|
1
|
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 2025:10.1007/s00464-025-11717-1. [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] [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.
Collapse
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.
| |
Collapse
|
|
2
|
Xie XY, Chen R. Research progress of MRI-based radiomics in hepatocellular carcinoma. Front Oncol 2025; 15:1420599. [PMID: 39980543 PMCID: PMC11839447 DOI: 10.3389/fonc.2025.1420599] [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: 04/20/2024] [Accepted: 01/20/2025] [Indexed: 02/22/2025] Open
Abstract
Background Primary liver cancer (PLC), notably hepatocellular carcinoma (HCC), stands as a formidable global health challenge, ranking as the sixth most prevalent malignant tumor and the third leading cause of cancer-related deaths. HCC presents a daunting clinical landscape characterized by nonspecific early symptoms and late-stage detection, contributing to its poor prognosis. Moreover, the limited efficacy of existing treatments and high recurrence rates post-surgery compound the challenges in managing this disease. While histopathologic examination remains the cornerstone for HCC diagnosis, its utility in guiding preoperative decisions is constrained. Radiomics, an emerging field, harnesses high-throughput imaging data, encompassing shape, texture, and intensity features, alongside clinical parameters, to elucidate disease characteristics through advanced computational techniques such as machine learning and statistical modeling. MRI radiomics specifically holds significant importance in the diagnosis and treatment of hepatocellular carcinoma (HCC). Objective This study aims to evaluate the methodology of radiomics and delineate the clinical advancements facilitated by MRI-based radiomics in the realm of hepatocellular carcinoma diagnosis and treatment. Methods A systematic review of the literature was conducted, encompassing peer-reviewed articles published between July 2018 and Jan 2025, sourced from PubMed and Google Scholar. Key search terms included Hepatocellular carcinoma, HCC, Liver cancer, Magnetic resonance imaging, MRI, radiomics, deep learning, machine learning, and artificial intelligence. Results A comprehensive analysis of 93 articles underscores the efficacy of MRI radiomics, a noninvasive imaging analysis modality, across various facets of HCC management. These encompass tumor differentiation, subtype classification, histopathological grading, prediction of microvascular invasion (MVI), assessment of treatment response, early recurrence prognostication, and metastasis prediction. Conclusion MRI radiomics emerges as a promising adjunctive tool for early HCC detection and personalized preoperative decision-making, with the overarching goal of optimizing patient outcomes. Nevertheless, the current lack of interpretability within the field underscores the imperative for continued research and validation efforts.
Collapse
Affiliation(s)
- Xiao-Yun Xie
- Department of Radiation Oncology, Medical School of Southeast University, Nanjing, China
| | - Rong Chen
- Department of Radiation Oncology, Zhongda Hospital, Nanjing, China
| |
Collapse
|
|
3
|
Gu X, Wei Y, Lu M, Shen D, Wu X, Huang J. Systematic Analysis of Disulfidptosis-Related lncRNAs in Hepatocellular Carcinoma with Vascular Invasion Revealed That AC131009.1 Can Promote HCC Invasion and Metastasis through Epithelial-Mesenchymal Transition. ACS OMEGA 2024; 9:49986-49999. [PMID: 39713637 PMCID: PMC11656384 DOI: 10.1021/acsomega.4c09411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2024] [Revised: 11/14/2024] [Accepted: 11/19/2024] [Indexed: 12/24/2024]
Abstract
Disulfidptosis, a recently identified pathway of cellular demise, served as the focal point of this research, aiming to pinpoint relevant lncRNAs that differentiate between hepatocellular carcinoma (HCC) with and without vascular invasion while also forecasting survival rates and responses to immunotherapy in patients with vascular invasion (VI+). First, we identified 300 DRLRs in the TCGA database. Subsequently, utilizing univariate analysis, LASSO-Cox proportional hazards modeling, and multivariate analytical approaches, we selected three DRLRs (AC009779.2, AC131009.1, and LUCAT1) with the highest prognostic value to construct a prognostic risk model for VI+ HCC patients. Multivariate Cox regression analysis revealed that this model is an independent prognostic factor for predicting overall survival that outperforms traditional clinicopathological factors. Pathway analysis demonstrated the enrichment of tumor and immune-related pathways in the high-risk group. Immune landscape analysis revealed that immune cell infiltration degrees and immune functions had significant differences. Additionally, we identified valuable chemical drugs (AZD4547, BMS-536924, BPD-00008900, dasatinib, and YK-4-279) for high-risk VI+ HCC patients. In-depth bioinformatics analysis was subsequently conducted to assess immune characteristics, drug susceptibility, and potential biological pathways involving the three hub DRLRs. Furthermore, the abnormally elevated transcriptional levels of the three DRLRs in HCC cell lines were validated through qRT-PCR. Functional cell assays revealed that silencing the expression of lncRNA AC131009.1 can inhibit the migratory and invasive capabilities of HCC cells, a finding further corroborated by the chorioallantoic membrane (CAM) assay. Immunohistochemical analysis and hematoxylin-eosin staining (HE) staining provided preliminary evidence that AC131009.1 may promote the invasion and metastasis of HCC cells by inducing epithelial-mesenchymal transition (EMT) in both subcutaneous xenograft models and orthotopic HCC models within nude mice. To summarize, we developed a risk assessment model founded on DRLRs and explored the potential mechanisms by which hub DRLRs promote HCC invasion and metastasis.
