] [Indexed: 07/20/2024]
Abstract
RATIONALE AND OBJECTIVES To develop and validate a clinical-radiomics model of dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative discrimination of Vessels encapsulating tumor clusters (VETC)- microvascular invasion (MVI) and prognosis of hepatocellular carcinoma (HCC). MATERIALS AND METHODS 219 HCC patients from Institution 1 were split into internal training and validation groups, with 101 patients from Institution 2 assigned to external validation. Histologically confirmed VETC-MVI pattern categorizing HCC into VM-HCC+ (VETC+/MVI+, VETC-/MVI+, VETC+/MVI-) and VM-HCC- (VETC-/MVI-). The regions of intratumor and peritumor were segmented manually in the arterial, portal-venous and delayed phase (AP, PP, and DP, respectively) of DCE-MRI. Six radiomics models (intratumor and peritumor in AP, PP, and DP of DCE-MRI) and one clinical model were developed for assessing VM-HCC. Establishing intra-tumoral and peri-tumoral models through combining intratumor and peritumor features. The best-performing radiomics model and the clinical model were then integrated to create a Combined model. RESULTS In institution 1, pathological VM-HCC+ were confirmed in 88 patients (training set: 61, validation set: 27). In internal testing, the Combined model had an AUC of 0.85 (95% CI: 0.76-0.93), which reached an AUC of 0.75 (95% CI: 0.66-0.85) in external validation. The model's predictions were associated with early recurrence and progression-free survival in HCC patients. CONCLUSIONS The clinical-radiomics model offers a non-invasive approach to discern VM-HCC and predict HCC patients' prognosis preoperatively, which could offer clinicians valuable insights during the decision-making phase.
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Affiliation(s)
- Jiawen Yang
- Department of Radiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, Zhejiang 317000, China; Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.
| | - Xue Dong
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| | - Shengze Jin
- Department of Radiology, Taizhou Hospital of Zhejiang Province, Shaoxing University, Taizhou 318000 Zhejiang, China.
| | - Sheng Wang
- Department of Radiology, Taizhou First People's Hospital, Wenzhou Medical College, Taizhou 318020 Zhejiang, China.
| | - Yanna Wang
- Department of Radiology, Taizhou Central Hospital,Wenzhou Medical University, Taizhou 318000 Zhejiang,China.
| | - Limin Zhang
- Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
| | - Yuguo Wei
- Precision Health Institution, GE Healthcare, 310000 Xihu District, Hangzhou, China.
| | - Yitian Wu
- Department of Radiology, Taizhou Hospital of Zhejiang Province, Shaoxing University, Taizhou 318000 Zhejiang, China.
| | - Lingxia Wang
- Department of Radiology, Taizhou Hospital, Zhejiang University, Taizhou 318000 Zhejiang, China.
| | - Lingwei Zhu
- Department of Radiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, Zhejiang 317000, China.
| | - Yuyi Feng
- Department of Radiology, Taizhou Hospital of Zhejiang Province, Shaoxing University, Taizhou 318000 Zhejiang, China.
| | - Meifu Gan
- Department of Pathology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, Zhejiang 317000, China.
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 310016 Hangzhou, People's Republic of China.
| | - Wenbin Ji
- Department of Radiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Taizhou, Zhejiang 317000, China; Key Laboratory of evidence-based Radiology of Taizhou, Linhai 317000, Zhejiang, China.
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Famularo S, Penzo C, Maino C, Milana F, Oliva R, Marescaux J, Diana M, Romano F, Giuliante F, Ardito F, Grazi GL, Donadon M, Torzilli G. Preoperative detection of hepatocellular carcinoma's microvascular invasion on CT-scan by machine learning and radiomics: A preliminary analysis. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2025; 51:108274. [PMID: 38538504 DOI: 10.1016/j.ejso.2024.108274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/20/2024] [Accepted: 03/16/2024] [Indexed: 08/22/2024]
Abstract
INTRODUCTION Microvascular invasion (MVI) is the main risk factor for overall mortality and recurrence after surgery for hepatocellular carcinoma (HCC).The aim was to train machine-learning models to predict MVI on preoperative CT scan. METHODS 3-phases CT scans were retrospectively collected among 4 Italian centers. DICOM files were manually segmented to detect the liver and the tumor(s). Radiomics features were extracted from the tumoral, peritumoral and healthy liver areas in each phase. Principal component analysis (PCA) was performed to reduce the dimensions of the dataset. Data were divided between training (70%) and test (30%) sets. Random-Forest (RF), fully connected MLP Artificial neural network (neuralnet) and extreme gradient boosting (XGB) models were fitted to predict MVI. Prediction accuracy was estimated in the test set. RESULTS Between 2008 and 2022, 218 preoperative CT scans were collected. At the histological specimen, 72(33.02%) patients had MVI. First and second order radiomics features were extracted, obtaining 672 variables. PCA selected 58 dimensions explaining >95% of the variance.In the test set, the XGB model obtained Accuracy = 68.7% (Sens: 38.1%, Spec: 83.7%, PPV: 53.3% and NPV: 73.4%). The neuralnet showed an Accuracy = 50% (Sens: 52.3%, Spec: 48.8%, PPV: 33.3%, NPV: 67.7%). RF was the best performer (Acc = 96.8%, 95%CI: 0.91-0.99, Sens: 95.2%, Spec: 97.6%, PPV: 95.2% and NPV: 97.6%). CONCLUSION Our model allowed a high prediction accuracy of the presence of MVI at the time of HCC diagnosis. This could lead to change the treatment allocation, the surgical extension and the follow-up strategy for those patients.
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Affiliation(s)
- Simone Famularo
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France.
| | - Camilla Penzo
- Pole d'Expertise de la Regulation Numérique (PEReN), Paris, France
| | - Cesare Maino
- Department of Radiology, San Gerardo Hospital, Monza, Italy
| | - Flavio Milana
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Riccardo Oliva
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France
| | - Jacques Marescaux
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France
| | - Michele Diana
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France; Department of General, Digestive and Endocrine Surgery, University Hospital of Strasbourg, France; ICube Lab, Photonics for Health, Strasbourg, France
| | - Fabrizio Romano
- School of Medicine and Surgery, University of Milan-Bicocca, Department of Surgery, San Gerardo Hospital, Monza, Italy
| | - Felice Giuliante
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy
| | - Francesco Ardito
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy
| | - Gian Luca Grazi
- Division of Hepatobiliarypancreatic Unit, IRCCS - Regina Elena National Cancer Institute, Rome, Italy
| | - Matteo Donadon
- Department of Health Sciences, Università del Piemonte Orientale, Novara, Italy; Department of General Surgery, University Maggiore Hospital Della Carità, Novara, Italy
| | - Guido Torzilli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
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Xu ZL, Qian GX, Li YH, Lu JL, Wei MT, Bu XY, Ge YS, Cheng Y, Jia WD. Evaluating microvascular invasion in hepatitis B virus-related hepatocellular carcinoma based on contrast-enhanced computed tomography radiomics and clinicoradiological factors. World J Gastroenterol 2024; 30:4801-4816. [PMID: 39649551 PMCID: PMC11606376 DOI: 10.3748/wjg.v30.i45.4801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 08/28/2024] [Accepted: 09/23/2024] [Indexed: 11/13/2024] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a significant indicator of the aggressive behavior of hepatocellular carcinoma (HCC). Expanding the surgical resection margin and performing anatomical liver resection may improve outcomes in patients with MVI. However, no reliable preoperative method currently exists to predict MVI status or to identify patients at high-risk group (M2). AIM To develop and validate models based on contrast-enhanced computed tomography (CECT) radiomics and clinicoradiological factors to predict MVI and identify M2 among patients with hepatitis B virus-related HCC (HBV-HCC). The ultimate goal of the study was to guide surgical decision-making. METHODS A total of 270 patients who underwent surgical resection were retrospectively analyzed. The cohort was divided into a training dataset (189 patients) and a validation dataset (81) with a 7:3 ratio. Radiomics features were selected using intra-class correlation coefficient analysis, Pearson or Spearman's correlation analysis, and the least absolute shrinkage and selection operator algorithm, leading to the construction of radscores from CECT images. Univariate and multivariate analyses identified significant clinicoradiological factors and radscores associated with MVI and M2, which were subsequently incorporated into predictive models. The models' performance was evaluated using calibration, discrimination, and clinical utility analysis. RESULTS Independent risk factors for MVI included non-smooth tumor margins, absence of a peritumoral hypointensity ring, and a high radscore based on delayed-phase CECT images. The MVI prediction model incorporating these factors achieved an area under the curve (AUC) of 0.841 in the training dataset and 0.768 in the validation dataset. The M2 prediction model, which integrated the radscore from the 5 mm peritumoral area in the CECT arterial phase, α-fetoprotein level, enhancing capsule, and aspartate aminotransferase level achieved an AUC of 0.865 in the training dataset and 0.798 in the validation dataset. Calibration and decision curve analyses confirmed the models' good fit and clinical utility. CONCLUSION Multivariable models were constructed by combining clinicoradiological risk factors and radscores to preoperatively predict MVI and identify M2 among patients with HBV-HCC. Further studies are needed to evaluate the practical application of these models in clinical settings.
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Affiliation(s)
- Zi-Ling Xu
- Department of General Surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei 230001, Anhui Province, China
| | - Gui-Xiang Qian
- Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
| | - Yong-Hai Li
- Department of Anorectal Surgery, The First People's Hospital of Hefei, Hefei 230001, Anhui Province, China
| | - Jian-Lin Lu
- Department of General Surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei 230001, Anhui Province, China
| | - Ming-Tong Wei
- Department of General Surgery, Anhui Provincial Hospital Affiliated to Anhui Medical University, Hefei 230001, Anhui Province, China
| | - Xiang-Yi Bu
- Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
| | - Yong-Sheng Ge
- Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
| | - Yuan Cheng
- Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
| | - Wei-Dong Jia
- Department of General Surgery, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Science and Medicine, University of Science and Technology of China, Hefei 230001, Anhui Province, China
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Lee JS, Choi HW, Kim JS, Lee TY, Yoon YC. Update on Resection Strategies for Hepatocellular Carcinoma: A Narrative Review. Cancers (Basel) 2024; 16:4093. [PMID: 39682279 DOI: 10.3390/cancers16234093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2024] [Accepted: 12/03/2024] [Indexed: 12/18/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer, the incidence of which is rising globally. Despite recent advancements in immunotherapeutic and surgical treatment modalities, the prognosis for HCC remains poor. The surgical treatment strategy for HCC comprises a multimodal effort that ranges from ablative therapy and surgical resection to liver transplantation. Thanks to collective efforts from the surgical society, there have been rapid advances in resection strategies, such as 3D printing for surgical planning and minimally invasive techniques to minimize surgical trauma. This review examines recent advancements in surgical techniques, patient selection criteria, and perioperative management for HCC resection. The purpose of this review was to provide clinicians and researchers with an up-to-date perspective on the evolving role of surgical resection in HCC treatment, and to identify key areas for future investigation to improve patient outcomes.