Collapse
Affiliation(s)
- Xuefeng Gu
- Department
of Infectious Diseases, Jurong Hospital
Affiliated to Jiangsu University, Zhenjiang, Jiangsu 212400, China
| | - Yanyan Wei
- Department
of Infectious Diseases, The First Affiliated
Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Mao Lu
- Department
of Gastroenterology, The Affiliated Changzhou
Second People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu 213003, China
| | - Duo Shen
- Department
of Gastroenterology, The Affiliated Changzhou
Second People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu 213003, China
| | - Xin Wu
- Department
of General Surgery, The Fourth Affiliated
Hospital of Nanjing Medical University, Nanjing, Jiangsu 210000, China
| | - Jin Huang
- Department
of Gastroenterology, The Affiliated Changzhou
Second People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu 213003, China
| |
Collapse
|
|
4
|
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.
Collapse
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.
| |
Collapse
|
|
5
|
Anisetti B, Ahmed AK, Coston T, Gardner L, Majeed U, Reynolds J, Babiker H. Delayed brain metastasis in recurrent hepatocellular carcinoma following liver transplantation: a case report highlighting the predictive value of microvascular invasion. Clin J Gastroenterol 2023; 16:864-870. [PMID: 37532904 DOI: 10.1007/s12328-023-01839-1] [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: 06/15/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023]
Abstract
Recurrent hepatocellular carcinoma (HCC) poses a significant challenge after liver transplantation, affecting approximately 10-23% of patients with a median onset of 13 months post-transplantation. Extrahepatic involvement, such as lung, bone, adrenal glands, peritoneum, lymph nodes, and central nervous system (CNS), is commonly observed among transplant recipients with HCC recurrence. Notably, vascular invasion (VI), including microvascular invasion (MiVI) and macrovascular invasion (MVI), substantially increase the risk of recurrence by 2.42- and 7.82-fold, respectively. This article presents a unique case of a 72-year-old male patient with a history of HCV-related cirrhosis and HCC who underwent orthotopic liver transplantation (OLT). Six years later, he presented to the emergency department following a fall, which led to the discovery of a pathologic fracture of T7 and an incidental intracranial mass during imaging. Subsequent biopsy confirmed metastatic HCC in the T7 lesion, while magnetic resonance imaging revealed two enhancing brain masses. One mass measured 4.8 cm in the left occipitotemporal lobe, and the other measured 1.7 cm in the right frontal gyrus. Notably, the patient had exhibited MiVI and a mildly elevated alpha-fetoprotein level (AFP) of 7.6 ng/mL at the time of his OLT. This case underscores the predictive value of MiVI in HCC recurrence post-OLT. Accordingly, extended post-transplantation surveillance is crucial for patients with HCC and MiVI. Moreover, this report highlights the uncommon occurrence of delayed brain metastasis following OLT in a patient with HCC.
Collapse
Affiliation(s)
- Bhrugun Anisetti
- Department of Hematology and Oncology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL, 32224, USA.
| | - Ahmed K Ahmed
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Tucker Coston
- Department of Hematology and Oncology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL, 32224, USA
| | - Lindsay Gardner
- Department of Hematology and Oncology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL, 32224, USA
| | - Umair Majeed
- Department of Hematology and Oncology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL, 32224, USA
| | - Jordan Reynolds
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Jacksonville, FL, USA
| | - Hani Babiker
- Department of Hematology and Oncology, Mayo Clinic, 4500 San Pablo Rd., Jacksonville, FL, 32224, USA
| |
Collapse
|
|
6
|
Yao J, Li K, Yang H, Lu S, Ding H, Luo Y, Li K, Xie X, Wu W, Jing X, Liu F, Yu J, Cheng Z, Tan S, Dou J, Dong X, Wang S, Zhang Y, Li Y, Qi E, Han Z, Liang P, Yu X. Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study. Eur Radiol 2023; 33:7066-7076. [PMID: 37115213 DOI: 10.1007/s00330-023-09656-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/23/2023] [Accepted: 03/07/2023] [Indexed: 04/29/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the potential of Sonazoid contrast-enhanced ultrasound (SNZ-CEUS) as an imaging biomarker for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS From August 2020 to March 2021, we conducted a prospective multicenter study on the clinical application of Sonazoid in liver tumor; a MVI prediction model was developed and validated by integrating clinical and imaging variables. Multivariate logistic regression analysis was used to establish the MVI prediction model; three models were developed: a clinical model, a SNZ-CEUS model, and a combined model and conduct external validation. We conducted subgroup analysis to investigate the performance of the SNZ-CEUS model in non-invasive prediction of MVI. RESULTS Overall, 211 patients were evaluated. All patients were split into derivation (n = 170) and external validation (n = 41) cohorts. Patients who had MVI accounted for 89 of 211 (42.2%) patients. Multivariate analysis revealed that tumor size (> 49.2 mm), pathology differentiation, arterial phase heterogeneous enhancement pattern, non-single nodular gross morphology, washout time (< 90 s), and gray value ratio (≤ 0.50) were significantly associated with MVI. Combining these factors, the area under the receiver operating characteristic (AUROC) of the combined model in the derivation and external validation cohorts was 0.859 (95% confidence interval (CI): 0.803-0.914) and 0.812 (95% CI: 0.691-0.915), respectively. In subgroup analysis, the AUROC of the SNZ-CEUS model in diameter ≤ 30 mm and ˃ 30 mm cohorts were 0.819 (95% CI: 0.698-0.941) and 0.747 (95% CI: 0.670-0.824). CONCLUSIONS Our model predicted the risk of MVI in HCC patients with high accuracy preoperatively. CLINICAL RELEVANCE STATEMENT Sonazoid, a novel second-generation ultrasound contrast agent, can accumulate in the endothelial network and form a unique Kupffer phase in liver imaging. The preoperative non-invasive prediction model based on Sonazoid for MVI is helpful for clinicians to make individualized treatment decisions. KEY POINTS • This is the first prospective multicenter study to analyze the possibility of SNZ-CEUS preoperatively predicting MVI. • The model established by combining SNZ-CEUS image features and clinical features has high predictive performance in both derivation cohort and external validation cohort. • The findings can help clinicians predict MVI in HCC patients before surgery and provide a basis for optimizing surgical management and monitoring strategies for HCC patients.
Collapse
Affiliation(s)
- Jundong Yao
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
- Chinese PLA Medical School, Beijing, 100853, China
| | - Kaiyan Li
- Department of Ultrasound Imaging, Affiliated Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Hong Yang
- Department of Ultrasound, the First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, China
| | - Shichun Lu
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China
| | - Hong Ding
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yan Luo
- Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Kai Li
- Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China
| | - Xiaoyan Xie
- Department of Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Wei Wu
- Department of Ultrasound, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Xiang Jing
- Department of Ultrasound, the Third Central Hospital of Tianjin, Tianjin, 300170, China
| | - Fangyi Liu
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Jie Yu
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Zhigang Cheng
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Shuilian Tan
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Jianping Dou
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - XueJuan Dong
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Shuo Wang
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Yiqiong Zhang
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Yunlin Li
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Erpeng Qi
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China
| | - Zhiyu Han
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
| | - Ping Liang
- Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
| | - XiaoLing Yu
- Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China.
| |
Collapse
|
|
7
|
Zhang L, Pang G, Zhang J, Yuan Z. Perfusion parameters of triphasic computed tomography hold preoperative prediction value for microvascular invasion in hepatocellular carcinoma. Sci Rep 2023; 13:8629. [PMID: 37244941 DOI: 10.1038/s41598-023-35913-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 05/25/2023] [Indexed: 05/29/2023] Open
Abstract
The purpose of this study was to evaluate perfusion parameters of triphasic computed tomography (CT) scans in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). All patients were pathologically diagnosed as HCC and underwent triple-phase enhanced CT imaging, which was used to calculate the blood perfusion parameters of hepatic arterial supply perfusion (HAP), portal vein blood supply perfusion (PVP), hepatic artery perfusion Index (HPI), and arterial enhancement fraction (AEF). Receiver operating characteristic (ROC) curve was used to evaluate the performance. The mean values of PVP(Min), AEF(Min), the difference in PVP, HPI and AEF related parameters, the relative PVP(Min) and AEF(Min) in MVI negative group were significantly higher than those in MVI positive group, while for the difference in HPI(Max), the relative HPI(Max) and AEF(Max), the value of MVI positive group significantly higher than that of negative group. The combination of PVP, HPI and AEF had the highest diagnostic efficacy. The two parameters related to HPI had the highest sensitivity, while the combination of PVP related parameters had higher specificity. A combination of perfusion parameters in patients with HCC derived from traditional triphasic CT scans can be used as a preoperative biomarker for predicting MVI.
Collapse
Affiliation(s)
- Li Zhang
- Department of Radiology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
| | - Guodong Pang
- Department of Radiology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
| | - Jing Zhang
- Department of Radiology, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, Shandong, China
| | - Zhenguo Yuan
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250021, Shandong, China.
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong, China.
| |
Collapse
|
|
8
|
Wang H, Liu R, Mo H, Li R, Lian J, Liu Q, Han S. A novel nomogram predicting the early recurrence of hepatocellular carcinoma patients after R0 resection. Front Oncol 2023; 13:1133807. [PMID: 37007138 PMCID: PMC10063973 DOI: 10.3389/fonc.2023.1133807] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 02/20/2023] [Indexed: 03/19/2023] Open
Abstract
Background Early tumor recurrence is one of the most significant poor prognostic factors for patients with HCC after R0 resection. The aim of this study is to identify risk factors of early recurrence, in addition, to develop a nomogram model predicting early recurrence of HCC patients. Methods A total of 481 HCC patients after R0 resection were enrolled and divided into a training cohort (n = 337) and a validation cohort (n = 144). Risk factors for early recurrence were determined based on Cox regression analysis in the training cohort. A nomogram incorporating independent risk predictors was established and validated. Results Early recurrence occurred in 37.8% of the 481 patients who underwent curative liver resection of HCC. AFP ≥ 400 ng/mL (HR: 1.662; P = 0.008), VEGF-A among 127.8 to 240.3 pg/mL (HR: 1.781, P = 0.012), VEGF-A > 240.3 pg/mL (HR: 2.552, P < 0.001), M1 subgroup of MVI (HR: 2.221, P = 0.002), M2 subgroup of MVI (HR: 3.120, P < 0.001), intratumor necrosis (HR: 1.666, P = 0.011), surgical margin among 5.0 to 10.0 mm (HR: 1.601, P = 0.043) and surgical margin < 5.0 mm (HR: 1.790, P = 0.012) were found to be independent risk factors for recurrence-free survival in the training cohort and were used for constructing the nomogram. The nomogram indicated good predictive performance with an AUC of 0.781 (95% CI: 0.729-0.832) and 0.808 (95% CI: 0.731-0.886) in the training and validation cohorts, respectively. Conclusions Elevated serum concentrations of AFP and VEGF-A, microvascular invasion, intratumor necrosis, surgical margin were independent risk factors of early intrahepatic recurrence. A reliable nomogram model which incorporated blood biomarkers and pathological variables was established and validated. The nomogram achieved desirable effectiveness in predicting early recurrence in HCC patients.