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Affiliation(s)
- Jun Suh Lee
- Department of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Hyeong Woo Choi
- Department of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Ji Su Kim
- Department of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Tae Yoon Lee
- Department of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
| | - Young Chul Yoon
- Department of Surgery, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea
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Hui RWH, Chiu KWH, Lee IC, Wang C, Cheng HM, Lu J, Mao X, Yu S, Lam LK, Mak LY, Cheung TT, Chia NH, Cheung CC, Kan WK, Wong TCL, Chan ACY, Huang YH, Yuen MF, Yu PLH, Seto WK. Multimodal multiphasic preoperative image-based deep-learning predicts HCC outcomes after curative surgery. Hepatology 2024:01515467-990000000-01099. [PMID: 39626212 DOI: 10.1097/hep.0000000000001180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Accepted: 11/16/2024] [Indexed: 12/28/2024]
Abstract
BACKGROUND AND AIMS HCC recurrence frequently occurs after curative surgery. Histological microvascular invasion (MVI) predicts recurrence but cannot provide preoperative prognostication, whereas clinical prediction scores have variable performances. APPROACH AND RESULTS Recurr-NET, a multimodal multiphasic residual-network random survival forest deep-learning model incorporating preoperative CT and clinical parameters, was developed to predict HCC recurrence. Preoperative triphasic CT scans were retrieved from patients with resected histology-confirmed HCC from 4 centers in Hong Kong (internal cohort). The internal cohort was randomly divided in an 8:2 ratio into training and internal validation. External testing was performed in an independent cohort from Taiwan.Among 1231 patients (age 62.4y, 83.1% male, 86.8% viral hepatitis, and median follow-up 65.1mo), cumulative HCC recurrence rates at years 2 and 5 were 41.8% and 56.4%, respectively. Recurr-NET achieved excellent accuracy in predicting recurrence from years 1 to 5 (internal cohort AUROC 0.770-0.857; external AUROC 0.758-0.798), significantly outperforming MVI (internal AUROC 0.518-0.590; external AUROC 0.557-0.615) and multiple clinical risk scores (ERASL-PRE, ERASL-POST, DFT, and Shim scores) (internal AUROC 0.523-0.587, external AUROC: 0.524-0.620), respectively (all p < 0.001). Recurr-NET was superior to MVI in stratifying recurrence risks at year 2 (internal: 72.5% vs. 50.0% in MVI; external: 65.3% vs. 46.6% in MVI) and year 5 (internal: 86.4% vs. 62.5% in MVI; external: 81.4% vs. 63.8% in MVI) (all p < 0.001). Recurr-NET was also superior to MVI in stratifying liver-related and all-cause mortality (all p < 0.001). The performance of Recurr-NET remained robust in subgroup analyses. CONCLUSIONS Recurr-NET accurately predicted HCC recurrence, outperforming MVI and clinical prediction scores, highlighting its potential in preoperative prognostication.
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Affiliation(s)
- Rex Wan-Hin Hui
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | | | - I-Cheng Lee
- Department of Medicine, Division of Gastroenterology and Hepatology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chenlu Wang
- Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong
| | - Ho-Ming Cheng
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Jianliang Lu
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Xianhua Mao
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Sarah Yu
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Lok-Ka Lam
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Lung-Yi Mak
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
| | - Tan-To Cheung
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
- Department of Surgery, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Nam-Hung Chia
- Department of Surgery, Queen Elizabeth Hospital, Hong Kong
| | | | - Wai-Kuen Kan
- Department of Radiology, Pamela Youde Nethersole Eastern Hospital, Hong Kong
| | - Tiffany Cho-Lam Wong
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
- Department of Surgery, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Albert Chi-Yan Chan
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
- Department of Surgery, School of Clinical Medicine, The University of Hong Kong, Hong Kong
| | - Yi-Hsiang Huang
- Department of Medicine, Division of Gastroenterology and Hepatology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Healthcare and Services Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Man-Fung Yuen
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
| | - Philip Leung-Ho Yu
- Department of Mathematics and Information Technology, The Education University of Hong Kong, Hong Kong
| | - Wai-Kay Seto
- Department of Medicine, School of Clinical Medicine, The University of Hong Kong, Hong Kong
- State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong
- Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
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Zhang L, Dang N, Wang J, Zhang W, Hu X, Jiang B, Zhao D, Liu F, Yuan H. ZNF143-mediated upregulation of MEX3C promotes hepatocellular carcinoma progression. Clin Res Hepatol Gastroenterol 2024; 48:102492. [PMID: 39488269 DOI: 10.1016/j.clinre.2024.102492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2024] [Revised: 10/18/2024] [Accepted: 10/30/2024] [Indexed: 11/04/2024]
Abstract
BACKGROUND Microvascular invasion is strongly associated with aggressive tumor behavior and recurrence in hepatocellular carcinoma (HCC) patients. Zinc finger protein 143(ZNF143) is a transcription factor involved in a wide variety of physiological and developmental processes. This study primarily focuses on the exact biological role and mechanism of ZNF143 in HCC migration and invasion. METHODS The expression and prognosis of ZNF143 in HCC patients were analyzed. The levels of ZNF143, mex-3 RNA binding family member C (MEX3C) were quantified by western blot and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cell migration ability was detected by wound- healing assay. Matrigel transwell assay was conducted to evaluate the invasion of HCC cells. The differential expression genes of ZNF143 overexpression and knockdown were screened by mRNA profiling analysis. Dual luciferase assay was performed to determine the promoter activity of MEX3C. The enrichment of ZNF143 at MEX3C promoter was determined by chromatin immunoprecipitation (ChIP). RESULTS ZNF143 is overexpressed in HCC tissues and that its overexpression is correlated with poorer prognosis, especially in HCC patients with higher tumor grades and microvascular invasion. Gain- and loss-of function experiments showed that ZNF143 promotes migration and invasion in HCC cells. mRNA profiling showed that ZNF143 significantly upregulates MEX3C. ZNF143 was positively correlated with MEX3C expression in HCC tissue. ZNF143 activates MEX3C transcription by directly binding to its promoter. MEX3C knockdown inhibited migration and invasion induced by ZNF143 overexpression in HCC cells. CONCLUSION ZNF143 promotes HCC cell migration and invasion by binding to MEX3C promoter and activating its expression.
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Affiliation(s)
- Lili Zhang
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Nan Dang
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Jiongyi Wang
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Wenying Zhang
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Xiaohua Hu
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Bin Jiang
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China
| | - Dan Zhao
- Department of Digestive Medicine, Zhengzhou Third People's Hospital, Zhengzhou, Henan Province, 450000, China.
| | - Feng Liu
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China.
| | - Haihua Yuan
- Department of Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao tong University School of Medicine, Shanghai, 201900, China.
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Wu F, Cao G, Lu J, Ye S, Tang X. Correlation between 18 F-FDG PET/CT metabolic parameters and microvascular invasion before liver transplantation in patients with hepatocellular carcinoma. Nucl Med Commun 2024; 45:1033-1038. [PMID: 39267532 PMCID: PMC11537472 DOI: 10.1097/mnm.0000000000001897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Accepted: 08/30/2024] [Indexed: 09/17/2024]
Abstract
BACKGROUND Microvascular infiltration (MVI) before liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) is associated with postoperative tumor recurrence and survival. MVI is mainly assessed by pathological analysis of tissue samples, which is invasive and heterogeneous. PET/computed tomography (PET/CT) with 18 F-labeled fluorodeoxyglucose ( 18 F-FDG) as a tracer has been widely used in the examination of malignant tumors. This study investigated the association between 18 F-FDG PET/CT metabolic parameters and MVI before LT in HCC patients. METHODS About 124 HCC patients who had 18 F-FDG PET/CT examination before LT were included. The patients' clinicopathological features and 18 F-FDG PET/CT metabolic parameters were recorded. Correlations between clinicopathological features, 18 F-FDG PET/CT metabolic parameters, and MVI were analyzed. ROC curve was used to determine the optimal diagnostic cutoff value, area under the curve (AUC), sensitivity, and specificity for predictors of MVI. RESULT In total 72 (58.06%) patients were detected with MVI among the 124 HCC patients. Univariate analysis showed that tumor size ( P = 0.001), T stage ( P < 0.001), maximum standardized uptake value (SUV max ) ( P < 0.001), minimum standardized uptake value (SUV min ) ( P = 0.031), mean standardized uptake value (SUV mean ) ( P = 0.001), peak standardized uptake value (SUV peak ) ( P = 0.001), tumor-to-liver ratio (SUV ratio ) ( P = 0.010), total lesion glycolysis (TLG) ( P = 0.006), metabolic tumor volume (MTV) ( P = 0.011) and MVI were significantly different. Multivariate logistic regression showed that tumor size ( P = 0.018), T stage ( P = 0.017), TLG ( P = 0.023), and MTV ( P = 0.015) were independent predictors of MVI. In the receiver operating characteristic curve, TLG predicted MVI with an AUC value of 0.645. MTV predicted MVI with an AUC value of 0.635. Patients with tumor size ≥5 cm, T3-4, TLG > 400.67, and MTV > 80.58 had a higher incidence of MVI. CONCLUSION 18 F-FDG PET/CT metabolic parameters correlate with MVI and may be used as a noninvasive technique to predict MVI before LT in HCC patients.
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Affiliation(s)
- Fan Wu
- Department of Nuclear Medicine and Radiology, Shulan (Hangzhou) Hospital, Shulan International Medical College, Zhejiang Shuren University
| | - Guohong Cao
- Department of Nuclear Medicine and Radiology, Shulan (Hangzhou) Hospital, Shulan International Medical College, Zhejiang Shuren University
| | - Jinlan Lu
- Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital
| | - Shengli Ye
- Department of Nuclear Medicine and Radiology, Shulan (Hangzhou) Hospital, Shulan International Medical College, Zhejiang Shuren University
| | - Xin Tang
- Department of Radiology, Hangzhou Wuyunshan Hospital, Hangzhou Health Promotion Research Institute, Hangzhou, China
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Wang F, Numata K, Funaoka A, Kumamoto T, Takeda K, Chuma M, Nozaki A, Ruan L, Maeda S. Construction of a nomogram combining CEUS and MRI imaging for preoperative diagnosis of microvascular invasion in hepatocellular carcinoma. Eur J Radiol Open 2024; 13:100587. [PMID: 39070064 PMCID: PMC11279689 DOI: 10.1016/j.ejro.2024.100587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/22/2024] [Accepted: 06/30/2024] [Indexed: 07/30/2024] Open
Abstract
Purpose To use Sonazoid contrast-enhanced ultrasound (S-CEUS) and Gadolinium-Ethoxybenzyl-Diethylenetriamine Penta-Acetic Acid magnetic-resonance imaging (EOB-MRI), exploring a non-invasive preoperative diagnostic strategy for microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods 111 newly developed HCC cases were retrospectively collected. Both S-CEUS and EOB-MRI examinations were performed within one month of hepatectomy. The following indicators were investigated: size; vascularity in three phases of S-CEUS; margin, signal intensity, and peritumoral wedge shape in EOB-MRI; tumoral homogeneity, presence and integrity of the tumoral capsule in S-CEUS or EOB-MRI; presence of branching enhancement in S-CEUS; baseline clinical and serological data. The least absolute shrinkage and selection operator regression and multivariate logistic regression analysis were applied to optimize feature selection for the model. A nomogram for MVI was developed and verified by bootstrap resampling. Results Of the 16 variables we included, wedge and margin in HBP of EOB-MRI, capsule integrity in AP or HBP/PVP images of EOB-MRI/S-CEUS, and branching enhancement in AP of S-CEUS were identified as independent risk factors for MVI and incorporated into construction of the nomogram. The nomogram achieved an excellent diagnostic efficiency with an area under the curve of 0.8434 for full data training set and 0.7925 for bootstrapping validation set for 500 repetitions. In evaluating the nomogram, Hosmer-Lemeshow test for training set exhibited a good model fit with P > 0.05. Decision curve analysis of nomogram model yielded excellent clinical net benefit with a wide range (5-80 % and 85-94 %) of risk threshold. Conclusions The MVI Nomogram established in this study may provide a strategy for optimizing the preoperative diagnosis of MVI, which in turn may improve the treatment and prognosis of MVI-related HCC.