Collapse
Affiliation(s)
- Huanhuan Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Runkun Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Huanye Mo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Runtian Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jie Lian
- Department of Pathology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Qingguang Liu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Shaoshan Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| |
Collapse
|
|
9
|
Zheng J, Wang N, Yuan J, Huang Y, Pu X, Xie W, Jiang L, Yang J. The appropriate method of hepatectomy for hepatocellular carcinoma within University of California San Francisco (UCSF) criteria through neural network analysis. HPB (Oxford) 2023; 25:497-506. [PMID: 36809863 DOI: 10.1016/j.hpb.2023.02.001] [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: 04/15/2022] [Revised: 01/10/2023] [Accepted: 02/06/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND This study aimed to find effective treatments for the patient within UCSF criteria. METHODS This study enrolled 1006 patients meeting UCSF criteria, undergoing hepatic resection (HR), divided into two groups: single tumor group and multiple tumors group. We compared and analyzed the risk factors between these two groups' long-term outcomes, through log-rank test, cox proportional hazards model and using neural network analysis to identify the independent risk factors. RESULTS The 1-, 3-, and 5-year OS rates in single tumor were significantly higher than multiple tumors (95.0%, 73.2% and 52.3% versus 93.9%, 69.7% and 38.0%, respectively, p < 0.001). The 1-, 3- and 5-year RFS rates were 90.3%, 60.7%, and 40.1% in single tumor and 83.4%, 50.7% and 23.8% in multiple tumors, respectively (p < 0.001). And tumor type, anatomic resection and MVI were the independent risk factors for the patient within UCSF criteria. MVI was the most important risk factor affecting OS and RFS rates in neural network analysis. The method of hepatic resection and the number of tumors were also affected OS and RFS rates. CONCLUSION The anatomic resection should be applied to the patient within UCSF criteria, especially for the patient was in single tumor with MVI-negative.
Collapse
Affiliation(s)
- Jinli Zheng
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China; Department of Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Ning Wang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China; Department of Hepatobiliary Surgery, West China JinTang Hospital, China
| | - Jingsheng Yuan
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China; Department of Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yang Huang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Xingyu Pu
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Wei Xie
- Department of Radiology Department, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Li Jiang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
| | - Jiayin Yang
- Department of Liver Surgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China; Department of Liver Transplantation Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| |
Collapse
|
|
10
|
Huang J, Li L, Liu FC, Tan BB, Yang Y, Jiang BG, Pan ZY. Prognostic Analysis of Single Large Hepatocellular Carcinoma Following Radical Resection: A Single-Center Study. J Hepatocell Carcinoma 2023; 10:573-586. [PMID: 37056420 PMCID: PMC10086221 DOI: 10.2147/jhc.s404895] [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: 01/27/2023] [Accepted: 03/28/2023] [Indexed: 04/15/2023] Open
Abstract
Objective To investigate the survival and independent prognostic factors for single large hepatocellular carcinoma (SLHCC) after surgical resection. Methods Patients with SLHCC who underwent radical resection from January 2013 to December 2017 were retrospectively analyzed. The Kaplan-Meier method was used to analyze the overall survival (OS) rate and recurrence-free survival (RFS) rates. Cox forward stepwise regression was performed to analyze the independent prognostic factors. Results A total of 485 cases were included. The average age was 51.2±11.2 years, 88.9% had a history of hepatitis B virus infection, and most patients had normal liver function. The average tumor diameter was 8.8±3.0 cm. The 1-, 3-, and 5-year OS and RFS rates were 76.8%, 56.7%, and 45.7%, and 61.0%, 46.2%, and 34.7%, respectively. Multivariate analysis showed that liver cirrhosis (HR=1.456, P=0.004), total bilirubin (TB) ≥17.1 μmol/L (HR=1.437, P=0.011), glutamyl transferase (GGT) >60 U/L (HR=1.438, P=0.020), lactate dehydrogenase (LDH) >225 U/L (HR=1.442, P=0.007), blood loss ≥400 mL (HR=1.339, P=0.027), microvascular invasion (MVI) (HR=1.492, P=0.004), satellite lesions (HR=1.859, P<0.0001) and Edmondson-Steiner grade III+IV (HR=1.740, P=0.018) were independent risk factors for reduced OS in SLHCC patients. Sex (HR=1.763, P=0.003), liver cirrhosis (HR=1.382, P=0.007), GGT >60 U/L (HR=1.512, P=0.003), LDH >225 U/L (HR=1.480, P=0.002), MVI (HR=1.545, P=0.001), and satellite lesions (HR=1.564, P=0.001) were independent risk factors for reduced RFS. OS and RFS nomograms were constructed using risk factors with C-index values of 0.692 (95% CI: 0.659-0.724) and 0.659 (95% CI: 0.623-0.693), respectively. The Hosmer-Leme test demonstrated the good fit of both nomograms. Conclusion Surgical resection is the standard and effective treatment for SLHCC patients. Sex, liver cirrhosis, TB≥17.1 μmol/L, GGT>60 U/L, LDH>225 U/L, blood loss≥400 mL, MVI, Edmondson-Steiner grade III+IV, and satellite lesions were found to be independent prognostic factors in SLHCC patients following radical resection. The OS and RFS nomograms accurately predicted the prognosis of SLHCC patients.