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Affiliation(s)
- Feiqian Wang
- Ultrasound Department, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277 West Yanta Road, Xi’an, Shaanxi 710061, PR China
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Kazushi Numata
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Akihiro Funaoka
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Takafumi Kumamoto
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Kazuhisa Takeda
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Makoto Chuma
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Akito Nozaki
- Gastroenterological Center, Yokohama City University Medical Center, 4-57 Urafune-cho, Minami-ku, Yokohama, Kanagawa 232-0024, Japan
| | - Litao Ruan
- Ultrasound Department, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277 West Yanta Road, Xi’an, Shaanxi 710061, PR China
| | - Shin Maeda
- Division of Gastroenterology, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
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Gou J, Li J, Li Y, Lu M, Wang C, Zhuo Y, Dong X. The Diagnostic Accuracy Between Radiomics Model and Non-radiomics Model for Preoperative of Microvascular Invasion of Solitary Hepatocellular Carcinoma: A Systematic Review and Meta-analysis. Acad Radiol 2024; 31:4419-4433. [PMID: 38664142 DOI: 10.1016/j.acra.2024.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 04/01/2024] [Accepted: 04/05/2024] [Indexed: 11/01/2024]
Abstract
RATIONALE AND OBJECTIVES Microvascular invasion (MVI) is a key prognostic factor for hepatocellular carcinoma (HCC). The predictive models for solitary HCC could potentially integrate more comprehensive tumor information. Owing to the diverse findings across studies, we aimed to compare radiomic and non-radiomic methods for preoperative MVI detection in solitary HCC. MATERIALS AND METHODS Articles were reviewed from databases including PubMed, Embase, Web of Science, and the Cochrane Library until April 7, 2023. The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were calculated using a random-effects model within a 95% confidence interval (CI). Diagnostic accuracy was assessed using summary receiver-operating characteristic curves and the area under the curve (AUC). Meta-regression and Z-tests identified heterogeneity and compared the predictive accuracy. Subgroup analyses were performed to compare the AUC of two methods according to study type, study design, tumor size, modeling methods, and imaging modality. RESULTS The analysis incorporated 26 studies involving 3539 patients with solitary HCC. The radiomics models showed a pooled sensitivity and specificity of 0.79 (95%CI: 0.72-0.85) and 0.78 (95%CI: 0.73-0.82), with an AUC at 0.85 (95%CI: 0.82-0.88). Conversely, the non-radiomics models had sensitivity and specificity of 0.74 (95%CI: 0.65-0.81) and 0.88 (95%CI: 0.82-0.92) and an AUC of 0.88 (95%CI: 0.85-0.91). Subgroups with preoperative MRI, larger tumors, and functional imaging had higher accuracy than those using preoperative CT, smaller tumors, and conventional imaging. CONCLUSION Non-radiomic methods outperformed radiomic methods, but high heterogeneity calls across studies for cautious interpretation.
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Affiliation(s)
- Junjiu Gou
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Jingqi Li
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Yingfeng Li
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Mingjie Lu
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Chen Wang
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Yi Zhuo
- The Clinical Medical College, Guizhou Medical University, Guiyang 550004, Guizhou Province, China
| | - Xue Dong
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.
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Rhee H, Park YN, Choi JY. Advances in Understanding Hepatocellular Carcinoma Vasculature: Implications for Diagnosis, Prognostication, and Treatment. Korean J Radiol 2024; 25:887-901. [PMID: 39344546 PMCID: PMC11444852 DOI: 10.3348/kjr.2024.0307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 07/27/2024] [Accepted: 07/31/2024] [Indexed: 10/01/2024] Open
Abstract
Hepatocellular carcinoma (HCC) progresses through multiple stages of hepatocarcinogenesis, with each stage characterized by specific changes in vascular supply, drainage, and microvascular structure. These vascular changes significantly influence the imaging findings of HCC, enabling non-invasive diagnosis. Vascular changes in HCC are closely related to aggressive histological characteristics and treatment responses. Venous drainage from the tumor toward the portal vein in the surrounding liver facilitates vascular invasion, and the unique microvascular pattern of vessels that encapsulate the tumor cluster (known as a VETC pattern) promotes vascular invasion and metastasis. Systemic treatments for HCC, which are increasingly being used, primarily target angiogenesis and immune checkpoint pathways, which are closely intertwined. By understanding the complex relationship between histopathological vascular changes in hepatocarcinogenesis and their implications for imaging findings, radiologists can enhance the accuracy of imaging diagnosis and improve the prediction of prognosis and treatment response. This, in turn, will ultimately lead to better patient care.
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Affiliation(s)
- Hyungjin Rhee
- Department of Radiology, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
- Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Republic of Korea
| | - Young Nyun Park
- Department of Pathology, Graduate School of Medical Science, Brain Korea 21 Project, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin-Young Choi
- Department of Radiology, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
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Yoon JK, Han DH, Lee S, Choi JY, Choi GH, Kim DY, Kim MJ. Intraindividual comparison of prognostic imaging features of HCCs between MRIs with extracellular and hepatobiliary contrast agents. Liver Int 2024; 44:2847-2857. [PMID: 39105495 DOI: 10.1111/liv.16059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 07/18/2024] [Accepted: 07/24/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND & AIMS Accumulating evidence suggests that certain imaging features of hepatocellular carcinoma (HCC) may have prognostic implications. This study aimed to intraindividually compare MRIs with extracellular contrast agent (ECA-MRI) and hepatobiliary agent (HBA-MRI) for prognostic imaging features of HCC and to compare the prediction of microvascular invasion (MVI) and early recurrence between the two MRIs. METHODS The present study included 102 prospectively enrolled at-risk patients (median age, 61.0 years; 83 men) with surgically resected single HCC with both preoperative ECA-MRI and HBA-MRI between July 2019 and June 2023. The McNemar test was used to compare each prognostic imaging feature between the two MRIs. Significant imaging features associated with MVI were identified by multivariable logistic regression analysis, and early recurrence rates (<2 years) were compared between the two MRIs. RESULTS The frequencies of prognostic imaging features were not significantly different between the two MRIs (p = .07 to >.99). Non-smooth tumour margin (ECA-MRI, odds ratio [OR] = 5.30; HBA-MRI, OR = 7.07) and peritumoral arterial phase hyperenhancement (ECA-MRI, OR = 4.26; HBA-MRI, OR = 4.43) were independent factors significantly associated with MVI on both MRIs. Two-trait predictor of venous invasion (presence of internal arteries and absence of hypoattenuating halo) on ECA-MRI (OR = 11.24) and peritumoral HBP hypointensity on HBA-MRI (OR = 20.42) were other predictors of MVI. Early recurrence rates of any two or more significant imaging features (49.8% on ECA-MRI vs 51.3% on HBA-MRI, p = .75) were not significantly different between the two MRIs. CONCLUSION Prognostic imaging features of HCC may be comparable between ECA-MRI and HBA-MRI.
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Affiliation(s)
- Ja Kyung Yoon
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dai Hoon Han
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin-Young Choi
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Gi Hong Choi
- Department of Surgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Do Young Kim
- Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Myeong-Jin Kim
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
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Birgin E, Nebelung H, Abdelhadi S, Rink JS, Froelich MF, Hetjens S, Rahbari M, Téoule P, Rasbach E, Reissfelder C, Weitz J, Schoenberg SO, Riediger C, Plodeck V, Rahbari NN. Development and validation of a digital biopsy model to predict microvascular invasion in hepatocellular carcinoma. Front Oncol 2024; 14:1360936. [PMID: 39376989 PMCID: PMC11457731 DOI: 10.3389/fonc.2024.1360936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2023] [Accepted: 08/30/2024] [Indexed: 10/09/2024] Open
Abstract
Background Microvascular invasion is a major histopathological risk factor of postoperative recurrence in patients with hepatocellular carcinoma. This study aimed to develop and validate a digital biopsy model using imaging features to predict microvascular invasion before hepatectomy. Methods A total of 217 consecutive patients who underwent hepatectomy for resectable hepatocellular carcinoma were enrolled at two tertiary-care reference centers. An imaging-based digital biopsy model was developed and internally validated using logistic regression analysis with adjustments for age, sex, etiology of disease, size and number of lesions. Results Three imaging features, i.e., non-smoothness of lesion margin (OR = 16.40), ill-defined pseudocapsula (OR = 4.93), and persistence of intratumoral internal artery (OR = 10.50), were independently associated with microvascular invasion and incorporated into a prediction model. A scoring system with 0 - 3 points was established for the prediction model. Internal validation confirmed an excellent calibration of the model. A cutoff of 2 points indicates a high risk of microvascular invasion (area under the curve 0.87). The overall survival and recurrence-free survival stratified by the risk model was significantly shorter in patients with high risk features of microvascular invasion compared to those patients with low risk of microvascular invasion (overall survival: median 35 vs. 75 months, P = 0.027; recurrence-free survival: median 17 vs. 38 months, P < 0.001)). Conclusion A preoperative assessment of microvascular invasion by digital biopsy is reliable, easily applicable, and might facilitate personalized treatment strategies.
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Affiliation(s)
- Emrullah Birgin
- Department of General and Visceral Surgery, University Hospital Ulm, Ulm, Germany
| | - Heiner Nebelung
- Department of Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Schaima Abdelhadi
- Department of Surgery, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Johann S. Rink
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
| | - Matthias F. Froelich
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
| | - Svetlana Hetjens
- Department of Medical Statistics and Biomathematics, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mohammad Rahbari
- Department of Surgery, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Patrick Téoule
- Department of Surgery, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Erik Rasbach
- Department of Surgery, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Christoph Reissfelder
- Department of Surgery, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- DKFZ Hector Cancer Institute at the University Medical Center Mannheim, Mannheim, Germany
| | - Jürgen Weitz
- Department of Visceral-, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Stefan O. Schoenberg
- Department of Radiology and Nuclear Medicine, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
| | - Carina Riediger
- Department of Visceral-, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Verena Plodeck
- Department of Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Nuh N. Rahbari
- Department of General and Visceral Surgery, University Hospital Ulm, Ulm, Germany
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Zhong Y, Chen L, Ding F, Ou W, Zhang X, Weng S. Assessing microvascular invasion in HBV-related hepatocellular carcinoma: an online interactive nomogram integrating inflammatory markers, radiomics, and convolutional neural networks. Front Oncol 2024; 14:1401095. [PMID: 39351352 PMCID: PMC11439624 DOI: 10.3389/fonc.2024.1401095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 08/22/2024] [Indexed: 10/04/2024] Open
Abstract
Objective The early recurrence of hepatocellular carcinoma (HCC) correlates with decreased overall survival. Microvascular invasion (MVI) stands out as a prominent hazard influencing post-resection survival status and metastasis in patients with HBV-related HCC. The study focused on developing a web-based nomogram for preoperative prediction of MVI in HBV-HCC. Materials and methods 173 HBV-HCC patients from 2017 to 2022 with complete preoperative clinical data and Gadopentetate dimeglumine-enhanced magnetic resonance images were randomly divided into two groups for the purpose of model training and validation, using a ratio of 7:3. MRI signatures were extracted by pyradiomics and the deep neural network, 3D ResNet. Clinical factors, blood-cell-inflammation markers, and MRI signatures selected by LASSO were incorporated into the predictive nomogram. The evaluation of the predictive accuracy involved assessing the area under the receiver operating characteristic (ROC) curve (AUC), the concordance index (C-index), along with analyses of calibration and decision curves. Results Inflammation marker, neutrophil-to-lymphocyte ratio (NLR), was positively correlated with independent MRI radiomics risk factors for MVI. The performance of prediction model combined serum AFP, AST, NLR, 15 radiomics features and 7 deep features was better than clinical and radiomics models. The combined model achieved C-index values of 0.926 and 0.917, with AUCs of 0.911 and 0.907, respectively. Conclusion NLR showed a positive correlation with MRI radiomics and deep learning features. The nomogram, incorporating NLR and MRI features, accurately predicted individualized MVI risk preoperatively.
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Affiliation(s)
- Yun Zhong
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Lingfeng Chen
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Fadian Ding
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Wenshi Ou
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Xiang Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Shangeng Weng
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Abdominal Surgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Hepatobiliary and Pancreatic Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Provincial Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
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Saleh GA, Denewar FA, Ali KM, Saleh M, Ali MA, Shehta A, Mansour M. Inter-observer reliability and predictive values of triphasic computed tomography for microvascular invasion in hepatocellular carcinoma. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2024; 55:176. [DOI: 10.1186/s43055-024-01354-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 08/28/2024] [Indexed: 02/11/2025] Open
Abstract
Abstract
Background
Hepatocellular carcinoma (HCC) is the most frequent primary liver tumor globally and a leading cause of mortality in cirrhotic patients. Our study aimed to estimate the diagnostic performance of triphasic CT and inter-observer reliability in the preoperative detection of microvascular invasion (MVI) in HCC. Two independent radiologists accomplished a retrospective analysis for 99 patients with HCC to assess the CT features for MVI in each lesion. Postoperative histopathology was considered the gold standard.
Results
Multivariate regression analysis revealed that incomplete or absent tumor capsules, presence of TTPV, and absence of hypodense halo were statistically significant independent predictors of MVI. There was excellent agreement among observers in evaluating peritumoral enhancement, identifying intratumoral arteries, hypodense halo, TTPV, and macrovascular invasion. Also, our results revealed moderate agreement in assessing the tumor margin and tumor capsule.
Conclusion
Triphasic CT features of MVI are reliable imaging predictors that may be helpful for standard preoperative interpretation of HCC.
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Laurent-Bellue A, Sadraoui A, Claude L, Calderaro J, Posseme K, Vibert E, Cherqui D, Rosmorduc O, Lewin M, Pesquet JC, Guettier C. Deep Learning Classification and Quantification of Pejorative and Nonpejorative Architectures in Resected Hepatocellular Carcinoma from Digital Histopathologic Images. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:1684-1700. [PMID: 38879083 DOI: 10.1016/j.ajpath.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/17/2024] [Accepted: 05/16/2024] [Indexed: 06/27/2024]
Abstract
Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of recurrence critical. Microvascular invasion (mVI), poor differentiation, pejorative macrotrabecular architectures, and vessels encapsulating tumor clusters architectures are the most accurate histologic predictors of recurrence, but their evaluation is time-consuming and imperfect. Herein, a supervised deep learning-based approach with ResNet34 on 680 whole slide images (WSIs) from 107 liver resection specimens was used to build an algorithm for the identification and quantification of these pejorative architectures. This model achieved an accuracy of 0.864 at patch level and 0.823 at WSI level. To assess its robustness, it was validated on an external cohort of 29 HCCs from another hospital, with an accuracy of 0.787 at WSI level, affirming its generalization capabilities. Moreover, the largest connected areas of the pejorative architectures extracted from the model were positively correlated to the presence of mVI and the number of tumor emboli. These results suggest that the identification of pejorative architectures could be an efficient surrogate of mVI and have a strong predictive value for the risk of recurrence. This study is the first step in the construction of a composite predictive algorithm for early post-resection recurrence of HCC, including artificial intelligence-based features.
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Affiliation(s)
- Astrid Laurent-Bellue
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Aymen Sadraoui
- Centre de Vision Numérique, Paris-Saclay University, Inria, CentraleSupélec, Gif-sur-Yvette, France
| | - Laura Claude
- Department of Pathology, Charles Nicolle Hospital, Rouen, France
| | - Julien Calderaro
- Department of Pathology, Henri-Mondor Hospital, Assistance Publique-Hôpitaux de Paris, Créteil, France
| | - Katia Posseme
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Eric Vibert
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Daniel Cherqui
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Olivier Rosmorduc
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Maïté Lewin
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Jean-Christophe Pesquet
- Centre de Vision Numérique, Paris-Saclay University, Inria, CentraleSupélec, Gif-sur-Yvette, France
| | - Catherine Guettier
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France.
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Chen JL, Chen YS, Hsieh KC, Lee HM, Chen CY, Chen JH, Hung CM, Hsu CT, Huang YL, Ker CG. Clinical Nomogram Model for Pre-Operative Prediction of Microvascular Invasion of Hepatocellular Carcinoma before Hepatectomy. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:1410. [PMID: 39336451 PMCID: PMC11433876 DOI: 10.3390/medicina60091410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 08/09/2024] [Accepted: 08/21/2024] [Indexed: 09/30/2024]
Abstract
Background and Objectives: Microvascular invasion (MVI) significantly impacts recurrence and survival rates after liver resection in hepatocellular carcinoma (HCC). Pre-operative prediction of MVI is crucial in determining the treatment strategy. This study aims to develop a nomogram model to predict the probability of MVI based on clinical features in HCC patients. Materials and Methods: A total of 489 patients with a pathological diagnosis of HCC were enrolled from our hospital. Those registered from 2012-2015 formed the derivation cohort, and those from 2016-2019 formed the validation cohort for pre-operative prediction of MVI. A nomogram model for prediction was created using a regression model, with risk factors derived from clinical and tumor-related features before surgery. Results: Using the nomogram model to predict the odds ratio of MVI before hepatectomy, the AFP, platelet count, GOT/GPT ratio, albumin-alkaline phosphatase ratio, ALBI score, and GNRI were identified as significant variables for predicting MVI. The Youden index scores for each risk variable were 0.287, 0.276, 0.196, 0.185, 0.115, and 0.112, respectively, for the AFP, platelet count, GOT/GPT ratio, AAR, ALBI, and GNRI. The maximum value of the total nomogram scores was 220. An increase in the number of nomogram points indicated a higher probability of MVI occurrence. The accuracy rates ranged from 55.9% to 64.4%, and precision rates ranged from 54.3% to 68.2%. Overall survival rates were 97.6%, 83.4%, and 73.9% for MVI(-) and 80.0%, 71.8%, and 41.2% for MVI(+) (p < 0.001). The prognostic effects of MVI(+) on tumor-free survival and overall survival were poor in both the derivation and validation cohorts. Conclusions: Our nomogram model, which integrates clinical factors, showed reliable calibration for predicting MVI and provides a useful tool enabling surgeons to estimate the probability of MVI before resection. Consequently, surgical strategies and post-operative care programs can be adapted to improve the prognosis of HCC patients where possible.
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Affiliation(s)
- Jen-Lung Chen
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Yaw-Sen Chen
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Kun-Chou Hsieh
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Hui-Ming Lee
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Chung-Yen Chen
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Jian-Han Chen
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
| | - Chao-Ming Hung
- Department of General Surgery, E-Da Cancer Hospital, I-Shou University, Kaohsiung 824, Taiwan;
| | - Chao-Tien Hsu
- Department of Pathology, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan;
| | - Ya-Ling Huang
- Cancer Registration Center, E-Da Cancer Hospital, I-Shou University, Kaohsiung 824, Taiwan;
| | - Chen-Guo Ker
- Department of General Surgery, E-Da Hospital, I-Shou University, Kaohsiung 824, Taiwan; (J.-L.C.); (Y.-S.C.); (K.-C.H.); (H.-M.L.); (C.-Y.C.); (J.-H.C.)
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Xu JY, Yang YF, Huang ZY, Qian XY, Meng FH. Preoperative prediction of hepatocellular carcinoma microvascular invasion based on magnetic resonance imaging feature extraction artificial neural network. World J Gastrointest Surg 2024; 16:2546-2554. [PMID: 39220077 PMCID: PMC11362924 DOI: 10.4240/wjgs.v16.i8.2546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 05/29/2024] [Accepted: 06/27/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) recurrence is highly correlated with increased mortality. Microvascular invasion (MVI) is indicative of aggressive tumor biology in HCC. AIM To construct an artificial neural network (ANN) capable of accurately predicting MVI presence in HCC using magnetic resonance imaging. METHODS This study included 255 patients with HCC with tumors < 3 cm. Radiologists annotated the tumors on the T1-weighted plain MR images. Subsequently, a three-layer ANN was constructed using image features as inputs to predict MVI status in patients with HCC. Postoperative pathological examination is considered the gold standard for determining MVI. Receiver operating characteristic analysis was used to evaluate the effectiveness of the algorithm. RESULTS Using the bagging strategy to vote for 50 classifier classification results, a prediction model yielded an area under the curve (AUC) of 0.79. Moreover, correlation analysis revealed that alpha-fetoprotein values and tumor volume were not significantly correlated with the occurrence of MVI, whereas tumor sphericity was significantly correlated with MVI (P < 0.01). CONCLUSION Analysis of variable correlations regarding MVI in tumors with diameters < 3 cm should prioritize tumor sphericity. The ANN model demonstrated strong predictive MVI for patients with HCC (AUC = 0.79).