Collapse
Affiliation(s)
- Jian Huang
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Li Li
- Department of Nephrology, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Fu-Chen Liu
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Bi-Bo Tan
- Department of Ultrasonic, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Yun Yang
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Bei-Ge Jiang
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
| | - Ze-Ya Pan
- Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, 201805, People’s Republic of China
- Correspondence: Ze-Ya Pan; Bei-Ge Jiang, Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, No. 700, MoYu North Road, Jiading, Shanghai, People’s Republic of China, Tel +86-13391236437; +86-13764561303, Email ;
| |
Collapse
|
|
11
|
Deng Y, Yang J, Chen Y, Wang J, Fu B, Zhang T, Yi S, Yang Y. Development of a Risk Classifier to Predict Tumor Recurrence and Lenvatinib Benefits in Hepatocellular Carcinoma After Liver Transplantation. Transplant Proc 2023; 55:153-163. [PMID: 36522222 DOI: 10.1016/j.transproceed.2022.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 10/22/2022] [Accepted: 11/16/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Current selection tools were not precise enough to predict recurrence of hepatocellular carcinoma (HCC) and benefit of adjuvant lenvatinib for patients who received liver transplant (LT) for HCC. Thus, we aim at developing a risk classifier to predict recurrence of HCC and benefit of adjuvant Lenvatinib for those who underwent LT for HCC. METHODS Cox regression model was applied to selected predictors and created the final model in a training cohort of 287 patients who underwent LT for HCC, which was tested in an internal validation cohort of 72 patients by using C-statistic and net classification index (NRI) compared with the following HCC selection criteria: the Milan criteria, the Up-to-7 criteria, and the University of California, San Francisco criteria. RESULTS We built a Risk Classifier of South China Cohort (RCOSC) based on 4 variables: the maximum diameter plus number of viable tumors, alpha-fetoprotein, microvascular invasion, and highest alanine aminotransferase in 7 days after LT. In validation analyses, our RCOSC showed good predictive performance (C-statistic, 0.866; 95% confidence interval [CI], 0.833-0.899) and had better prognostic value than Milan criteria (NRI, 0.406; P < .001), University of California, San Francisco (NRI, 0.497; P < .001), and Up-to-7 (NRI, 0.527; P < .001). By applying the RCOSC, we were able to accurately categorize patients into high-risk and low-risk groups. Further survival analysis revealed that the patients in the high-risk group might have a better therapeutic response to preventive regimen of lenvatinib after LT for HCC (hazard ratio, 0.38; 95% CI, 0.161-0.871, P = .018). CONCLUSIONS Our RCOSC presented favorable predictive performance for HCC recurrence. It might be capable of sifting out patients who benefit from adjuvant therapy after LT for HCC, providing a reliable tool for precise clinical decision-making of patients with HCC with LT.
Collapse
Affiliation(s)
- Yinan Deng
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jianming Yang
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yewu Chen
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jiangfeng Wang
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Binsheng Fu
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Tong Zhang
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shuhong Yi
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
| | - Yang Yang
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Liver Disease Research, Guangzhou, China.
| |
Collapse
|
|
12
|
Wang S, Zheng W, Zhang Z, Zhang GH, Huang DJ. Microvascular invasion risk scores affect the estimation of early recurrence after resection in patients with hepatocellular carcinoma: a retrospective study. BMC Med Imaging 2022; 22:204. [PMID: 36419016 PMCID: PMC9682687 DOI: 10.1186/s12880-022-00940-0] [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: 01/26/2022] [Accepted: 11/15/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a histological factor that is closely related to the early recurrence of hepatocellular carcinoma (HCC) after resection. To investigate whether a noninvasive risk score system based on MVI status can be established to estimate early recurrence of HCC after resection. METHODS Between January 2018 to March 2021, a total of 108 patients with surgically treated single HCC was retrospectively included in our study. Fifty-one patients were pathologically confirmed with MVI and 57 patients were absent of MVI. Univariate and multivariate logistic regression analysis of preoperative laboratory and magnetic resonance imaging (MRI) features were used to screen noninvasive risk factors in association with MVI in HCC. Risk scores based on the odds ratio (OR) values of MVI-related risk factors were calculated to estimate the early recurrence after resection of HCC. RESULTS In multivariate logistic regression analysis, tumor size > 2 cm (P = 0.024, OR 3.05, 95% CI 1.19-11.13), Prothrombin induced by vitamin K absence-II > 32 mAU/ml (P = 0.001, OR 4.13, 95% CI 1.23-11.38), irregular tumor margin (P = 0.018, OR 3.10, 95% CI 1.16-8.31) and apparent diffusion coefficient value < 1007 × 10- 3mm2/s (P = 0.035, OR 2.27, 95% CI 1.14-7.71) were independent risk factors correlated to MVI in HCC. Risk scores of patients were calculated and were then categorized into high or low-risk levels. In multivariate cox survival analysis, only high-risk score of MVI was the independent risk factor of early recurrence (P = 0.009, OR 2.11, 95% CI 1.20-3.69), with a sensitivity and specificity of 0.52, 0.88, respectively. CONCLUSION A risk score system based on MVI status can help stratify patients in high-risk of early recurrence after resection of HCC.
Collapse
Affiliation(s)
- Sheng Wang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
| | - Weizhi Zheng
- grid.469601.cDepartment of Pathology, Taizhou First People’s Hospital, Taizhou City, 318020 Zhejiang Province China
| | - Zhencheng Zhang
- grid.469601.cDepartment of Laboratory, Taizhou First People’s Hospital, Taizhou City, 318020 Zhejiang Province China
| | - Guo-hua Zhang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
| | - Dan-jiang Huang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
| |
Collapse
|
|
13
|
Zhang S, Duan C, Zhou X, Liu F, Wang X, Shao Q, Gao Y, Duan F, Zhao R, Wang G. Radiomics nomogram for prediction of microvascular invasion in hepatocellular carcinoma based on MR imaging with Gd-EOB-DTPA. Front Oncol 2022; 12:1034519. [PMID: 36387156 PMCID: PMC9663997 DOI: 10.3389/fonc.2022.1034519] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/17/2022] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVE To develop a radiomics nomogram for predicting microvascular invasion (MVI) before surgery in hepatocellular carcinoma (HCC) patients. MATERIALS AND METHODS The data from a total of 189 HCC patients (training cohort: n = 141; validation cohort: n = 48) were collected, involving the clinical data and imaging characteristics. Radiomics features of all patients were extracted from hepatobiliary phase (HBP) in 15 min. Least absolute shrinkage selection operator (LASSO) regression and logistic regression were utilized to reduce data dimensions, feature selection, and to construct a radiomics signature. Clinicoradiological factors were identified according to the univariate and multivariate analyses, which were incorporated into the final predicted nomogram. A nomogram was developed to predict MVI of HCC by combining radiomics signatures and clinicoradiological factors. Radiomics nomograms were evaluated for their discrimination capability, calibration, and clinical usefulness. RESULTS In the clinicoradiological factors, gender, alpha-fetoprotein (AFP) level, tumor shape and halo sign served as the independent risk factors of MVI, with which the area under the curve (AUC) is 0.802. Radiomics signatures covering 14 features at HBP 15 min can effectively predict MVI in HCC, to construct radiomics signature model, with the AUC of 0.732. In the final nomogram model the clinicoradiological factors and radiomics signatures were integrated, outperforming the clinicoradiological model (AUC 0.884 vs. 0.802; p <0.001) and radiomics signatures model (AUC 0.884 vs. 0.732; p < 0.001) according to Delong test results. A robust calibration and discrimination were demonstrated in the nomogram model. The results of decision curve analysis (DCA) showed more significantly clinical efficiency of the nomogram model in comparison to the clinicoradiological model and the radiomic signature model. CONCLUSIONS Depending on the clinicoradiological factors and radiological features on HBP 15 min images, nomograms can effectively predict MVI status in HCC patients.
Collapse
Affiliation(s)
- Shuai Zhang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Chongfeng Duan
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiaoming Zhou
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Fang Liu
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xin Wang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Qiulin Shao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yuanxiang Gao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Feng Duan
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ruirui Zhao
- Operating Room, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Gang Wang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China,*Correspondence: Gang Wang,
| |
Collapse
|
|
14
|
Yang WL, Zhu F, Chen WX. Texture analysis of contrast-enhanced magnetic resonance imaging predicts microvascular invasion in hepatocellular carcinoma. Eur J Radiol 2022; 156:110528. [PMID: 36162156 DOI: 10.1016/j.ejrad.2022.110528] [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: 12/29/2021] [Revised: 04/03/2022] [Accepted: 09/15/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Microvascular invasion is one of the important risk factors of postoperative recurrence of hepatocellular carcinoma. Texture analysis uses mathematical methods to analyze the gray's quantitative value and distribution of images, for quantifying the heterogeneity of tissues. PURPOSE To investigate the feasibility of predicting MVI in HCC by analyzing the texture features of hepatic MR-enhanced images. METHODS 110 patients with HCC who underwent MR-enhanced examinations were included in this study, were divided into MVI-positive group (n = 52) and MVI-negative group (n = 58) according to postoperative pathology. Clinical, pathological data and MR imaging features were collected. 11 texture parameters were selected from the gray histogram and gray level co-occurrence matrix (GLCM). Texture parameters of MR-enhanced images were calculated for statistical analysis. RESULTS There were statistically significant differences in tumor size, location, degree of differentiation, AFP level, signal, pseudocapsule, margin, peritumoral enhancement and intratumoral artery between MVI-positive group and MVI-negative group (P < 0.05). The AUC value of combining MR image features in prediction of MVI was 0.693(sensitivity and specificity: 53.8 %, 82.8 %, respectively). There were statistically significant differences in the texture parameters of GLCM between two groups (P < 0.05). The AUC value of combining texture parameters in prediction of MVI was 0.797 (sensitivity and specificity: 88.2 %, 62.7 %, respectively). CONCLUSION MR image features and texture analysis have certain predictive effect on MVI, which are mutually verified and complementary. The texture parameters of GLCM could reflect tumor heterogeneity, which have great potential to help with preoperative decision. The combination of MR image features and texture analysis may improve the efficiency in prediction of MVI.
Collapse
Affiliation(s)
- Wei-Lin Yang
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China
| | - Fei Zhu
- Department of Radiology, West China Hospital, Sichuan University, 37# Guo Xue Xiang, Chengdu, Sichuan 610041, PR China
| | - Wei-Xia Chen
- Department of Radiology, West China Hospital, Sichuan University, 37# Guo Xue Xiang, Chengdu, Sichuan 610041, PR China.