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Affiliation(s)
- Jing-Yi Xu
- Center of Hepatobiliary Pancreatic Disease, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
| | - Yu-Fan Yang
- Center of Hepatobiliary Pancreatic Disease, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
| | - Zhong-Yue Huang
- Department of Surgical, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
| | - Xin-Ye Qian
- Center of Hepatobiliary Pancreatic Disease, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China
| | - Fan-Hua Meng
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai 200040, China
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Li H, Zhang D, Pei J, Hu J, Li X, Liu B, Wang L. Dual-energy computed tomography iodine quantification combined with laboratory data for predicting microvascular invasion in hepatocellular carcinoma: a two-centre study. Br J Radiol 2024; 97:1467-1475. [PMID: 38870535 PMCID: PMC11256957 DOI: 10.1093/bjr/tqae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 05/16/2024] [Accepted: 06/05/2024] [Indexed: 06/15/2024] Open
Abstract
OBJECTIVES Microvascular invasion (MVI) is a recognized biomarker associated with poorer prognosis in patients with hepatocellular carcinoma. Dual-energy computed tomography (DECT) is a highly sensitive technique that can determine the iodine concentration (IC) in tumour and provide an indirect evaluation of internal microcirculatory perfusion. This study aimed to assess whether the combination of DECT with laboratory data can improve preoperative MVI prediction. METHODS This retrospective study enrolled 119 patients who underwent DECT liver angiography at 2 medical centres preoperatively. To compare DECT parameters and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied across MVI groups. Finally, a general linear classifier was used to assess the classification ability of each PC score. RESULTS Significant differences were noted (P < .05) in alpha-fetoprotein (AFP) level, normalized arterial phase IC, and normalized portal phase IC between the MVI groups in the primary and validation datasets. The PC1-PC4 accounted for 67.9% of the variance in the primary dataset, with loadings of 24.1%, 16%, 15.4%, and 12.4%, respectively. In both primary and validation datasets, PC3 and PC4 were significantly different across MVI groups, with area under the curve values of 0.8410 and 0.8373, respectively. CONCLUSIONS The recombination of DECT IC and laboratory features based on varying factor loadings can well predict MVI preoperatively. ADVANCES IN KNOWLEDGE Utilizing PCA, the amalgamation of DECT IC and laboratory features, considering diverse factor loadings, showed substantial promise in accurately classifying MVI. There have been limited endeavours to establish such a combination, offering a novel paradigm for comprehending data in related research endeavours.
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Affiliation(s)
- Huan Li
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
- Medical Imaging Research Center, Anhui Medical University, Hefei, Anhui 230601, China
| | - Dai Zhang
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
- Medical Imaging Research Center, Anhui Medical University, Hefei, Anhui 230601, China
| | - Jinxia Pei
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
- Medical Imaging Research Center, Anhui Medical University, Hefei, Anhui 230601, China
| | - Jingmei Hu
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
- Medical Imaging Research Center, Anhui Medical University, Hefei, Anhui 230601, China
| | - Xiaohu Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
| | - Bin Liu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
| | - Longsheng Wang
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230601, China
- Medical Imaging Research Center, Anhui Medical University, Hefei, Anhui 230601, China
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Altaf A, Endo Y, Munir MM, Khan MMM, Rashid Z, Khalil M, Guglielmi A, Ratti F, Marques H, Cauchy F, Lam V, Poultsides G, Kitago M, Popescu I, Martel G, Gleisner A, Hugh T, Shen F, Endo I, Pawlik TM. Impact of an artificial intelligence based model to predict non-transplantable recurrence among patients with hepatocellular carcinoma. HPB (Oxford) 2024; 26:1040-1050. [PMID: 38796346 DOI: 10.1016/j.hpb.2024.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 05/09/2024] [Accepted: 05/12/2024] [Indexed: 05/28/2024]
Abstract
OBJECTIVE We sought to develop Artificial Intelligence (AI) based models to predict non-transplantable recurrence (NTR) of hepatocellular carcinoma (HCC) following hepatic resection (HR). METHODS HCC patients who underwent HR between 2000-2020 were identified from a multi-institutional database. NTR was defined as recurrence beyond Milan Criteria. Different machine learning (ML) and deep learning (DL) techniques were used to develop and validate two prediction models for NTR, one using only preoperative factors and a second using both preoperative and postoperative factors. RESULTS Overall, 1763 HCC patients were included. Among 877 patients with recurrence, 364 (41.5%) patients developed NTR. An ensemble AI model demonstrated the highest area under ROC curves (AUC) of 0.751 (95% CI: 0.719-0.782) and 0.717 (95% CI:0.653-0.782) in the training and testing cohorts, respectively which improved to 0.858 (95% CI: 0.835-0.884) and 0.764 (95% CI: 0.704-0.826), respectively after incorporation of postoperative pathologic factors. Radiologic tumor burden score and pathological microvascular invasion were the most important preoperative and postoperative factors, respectively to predict NTR. Patients predicted to develop NTR had overall 1- and 5-year survival of 75.6% and 28.2%, versus 93.4% and 55.9%, respectively, among patients predicted to not develop NTR (p < 0.0001). CONCLUSION The AI preoperative model may help inform decision of HR versus LT for HCC, while the combined AI model can frame individualized postoperative care (https://altaf-pawlik-hcc-ntr-calculator.streamlit.app/).
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Affiliation(s)
- Abdullah Altaf
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Yutaka Endo
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Muhammad M Munir
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Muhammad Muntazir M Khan
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Zayed Rashid
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Mujtaba Khalil
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | | | | | - Hugo Marques
- Department of Surgery, Curry Cabral Hospital, Lisbon, Portugal
| | - François Cauchy
- Department of Hepatobiliopancreatic Surgery, APHP, Beaujon Hospital, Clichy, France
| | - Vincent Lam
- Department of Surgery, Westmead Hospital, Sydney, NSW, Australia
| | - George Poultsides
- Department of Surgery, Stanford University, Stanford, CA, United States
| | - Minoru Kitago
- Department of Surgery, Keio University, Tokyo, Japan
| | - Irinel Popescu
- Department of Surgery, Fundeni Clinical Institute, Bucharest, Romania
| | | | - Ana Gleisner
- Department of Surgery, University of Colorado, Aurora, CO, United States
| | - Tom Hugh
- Department of Surgery, School of Medicine, The University of Sydney, Sydney, NSW, Australia
| | - Feng Shen
- Department of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Itaru Endo
- Department of Surgery, Yokohama City University School of Medicine, Yokohama, Japan
| | - Timothy M Pawlik
- Department of Surgery, Division of Surgical Oncology, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
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Fan W, Zhu B, Chen S, Wu Y, Zhao X, Qiao L, Huang Z, Tang R, Chen J, Lau WY, Chen M, Li J, Kuang M, Peng Z. Survival in Patients With Recurrent Intermediate-Stage Hepatocellular Carcinoma: Sorafenib Plus TACE vs TACE Alone Randomized Clinical Trial. JAMA Oncol 2024; 10:1047-1054. [PMID: 38900435 PMCID: PMC11190833 DOI: 10.1001/jamaoncol.2024.1831] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/29/2023] [Indexed: 06/21/2024]
Abstract
Importance Transarterial chemoembolization (TACE) is commonly used to treat patients with recurrent intermediate-stage hepatocellular carcinoma (HCC) and positive microvascular invasion (MVI); however, TACE alone has demonstrated unsatisfactory survival benefits. A previous retrospective study suggested that TACE plus sorafenib (SOR-TACE) may be a better therapeutic option compared with TACE alone. Objective To investigate the clinical outcomes of SOR-TACE vs TACE alone for patients with recurrent intermediate-stage HCC after R0 hepatectomy with positive MVI. Design, Setting, and Participants In this phase 3, open-label, multicenter randomized clinical trial, patients with recurrent intermediate-stage HCC and positive MVI were randomly assigned in a 1:1 ratio via a computerized minimization technique to either SOR-TACE treatment or TACE alone. This trial was conducted at 5 hospitals in China, and enrolled patients from October 2019 to December 2021, with a follow-up period of 24 months. Data were analyzed from June 2023 to September 2023. Interventions Randomization to on-demand TACE (conventional TACE: doxorubicin, 50 mg, mixed with lipiodol and gelatin sponge particles [diameter: 150-350 μm]; drug-eluting bead TACE: doxorubicin, 75 mg, mixed with drug-eluting particles [diameter: 100-300 μm or 300-500 μm]) (TACE group) or sorafenib, 400 mg, twice daily plus on-demand TACE (SOR-TACE group) (conventional TACE: doxorubicin, 50 mg, mixed with lipiodol and gelatin sponge particles [diameter, 150-350 μm]; drug-eluting bead TACE: doxorubicin, 75 mg, mixed with drug-eluting particles [diameter: 100-300 μm or 300-500 μm]). Main Outcomes and Measures The primary end point was overall survival by intention-to-treat analysis. Safety was assessed in patients who received at least 1 dose of study treatment. Results A total of 162 patients (median [range] age, 55 [28-75] years; 151 males [93.2%]), were randomly assigned to be treated with either SOR-TACE (n = 81) or TACE alone (n = 81). The median overall survival was significantly longer in the SOR-TACE group than in the TACE group (22.2 months vs 15.1 months; hazard ratio [HR], 0.55; P < .001). SOR-TACE also prolonged progression-free survival (16.2 months vs 11.8 months; HR, 0.54; P < .001), and improved the objective response rate when compared with TACE alone based on the modified Response Evaluation Criteria in Solid Tumors criteria (80.2% vs 58.0%; P = .002). Any grade adverse events were more common in the SOR-TACE group, but all adverse events responded well to treatment. No unexpected adverse events or treatment-related deaths occurred in this study. Conclusions and Relevance The results of this randomized clinical trial demonstrated that SOR-TACE achieved better clinical outcomes than TACE alone. These findings suggest that combined treatment should be used for patients with recurrent intermediate-stage HCC after R0 hepatectomy with positive MVI. Trial Registration ClinicalTrials.gov Identifier: NCT04103398.
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Affiliation(s)
- Wenzhe Fan
- Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Bowen Zhu
- Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shuling Chen
- Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yanqin Wu
- Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xiao Zhao
- Cancer Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Liangliang Qiao
- Department of Interventional Oncology, Jinshazhou Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhen Huang
- Department of Interventional Angiology, Huizhou First People’s Hospital, Huizhou, China
| | - Rong Tang
- Department of Hepatopancreatobiliary Surgery, Hainan General Hospital, Haikou, China
| | - Jinghua Chen
- Cancer Center, Guangzhou Twelfth People’s Hospital, Guangzhou, China
| | - Wan Yee Lau
- Faculty of Medicine, the Chinese University of Hong Kong, Prince of Wale Hospital, Shatin, New Territories, Hongkong, SAR, China
| | - Minshan Chen
- Department of Liver Surgery, Cancer Center of Sun Yat-sen University, Guangzhou, China
| | - Jiaping Li
- Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ming Kuang
- Center of Hepato-PancreatoBiliary Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhenwei Peng
- Cancer Center, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Wei G, Fang G, Guo P, Fang P, Wang T, Lin K, Liu J. Preoperative prediction of microvascular invasion risk in hepatocellular carcinoma with MRI: peritumoral versus tumor region. Insights Imaging 2024; 15:188. [PMID: 39090456 PMCID: PMC11294513 DOI: 10.1186/s13244-024-01760-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Accepted: 06/23/2024] [Indexed: 08/04/2024] Open
Abstract
OBJECTIVES To explore the predictive performance of tumor and multiple peritumoral regions on dynamic contrast-enhanced magnetic resonance imaging (MRI), to identify optimal regions of interest for developing a preoperative predictive model for the grade of microvascular invasion (MVI). METHODS A total of 147 patients who were surgically diagnosed with hepatocellular carcinoma, and had a maximum tumor diameter ≤ 5 cm were recruited and subsequently divided into a training set (n = 117) and a testing set (n = 30) based on the date of surgery. We utilized a pre-trained AlexNet to extract deep learning features from seven different regions of the maximum transverse cross-section of tumors in various MRI sequence images. Subsequently, an extreme gradient boosting (XGBoost) classifier was employed to construct the MVI grade prediction model, with evaluation based on the area under the curve (AUC). RESULTS The XGBoost classifier trained with data from the 20-mm peritumoral region showed superior AUC compared to the tumor region alone. AUC values consistently increased when utilizing data from 5-mm, 10-mm, and 20-mm peritumoral regions. Combining arterial and delayed-phase data yielded the highest predictive performance, with micro- and macro-average AUCs of 0.78 and 0.74, respectively. Integration of clinical data further improved AUCs values to 0.83 and 0.80. CONCLUSION Compared with those of the tumor region, the deep learning features of the peritumoral region provide more important information for predicting the grade of MVI. Combining the tumor region and the 20-mm peritumoral region resulted in a relatively ideal and accurate region within which the grade of MVI can be predicted. CLINICAL RELEVANCE STATEMENT The 20-mm peritumoral region holds more significance than the tumor region in predicting MVI grade. Deep learning features can indirectly predict MVI by extracting information from the tumor region and directly capturing MVI information from the peritumoral region. KEY POINTS We investigated tumor and different peritumoral regions, as well as their fusion. MVI predominantly occurs in the peritumoral region, a superior predictor compared to the tumor region. The peritumoral 20 mm region is reasonable for accurately predicting the three-grade MVI.
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Affiliation(s)
- Guangya Wei
- Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, China
| | - Guoxu Fang
- Department of Hepatopancreatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, China
| | - Pengfei Guo
- Southeast Big Data Institute of Hepatobiliary Health, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, China
| | - Peng Fang
- Department of Radiology, Henan Province Hospital of TCM, Zhengzhou, China
| | - Tongming Wang
- Department of Radiology, Henan Province Hospital of TCM, Zhengzhou, China
| | - Kecan Lin
- Department of Hepatopancreatobiliary Surgery, First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jingfeng Liu
- Department of Hepatopancreatobiliary Surgery, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fujian Key Laboratory of Advanced Technology for Cancer Screening and Early Diagnosis, Fuzhou, China.
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Schmidt R, Hamm CA, Rueger C, Xu H, He Y, Gottwald LA, Gebauer B, Savic LJ. Decision-Tree Models Indicative of Microvascular Invasion on MRI Predict Survival in Patients with Hepatocellular Carcinoma Following Tumor Ablation. J Hepatocell Carcinoma 2024; 11:1279-1293. [PMID: 38974016 PMCID: PMC11227855 DOI: 10.2147/jhc.s454487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Accepted: 04/18/2024] [Indexed: 07/09/2024] Open
Abstract
Purpose Histological microvascular invasion (MVI) is a risk factor for poor survival and early recurrence in hepatocellular carcinoma (HCC) after surgery. Its prognostic value in the setting of locoregional therapies (LRT), where no tissue samples are obtained, remains unknown. This study aims to establish CT-derived indices indicative of MVI on liver MRI with superior soft tissue contrast and evaluate their association with patient survival after ablation via interstitial brachytherapy (iBT) versus iBT combined with prior conventional transarterial chemoembolization (cTACE). Patients and Methods Ninety-five consecutive patients, who underwent ablation via iBT alone (n = 47) or combined with cTACE (n = 48), were retrospectively included between 01/2016 and 12/2017. All patients received contrast-enhanced MRI prior to LRT. Overall (OS), progression-free survival (PFS), and time-to-progression (TTP) were assessed. Decision-tree models to determine Radiogenomic Venous Invasion (RVI) and Two-Trait Predictor of Venous Invasion (TTPVI) on baseline MRI were established, validated on an external test set (TCGA-LIHC), and applied in the study cohorts to investigate their prognostic value for patient survival. Statistics included Fisher's exact and t-test, Kaplan-Meier and cox-regression analysis, area under the receiver operating characteristic curve (AUC-ROC) and Pearson's correlation. Results OS, PFS, and TTP were similar in both treatment groups. In the external dataset, RVI showed low sensitivity but relatively high specificity (AUC-ROC = 0.53), and TTPVI high sensitivity but only low specificity (AUC-ROC = 0.61) for histological MVI. In patients following iBT alone, positive RVI and TTPVI traits were associated with poorer OS (RVI: p < 0.01; TTPVI: p = 0.08), PFS (p = 0.04; p = 0.04), and TTP (p = 0.14; p = 0.03), respectively. However, when patients with combined cTACE and iBT were stratified by RVI or TTPVI, no differences in OS (p = 0.75; p = 0.55), PFS (p = 0.70; p = 0.43), or TTP (p = 0.33; p = 0.27) were observed. Conclusion The study underscores the role of non-invasive imaging biomarkers indicative of MVI to identify patients, who would potentially benefit from embolotherapy via cTACE prior to ablation rather than ablation alone.
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Affiliation(s)
- Robin Schmidt
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
- Experimental Clinical Research Center (ECRC) at Charité - Universitätsmedizin Berlin and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, 13125, Germany
| | - Charlie Alexander Hamm
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, 10117, Germany
| | - Christopher Rueger
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
| | - Han Xu
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
| | - Yubei He
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
- Experimental Clinical Research Center (ECRC) at Charité - Universitätsmedizin Berlin and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, 13125, Germany
| | | | - Bernhard Gebauer
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
| | - Lynn Jeanette Savic
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology, Berlin, 13353, Germany
- Experimental Clinical Research Center (ECRC) at Charité - Universitätsmedizin Berlin and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, 13125, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, 10117, Germany
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Huang XW, Li Y, Jiang LN, Zhao BK, Liu YS, Chen C, Zhao D, Zhang XL, Li ML, Jiang YY, Liu SH, Zhu L, Zhao JM. Nomogram for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma. Transl Oncol 2024; 45:101986. [PMID: 38723299 PMCID: PMC11101742 DOI: 10.1016/j.tranon.2024.101986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 04/22/2024] [Accepted: 05/05/2024] [Indexed: 05/21/2024] Open
Abstract
Microvascular invasion (MVI) is an adverse prognostic indicator of tumor recurrence after surgery for hepatocellular carcinoma (HCC). Therefore, developing a nomogram for estimating the presence of MVI before liver resection is necessary. We retrospectively included 260 patients with pathologically confirmed HCC at the Fifth Medical Center of Chinese PLA General Hospital between January 2021 and April 2024. The patients were randomly divided into a training cohort (n = 182) for nomogram development, and a validation cohort (n = 78) to confirm the performance of the model (7:3 ratio). Significant clinical variables associated with MVI were then incorporated into the predictive nomogram using both univariate and multivariate logistic analyses. The predictive performance of the nomogram was assessed based on its discrimination, calibration, and clinical utility. Serum carnosine dipeptidase 1 ([CNDP1] OR 2.973; 95 % CI 1.167-7.575; p = 0.022), cirrhosis (OR 8.911; 95 % CI 1.922-41.318; p = 0.005), multiple tumors (OR 4.095; 95 % CI 1.374-12.205; p = 0.011), and tumor diameter ≥3 cm (OR 4.408; 95 % CI 1.780-10.919; p = 0.001) were independent predictors of MVI. Performance of the nomogram based on serum CNDP1, cirrhosis, number of tumors and tumor diameter was achieved with a concordance index of 0.833 (95 % CI 0.771-0.894) and 0.821 (95 % CI 0.720-0.922) in the training and validation cohorts, respectively. It fitted well in the calibration curves, and the decision curve analysis further confirmed its clinical usefulness. The nomogram, incorporating significant clinical variables and imaging features, successfully predicted the personalized risk of MVI in HCC preoperatively.
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Affiliation(s)
- Xiao-Wen Huang
- Medical School of Chinese PLA, Beijing, China; Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yan Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Li-Na Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Bo-Kang Zhao
- Department of Hepatology, Center of Infectious Diseases and Pathogen Biology, The First Hospital of Jilin University, Changchun, China
| | - Yi-Si Liu
- First Department of Liver Disease Center, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Chun Chen
- Senior Department of Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Dan Zhao
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xue-Li Zhang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Mei-Ling Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yi-Yun Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shu-Hong Liu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Li Zhu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jing-Min Zhao
- Medical School of Chinese PLA, Beijing, China; Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
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Danzeng A, Guo L, Yang ZH, He ZW, Zeng CL, Ciren P, Lan RH, Jiang XW, Wang C, Zhang BH. Postoperative lenvatinib + PD-1 blockade reduces early tumor recurrence in hepatocellular carcinoma with microvascular invasion (Barcelona Clinic Liver Cancer stage 0 or A): a propensity score matching analysis. J Gastrointest Surg 2024; 28:1104-1112. [PMID: 38723996 DOI: 10.1016/j.gassur.2024.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/22/2024] [Accepted: 05/03/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND This study aimed to determine the effectiveness of postoperative adjuvant lenvatinib + PD-1 blockade for patients with early-stage hepatocellular carcinoma (HCC) with microvascular invasion (MVI). METHODS A total of 393 patients with HCC (Barcelona Clinic Liver Cancer stage 0 or A) who underwent curative hepatectomy with histopathologically proven MVI were enrolled according to the inclusion and exclusion criteria and assigned to 2 groups: surgery alone (surgery-alone group) and surgery with lenvatinib and PD-1 blockade (surgery + lenvatinib + PD-1 group) to compare recurrence-free survival (RFS), overall survival (OS), recurrence type, and annual recurrence rate after the application of propensity score matching (PSM). The Cox proportional hazards model was used for univariate and multivariate analyses. RESULTS Overall, 99 matched pairs were selected using PSM. Patients in the surgery + lenvatinib + PD-1 group had significantly higher 3-year RFS rates (76.8%, 65.7%, and 53.5%) than patients in the surgery-alone group (60.6%, 45.5%, and 37.4%) (P = .012). The 2 groups showed no significant difference in recurrence types and OS. Surgery alone, MVI-M2, and alpha-fetoprotein of ≥200 ng/mL were independent risk factors for RFS (P < .05), and history of alcohol use disorder was an independent risk factor for OS (P = .022). CONCLUSION Postoperative lenvatinib + PD-1 blockade improved the RFS in patients with HCC with MVI and was particularly beneficial for specific individuals.