| |
Collapse
|
|
15
|
Renzulli M, Pecorelli A, Brandi N, Marasco G, Adduci F, Tovoli F, Stefanini B, Granito A, Golfieri R. Radiological Features of Microvascular Invasion of Hepatocellular Carcinoma in Patients with Non-Alcoholic Fatty Liver Disease. GASTROENTEROLOGY INSIGHTS 2022; 13:275-285. [DOI: 10.3390/gastroent13030028] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2024] Open
Abstract
Background: The aim of the present study was to evaluate the presence and the prognostic value of the radiological signs of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: Between January 2015 and December 2017, all patients (91 patients) with de novo HCC or HCC recurrence occurring at least 2 years after the last treatment in NAFLD (36 patients) or with hepatitis C virus (HCV) liver disease (55 patients) were included. Each HCC was treated with liver resection and transplantation to obtain the anatomopathological confirmation of MVI. All patients had at least one available computed tomography (CT) scan or magnetic resonance imaging (MRI) performed no more than one month prior to the treatment. The clinical data of each patient, tumor burden (diameter, margins, two-trait predictor of venous invasion (TTPVI), and peritumoral enhancement), the recurrence rate (RR) after a 1-year follow-up, and the time to recurrence (TTR) were collected. Results: The NAFLD–HCC nodules were larger as compared to HCV–HCC (51 mm vs. 36 mm, p = 0.004) and showed a higher prevalence of TTPVI (38.9 vs. 20.0%, p = 0.058). At multivariate analysis, nodule diameter >50 mm was found to be the only independent prognostic factor of TTPVI (hazard ratio: 21.3, 95% confidence interval: 4.2–107.7, p < 0.001), and the presence of TTPVI was confirmed to be the only independent prognostic factors of recurrence (hazard ratio: 2.349, 95% confidence interval: 1.369–4.032, p = 0.002). No correlations were found between TTR and irregular tumor margins or peritumoral enhancement. Conclusion: The NAFLD–HCC patients had larger tumors at diagnosis and showed a more frequent presence of radiological signs of MVI as compared to the HCV–HCC patients. The MVI was related to a more rapid recurrence after curative treatments, demonstrating the prognostic value of this radiological diagnosis.
Collapse
Affiliation(s)
- Matteo Renzulli
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Anna Pecorelli
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Nicolò Brandi
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Giovanni Marasco
- Internal Medicine and Digestive Physiopathology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Francesco Adduci
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Francesco Tovoli
- Division of Internal Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Bernardo Stefanini
- Division of Internal Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Alessandro Granito
- Division of Internal Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Rita Golfieri
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy
| |
Collapse
|
|
16
|
Ghidaglia J, Golse N, Pascale A, Sebagh M, Besson FL. 18F-FDG /18F-Choline Dual-Tracer PET Behavior and Tumor Differentiation in HepatoCellular Carcinoma. A Systematic Review. Front Med (Lausanne) 2022; 9:924824. [PMID: 35872754 PMCID: PMC9300997 DOI: 10.3389/fmed.2022.924824] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/07/2022] [Indexed: 12/12/2022] Open
Abstract
Background Post-operative recurrence remains the strongest prognostic factor of resected hepatocellular carcinoma (HCC), making the accurate selection of patients with curable HCC a crucial issue. PET imaging combining both 18F-FDG and fatty acid synthase (FAS) radiotracers—such as Choline—has shown its interest for the initial staging and therapeutic management of patients with HCC, but its use is still not consensual. Importantly, the very first dual-tracer PET studies suggested 18F-FDG/FAS PET behavior be linked to the degree of differentiation of HCC, a major predictive factor of post-operative recurrence. Although this key molecular imaging concept may impact how dual-tracer PET will be used in early-stage HCC, its level of evidence remains largely unexplored. In this study, we conducted a systematic review of the available evidence-based data to clarify the relevance of dual 18F-FDG/18F-Choline PET in characterizing the degree of differentiation of HCC tumors. Methods A systematic search of the PubMed/Medline and Embase databases was performed up to November 2021. A systematic review of the dual-tracer 18F-FDG/18F-Choline PET behavior of histology-proven HCC according to their degree of differentiation was conducted. The overall quality of the included studies was critically assessed based on the STROBE guidelines. Information on study date, design, patient cohort characteristics, grade of differentiation of HCC tumors, and the dual-tracer PET behavior per HCC was independently extracted and summarized. Results From 440 records initially available, 6 full-text articles (99 histology-proven HCC) provided dual-tracer 18F-FDG/18F-Choline PET behavior per HCC tumor grade were included in the systematic review. Based on our analysis, 43/99 HCCs were reported to be well-differentiated, and 56/99 HCCs were reported to be less-differentiated tumors. In the well-differentiated subgroup, more than half were exclusively positive for 18F-Choline (51%), whereas 39% were positive for both 18F-FDG and 18F-Choline. In the less-differentiated subgroup, 37% of HCC patients were positive exclusively for FDG, 36% were positive for both 18F-FDG and 18F-Choline, and 25% were positive exclusively for 18F-Choline. Conclusion The 18F-FDG/18F-Choline dual-tracer PET behavior of uptake shows high overlap between well- and less differentiated HCC, making the characterization of tumors challenging based on such PET combination alone. Given our growing knowledge of the molecular complexity of HCC, further studies are necessary to refine our understanding of radiotracers’ behavior in this field and improve the usefulness of PET imaging in the clinical decision process of HCC.