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Affiliation(s)
- Awang Danzeng
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ling Guo
- Division of Hepato-Pancreato-Biliary Surgery, Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Zhen-Hua Yang
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng-Wei He
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cheng-Long Zeng
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Pingcuo Ciren
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Run-Hu Lan
- Division of Hepato-Pancreato-Biliary Surgery, Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Xue-Wei Jiang
- Division of Hepato-Pancreato-Biliary Surgery, Tianyou Hospital, Wuhan University of Science and Technology, Wuhan, China
| | - Chao Wang
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bin-Hao Zhang
- Department of Surgery, Institute of Hepato-Pancreato-Biliary Surgery, Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Ye G, Wang J, Xia J, Zhu C, Gu C, Li X, Li J, Ye M, Jin X. Low protein expression of LZTR1 in hepatocellular carcinoma triggers tumorigenesis via activating the RAS/RAF/MEK/ERK signaling. Heliyon 2024; 10:e32855. [PMID: 38994114 PMCID: PMC11237970 DOI: 10.1016/j.heliyon.2024.e32855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 06/10/2024] [Accepted: 06/11/2024] [Indexed: 07/13/2024] Open
Abstract
LZTR1 is a substrate specific adaptor for E3 ligase involved in the ubiquitination and degradation of RAS GTPases, which inhibits the RAS/RAF/MEK/ERK signaling to suppress the pathogenesis of Noonan syndrome and glioblastoma. However, it's still unknown whether LZTR1 destabilizes RAS GTPases to suppress HCC progression by inhibiting these signaling pathway. Lenvatinib is the first-line drug for the treatment of advanced HCC, however, it has high drug resistance. To explore the roles of LZTR1 in HCC progression and the underlying mechanisms of lenvatinib resistance, techniques such as bioinformatics analysis, immunohistochemical staining, RT-qPCR, Western blot, cell functional experiments, small interfering RNA transfection and cycloheximide chase assay were applied in our study. Among these, bioinformatics analysis and immunohistochemical staining results indicated that LZTR1 protein was aberrantly expressed at low levels in HCC tissues, and low protein expression of LZTR1 was associated with poor prognosis of HCC patients. In vitro functional experiments confirmed that low expression of LZTR1 promoted HCC cell proliferation and migration via the aberrant activation of the RAS/RAF/MEK/ERK signaling due to the dysregulation of LZTR1-induced KRAS ubiquitination and degradation. Transwell assays revealed that blocking of LZTR1-mediated KRAS degradation could induce lenvatinib resistance in HCC cells. In conclusion, our study revealed that LZTR1 knockdown promoted HCC cell proliferation and migration, and induced lenvatinib resistance via activating the RAS/RAF/MEK/ERK signaling, which may provide new ideas for HCC treatment.
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Affiliation(s)
- Ganghui Ye
- Department of Biochemistry and Molecular Biology, Health Science Center, Ningbo University, Ningbo, 315211, China
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Jie Wang
- Department of Biochemistry and Molecular Biology, Health Science Center, Ningbo University, Ningbo, 315211, China
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Jingyi Xia
- Zhejiang Key Laboratory of Pathophysiology, Department of Biochemistry and Molecular Biology, Health Science Center of Ningbo University, Ningbo, 315211, China
| | - Chenlu Zhu
- Zhejiang Key Laboratory of Pathophysiology, Department of Biochemistry and Molecular Biology, Health Science Center of Ningbo University, Ningbo, 315211, China
| | - Chaoyu Gu
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Xinming Li
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Jingyun Li
- Department of Biochemistry and Molecular Biology, Health Science Center, Ningbo University, Ningbo, 315211, China
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Meng Ye
- Department of Biochemistry and Molecular Biology, Health Science Center, Ningbo University, Ningbo, 315211, China
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
| | - Xiaofeng Jin
- Department of Biochemistry and Molecular Biology, Health Science Center, Ningbo University, Ningbo, 315211, China
- Department of Oncology, The First Hospital of Ningbo University, Ningbo, 315020, China
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Chan KM, Lee WC. Liver transplantation for advanced hepatocellular carcinoma: Controversy over portal vein tumor thrombosis. Biomed J 2024; 48:100757. [PMID: 38942384 PMCID: PMC12001119 DOI: 10.1016/j.bj.2024.100757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/22/2024] [Accepted: 06/25/2024] [Indexed: 06/30/2024] Open
Abstract
Liver transplantation (LT) is considered the ideal treatment for hepatocellular carcinoma (HCC) concurrent with underlying cirrhotic liver disease. As well-known, LT for HCC based on the Milan criteria has shown satisfactory outcomes. However, numerous expanded transplantation criteria were proposed to benefit more patients for LT and showed comparable survivals as well. In addition, a modest expansion of transplantation criteria for HCC may be acceptable on the basis of the consensus within the transplantation community. Nonetheless, LT in patients with advanced HCC and portal vein tumor thrombosis (PVTT) recently has received attention and has been reported by many transplantation centers despite being contraindicated. Of those, the LT outcomes in certain HCC patients with PVTT were favorable. Additionally, the advancement of multimodality treatments and the evolution of systemic therapies have emerged as promising therapeutic options for downstaging advanced HCC prior to LT. Somehow, advanced HCC with PVTT could be downstaged to become eligible for LT through these multidisciplinary approaches. Although the available evidence of LT for HCC with PVTT is limited, it is hoped that LT may soon be more widely indicated for these patients. Nevertheless, several unknown factors associated with LT for HCC remain to be explored. Herein, this review aimed to update the developments in LT for patients with advanced HCC.
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Affiliation(s)
- Kun-Ming Chan
- Department of General Surgery and Chang Gung Transplantation Institute, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan.
| | - Wei-Chen Lee
- Department of General Surgery and Chang Gung Transplantation Institute, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan
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Derbel H, Galletto Pregliasco A, Mulé S, Calderaro J, Zaarour Y, Saccenti L, Ghosn M, Reizine E, Blain M, Laurent A, Brustia R, Leroy V, Amaddeo G, Luciani A, Tacher V, Kobeiter H. Should Hypervascular Incidentalomas Detected on Per-Interventional Cone Beam Computed Tomography during Intra-Arterial Therapies for Hepatocellular Carcinoma Impact the Treatment Plan in Patients Waiting for Liver Transplantation? Cancers (Basel) 2024; 16:2333. [PMID: 39001395 PMCID: PMC11240509 DOI: 10.3390/cancers16132333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/22/2024] [Accepted: 06/24/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Current guidelines do not indicate any comprehensive management of hepatic hypervascular incidentalomas (HVIs) discovered in hepatocellular carcinoma (HCC) patients during intra-arterial therapies (IATs). This study aims to evaluate the prognostic value of HVIs detected on per-interventional cone beam computed tomography (CBCT) during IAT for HCC in patients waiting for liver transplantation (LT). MATERIAL AND METHODS In this retrospective single-institutional study, all liver-transplanted HCC patients between January 2014 and December 2018 who received transarterial chemoembolization (TACE) or radioembolization (TARE) before LT were included. The number of ≥10 mm HCCs diagnosed on contrast-enhanced pre-interventional imaging (PII) was compared with that detected on per-interventional CBCT with a nonparametric Wilcoxon test. The correlation between the presence of an HVI and histopathological criteria associated with poor prognosis (HPP) on liver explants was investigated using the chi-square test. Tumor recurrence (TR) and TR-related mortality were investigated using the chi-square test. Recurrence-free survival (RFS), TR-related survival (TRRS), and overall survival (OS) were assessed according to the presence of HVI using Kaplan-Meier analysis. RESULTS Among 63 included patients (average age: 59 ± 7 years, H/F = 50/13), 36 presented HVIs on per-interventional CBCT. The overall nodule detection rate of per-interventional CBCT was superior to that of PII (median at 3 [Q1:2, Q3:5] vs. 2 [Q1:1, Q3:3], respectively, p < 0.001). No significant correlation was shown between the presence of HVI and HPP (p = 0.34), TR (p = 0.095), and TR-related mortality (0.22). Kaplan-Meier analysis did not show a significant impact of the presence of HVI on RFS (p = 0.07), TRRS (0.48), or OS (p = 0.14). CONCLUSIONS These results may indicate that the treatment plan during IAT should not be impacted or modified in response to HVI detection.
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Affiliation(s)
- Haytham Derbel
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Athena Galletto Pregliasco
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
| | - Sébastien Mulé
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Julien Calderaro
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
- Laboratory of Pathology, Henri Mondor University Hospital, 94010 Creteil, France
| | - Youssef Zaarour
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
| | - Laetitia Saccenti
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Mario Ghosn
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Edouard Reizine
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Maxime Blain
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Alexis Laurent
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
- Department of Visceral Surgery, Henri Mondor University Hospital, 94010 Creteil, France
| | - Raffaele Brustia
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
- Department of Visceral Surgery, Henri Mondor University Hospital, 94010 Creteil, France
| | - Vincent Leroy
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
- Department of Hepatology, Henri Mondor University Hospital, 94010 Creteil, France
| | - Giuliana Amaddeo
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
- Department of Hepatology, Henri Mondor University Hospital, 94010 Creteil, France
| | - Alain Luciani
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Vania Tacher
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Institut Mondor de Recherche Biomédicale, Inserm U955, Team n° 18, 94010 Creteil, France
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
| | - Hicham Kobeiter
- Medical Imaging Department, Henri Mondor University Hospital, 51 Avenue du Marechal de Lattre de Tassigny, 94010 Creteil, France (H.K.)
- Faculty of Medicine, University of Paris Est Creteil, 94010 Creteil, France
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Zhang Z, Jia XF, Chen XY, Chen YH, Pan KH. Radiomics-Based Prediction of Microvascular Invasion Grade in Nodular Hepatocellular Carcinoma Using Contrast-Enhanced Magnetic Resonance Imaging. J Hepatocell Carcinoma 2024; 11:1185-1192. [PMID: 38933179 PMCID: PMC11199320 DOI: 10.2147/jhc.s461420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 06/01/2024] [Indexed: 06/28/2024] Open
Abstract
Objective The aim of this study is to develop and verify a magnetic resonance imaging (MRI)-based radiomics model for predicting the microvascular invasion grade (MVI) before surgery in individuals diagnosed with nodular hepatocellular carcinoma (HCC). Methods A total of 198 patients were included in the study and were randomly stratified into two groups: a training group consisting of 139 patients and a test group comprising 59 patients. The tumor lesion was manually segmented on the largest cross-sectional slice using ITK SNAP, with agreement reached between two radiologists. The selection of radiomics features was carried out using the LASSO (Least Absolute Shrinkage and Selection Operator) algorithm. Radiomics models were then developed through maximum correlation, minimum redundancy, and logistic regression analyses. The performance of the models in predicting MVI grade was assessed using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. Results There were no notable statistical differences in sex, age, BMI (body mass index), tumor size, and location between the training and test groups. The AP and PP radiomic model constructed for predicting MVI grade demonstrated an AUC of 0.83 (0.75-0.88) and 0.73 (0.64-0.80) in the training group and an AUC of 0.74 (0.61-0.85) and 0.62 (0.48-0.74) in test group, respectively. The combined model consists of imaging data and clinical data (age and AFP), achieved an AUC of 0.85 (0.78-0.91) and 0.77 (0.64-0.87) in the training and test groups, respectively. Conclusion A radiomics model utilizing-contrast-enhanced MRI demonstrates strong predictive capability for differentiating MVI grades in individuals with nodular HCC. This model could potentially function as a dependable and resilient tool to support hepatologists and radiologists in their preoperative decision-making processes.
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Affiliation(s)
- Zhao Zhang
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China
| | - Xiu-Fen Jia
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China
| | - Xiao-Yu Chen
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China
| | - Yong-Hua Chen
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China
| | - Ke-Hua Pan
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China
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Zhu Y, Feng B, Wang P, Wang B, Cai W, Wang S, Meng X, Wang S, Zhao X, Ma X. Bi-regional dynamic contrast-enhanced MRI for prediction of microvascular invasion in solitary BCLC stage A hepatocellular carcinoma. Insights Imaging 2024; 15:149. [PMID: 38886267 PMCID: PMC11183021 DOI: 10.1186/s13244-024-01720-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/23/2024] [Indexed: 06/20/2024] Open
Abstract
OBJECTIVES To construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy. METHODS Patients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan-Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches. RESULTS A total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05). CONCLUSION The combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making. CRITICAL RELEVANCE STATEMENT The combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies. KEY POINTS Microvascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC). Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance. The combined model could help stratify the risk of recurrence and aid treatment planning.
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Affiliation(s)
- Yongjian Zhu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bing Feng
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Peng Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bingzhi Wang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Wei Cai
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Shuang Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xuan Meng
- Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Sicong Wang
- Magnetic Resonance Imaging Research, General Electric Healthcare (China), Beijing, 100176, China
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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He L, Ji WS, Jin HL, Lu WJ, Zhang YY, Wang HG, Liu YY, Qiu S, Xu M, Lei ZP, Zheng Q, Yang XL, Zhang Q. Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma. World J Gastroenterol 2024; 30:2763-2776. [PMID: 38899335 PMCID: PMC11185292 DOI: 10.3748/wjg.v30.i21.2763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/24/2024] [Accepted: 05/13/2024] [Indexed: 06/03/2024] Open
Abstract
BACKGROUND At present, liver transplantation (LT) is one of the best treatments for hepatocellular carcinoma (HCC). Accurately predicting the survival status after LT can significantly improve the survival rate after LT, and ensure the best way to make rational use of liver organs. AIM To develop a model for predicting prognosis after LT in patients with HCC. METHODS Clinical data and follow-up information of 160 patients with HCC who underwent LT were collected and evaluated. The expression levels of alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin, Golgi protein 73, cytokeratin-18 epitopes M30 and M65 were measured using a fully automated chemiluminescence analyzer. The best cutoff value of biomarkers was determined using the Youden index. Cox regression analysis was used to identify the independent risk factors. A forest model was constructed using the random forest method. We evaluated the accuracy of the nomogram using the area under the curve, using the calibration curve to assess consistency. A decision curve analysis (DCA) was used to evaluate the clinical utility of the nomograms. RESULTS The total tumor diameter (TTD), vascular invasion (VI), AFP, and cytokeratin-18 epitopes M30 (CK18-M30) were identified as important risk factors for outcome after LT. The nomogram had a higher predictive accuracy than the Milan, University of California, San Francisco, and Hangzhou criteria. The calibration curve analyses indicated a good fit. The survival and recurrence-free survival (RFS) of high-risk groups were significantly lower than those of low- and middle-risk groups (P < 0.001). The DCA shows that the model has better clinical practicability. CONCLUSION The study developed a predictive nomogram based on TTD, VI, AFP, and CK18-M30 that could accurately predict overall survival and RFS after LT. It can screen for patients with better postoperative prognosis, and improve long-term survival for LT patients.
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Affiliation(s)
- Li He
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
- School of Clinical Medicine, Shandong Second Medical University, Weifang 261053, Shandong Province, China
| | - Wan-Sheng Ji
- Clinical Research Center, The Affiliated Hospital of Shandong Second Medical University, Weifang 261053, Shandong Province, China
| | - Hai-Long Jin
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Wen-Jing Lu
- Department of Laboratory Medicine, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Yuan-Yuan Zhang
- Department of Laboratory Medicine, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Hua-Guang Wang
- Physiatry Department, Naval Aviation University, Yantai 100071, Shandong Province, China
| | - Yu-Yu Liu
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Shuang Qiu
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Meng Xu
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Zi-Peng Lei
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Qian Zheng
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Xiao-Li Yang
- Department of Laboratory Medicine, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
| | - Qing Zhang
- Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, Beijing 100039, China
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Tang M, Zhang S, Yang M, Feng R, Lin J, Chen X, Xu Y, Yu R, Liao X, Li Z, Li X, Li M, Zhang Q, Chen S, Qian W, Liu Y, Song L, Li J. Infiltrative Vessel Co-optive Growth Pattern Induced by IQGAP3 Overexpression Promotes Microvascular Invasion in Hepatocellular Carcinoma. Clin Cancer Res 2024; 30:2206-2224. [PMID: 38470497 DOI: 10.1158/1078-0432.ccr-23-2933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/26/2023] [Accepted: 03/08/2024] [Indexed: 03/14/2024]
Abstract
PURPOSE Microvascular invasion (MVI) is a major unfavorable prognostic factor for intrahepatic metastasis and postoperative recurrence of hepatocellular carcinoma (HCC). However, the intervention and preoperative prediction for MVI remain clinical challenges due to the absent precise mechanism and molecular marker(s). Herein, we aimed to investigate the mechanisms underlying vascular invasion that can be applied to clinical intervention for MVI in HCC. EXPERIMENTAL DESIGN The histopathologic characteristics of clinical MVI+/HCC specimens were analyzed using multiplex immunofluorescence staining. The liver orthotopic xenograft mouse model and mechanistic experiments on human patient-derived HCC cell lines, including coculture modeling, RNA-sequencing, and proteomic analysis, were used to investigate MVI-related genes and mechanisms. RESULTS IQGAP3 overexpression was correlated significantly with MVI status and reduced survival in HCC. Upregulation of IQGAP3 promoted MVI+-HCC cells to adopt an infiltrative vessel co-optive growth pattern and accessed blood capillaries by inducing detachment of activated hepatic stellate cells (HSC) from the endothelium. Mechanically, IQGAP3 overexpression contributed to HCC vascular invasion via a dual mechanism, in which IQGAP3 induced HSC activation and disruption of the HSC-endothelial interaction via upregulation of multiple cytokines and enhanced the trans-endothelial migration of MVI+-HCC cells by remodeling the cytoskeleton by sustaining GTPase Rac1 activity. Importantly, systemic delivery of IQGAP3-targeting small-interfering RNA nanoparticles disrupted the infiltrative vessel co-optive growth pattern and reduced the MVI of HCC. CONCLUSIONS Our results revealed a plausible mechanism underlying IQGAP3-mediated microvascular invasion in HCC, and provided a potential target to develop therapeutic strategies to treat HCC with MVI.
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Affiliation(s)
- Miaoling Tang
- Department of Oncology, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Shuxia Zhang
- Department of Oncology, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Meisongzhu Yang
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Rongni Feng
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jinbin Lin
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xiaohong Chen
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Yingru Xu
- Molecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Ruyuan Yu
- Molecular Diagnosis and Gene Testing Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinyi Liao
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Ziwen Li
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xincheng Li
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Man Li
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Qiliang Zhang
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Suwen Chen
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Wanying Qian
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Yuanji Liu
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Libing Song
- State Key Laboratory of Oncology in South China Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jun Li
- Department of Oncology, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
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50
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Yu Y, Wang XH, Hu WJ, Chen DH, Hu ZL, Li SQ. Patterns, Risk Factors, and Outcomes of Recurrence After Hepatectomy for Hepatocellular Carcinoma with and without Microvascular Invasion. J Hepatocell Carcinoma 2024; 11:801-812. [PMID: 38737385 PMCID: PMC11088842 DOI: 10.2147/jhc.s438850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 04/24/2024] [Indexed: 05/14/2024] Open
Abstract
Purpose The patterns and risk factors of postsurgical recurrence of patient with hepatocellular carcinoma (HCC) with microvascular invasion (MVI) are not clarified. This study aimed to decipher and compare the postoperative recurrent patterns and the risk factors contributing to recurrence between MVI positive (MVI(+)) and MVI negative (MVI(-)) HCC after hepatectomy. Patients and methods Patients with HCC who underwent hepatectomy in three Chinese academic hospitals between January 1, 2009, and December 31, 2018, were enrolled. Recurrent patterns included early (≤2 years) or late (>2 years) recurrence, recurrent sites and number, and risk factors of recurrence were compared between the MVI(+)and MVI(-) groups by propensity score-matching (PSM). Results Of 1756 patients included, 581 (33.1%) were MVI(+), and 875 (49.8%) patients developed early recurrence. Compared with the MVI(-) group, the MVI(+) group had a higher 2-year recurrence rate in the PSM cohort (hazard ratio [HR], 1.82; 95% confidence interval [CI], 1.59-2.10; P < 0.001), and more patients with multiple tumor recurrence. Patients with early recurrence in the MVI(+) group had a worse overall survival (OS) than those in the MVI(-) group (HR, 1.24; 95% CI, 1.02-1.50; P = 0.034). Resection margin (RM) ≤1.0 cm is a surgical predictor of early recurrence for the MVI(+) group (HR, 0.68; 95% CI, 0.54-0.87; P = 0.002), but not for the MVI(-) group. Conclusion Compared to MVI(-) HCC, MVI(+) HCC tends to be early, multiple recurrence and lung and lymph node metastasis after resection. RM ≤1.0 cm is a surgical risk factor of early recurrence for patient with MVI.
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Affiliation(s)
- Yang Yu
- Hepatic Pancreatobiliary Surgery Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
| | - Xiao-Hui Wang
- Department of Hepatobiliary Surgery, Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University) Changsha, Hunan Province, 410005, People’s Republic of China
| | - Wen-Jie Hu
- Hepatic Pancreatobiliary Surgery Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
| | - De-Hua Chen
- Hepatic Pancreatobiliary Surgery Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
| | - Zi-Li Hu
- Department of Liver Surgery, Sun Yat-Sen University Cancer Center, Guangdong, 510060, Guangzhou, People’s Republic of China
| | - Shao-Qiang Li
- Hepatic Pancreatobiliary Surgery Center, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China
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