Collapse
Affiliation(s)
- Jérôme Ghidaglia
- Department of Biophysics and Nuclear Medicine-Molecular Imaging, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Nicolas Golse
- Centre Hépato Biliaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Villejuif, France.,Université Paris-Saclay, INSERM, Physiopathogénèse et Traitement des Maladies du Foie, UMR-S 1193, Gif-sur-Yvette, France
| | - Alina Pascale
- Centre Hépato Biliaire, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Villejuif, France
| | - Mylène Sebagh
- Department of Pathology, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Florent L Besson
- Department of Biophysics and Nuclear Medicine-Molecular Imaging, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France.,Université Paris-Saclay, School of Medicine, Le Kremlin-Bicêtre, France.,Université Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, France
| |
Collapse
|
|
17
|
Li YM, Zhu YM, Gao LM, Han ZW, Chen XJ, Yan C, Ye RP, Cao DR. Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma. World J Gastroenterol 2022; 28:2733-2747. [PMID: 35979164 PMCID: PMC9260872 DOI: 10.3748/wjg.v28.i24.2733] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 03/20/2022] [Accepted: 05/12/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The prognosis of hepatocellular carcinoma (HCC) remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy. In terms of recent studies, microvascular invasion (MVI) is one of the potential predictors of recurrence. Accurate preoperative prediction of MVI is potentially beneficial to the optimization of treatment planning.
AIM To develop a radiomic analysis model based on pre-operative magnetic resonance imaging (MRI) data to predict MVI in HCC.
METHODS A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation, among whom 73 were found to have MVI and 40 were not. All the patients received preoperative examination by Gd-enhanced MRI and then curative hepatectomy. We manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI, namely, the regions of interest. Quantitative analyses included most discriminant factors (MDFs) developed using linear discriminant analysis algorithm and histogram analysis with MaZda software. Independent significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression analysis. Prediction ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic (ROC) curve analysis. Five-fold cross-validation was also applied via R software.
RESULTS The area under the ROC curve (AUC) of the MDF (0.77-0.85) outperformed that of histogram parameters (0.51-0.74). After multivariate analysis, MDF values of the arterial and portal venous phase, and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI (P < 0.05). The AUC value of the model was 0.939 [95% confidence interval (CI): 0.893-0.984, standard error: 0.023]. The result of internal five-fold cross-validation (AUC: 0.912, 95%CI: 0.841-0.959, standard error: 0.0298) also showed favorable predictive efficacy.
CONCLUSION Noninvasive MRI radiomic model based on MDF values and imaging biomarkers may be useful to make preoperative prediction of MVI in patients with primary HCC.
Collapse
Affiliation(s)
- Yue-Ming Li
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
- Key Laboratory of Radiation Biology (Fujian Medical University), Fujian Province University, Fuzhou 350005, Fujian Province, China
| | - Yue-Min Zhu
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Lan-Mei Gao
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Ze-Wen Han
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Xiao-Jie Chen
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Chuan Yan
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Rong-Ping Ye
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Dai-Rong Cao
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| |
Collapse
|
|
18
|
Wang F, Yan CY, Wang CH, Yang Y, Zhang D. The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma. Front Oncol 2022; 12:884854. [PMID: 35646649 PMCID: PMC9131658 DOI: 10.3389/fonc.2022.884854] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 03/31/2022] [Indexed: 12/14/2022] Open
Abstract
Background Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC. Methods PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis. Results The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect. Conclusion DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.
Collapse
Affiliation(s)
- Fei Wang
- Department of Medical Imaging, Luzhou People's Hospital, Luzhou, China.,Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Chun Yue Yan
- Department of Obstetrics, Luzhou People's Hospital, Luzhou, China
| | - Cai Hong Wang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Yan Yang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| |
Collapse
|
|
19
|
Lv K, Cao X, Du P, Fu JY, Geng DY, Zhang J. Radiomics for the detection of microvascular invasion in hepatocellular carcinoma. World J Gastroenterol 2022; 28:2176-2183. [PMID: 35721882 PMCID: PMC9157623 DOI: 10.3748/wjg.v28.i20.2176] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/09/2022] [Accepted: 04/25/2022] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer, accounting for about 90% of liver cancer cases. It is currently the fifth most common cancer in the world and the third leading cause of cancer-related mortality. Moreover, recurrence of HCC is common. Microvascular invasion (MVI) is a major factor associated with recurrence in postoperative HCC. It is difficult to evaluate MVI using traditional imaging modalities. Currently, MVI is assessed primarily through pathological and immunohistochemical analyses of postoperative tissue samples. Needle biopsy is the primary method used to confirm MVI diagnosis before surgery. As the puncture specimens represent just a small part of the tumor, and given the heterogeneity of HCC, biopsy samples may yield false-negative results. Radiomics, an emerging, powerful, and non-invasive tool based on various imaging modalities, such as computed tomography, magnetic resonance imaging, ultrasound, and positron emission tomography, can predict the HCC-MVI status preoperatively by delineating the tumor and/or the regions at a certain distance from the surface of the tumor to extract the image features. Although positive results have been reported for radiomics, its drawbacks have limited its clinical translation. This article reviews the application of radiomics, based on various imaging modalities, in preoperative evaluation of HCC-MVI and explores future research directions that facilitate its clinical translation.
Collapse
Affiliation(s)
- Kun Lv
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Xin Cao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai 200040, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Science and Technology Commission of Shanghai Municipality, Shanghai 200040, China
- Institute of Intelligent Imaging Phenomics, International Human Phenome Institutes (Shanghai), Shanghai 200040, China
| | - Peng Du
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jun-Yan Fu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Dao-Ying Geng
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai 200040, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Science and Technology Commission of Shanghai Municipality, Shanghai 200040, China
- Institute of Intelligent Imaging Phenomics, International Human Phenome Institutes (Shanghai), Shanghai 200040, China
| | - Jun Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai 200040, China
- Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research, Science and Technology Commission of Shanghai Municipality, Shanghai 200040, China
- Institute of Intelligent Imaging Phenomics, International Human Phenome Institutes (Shanghai), Shanghai 200040, China
| |
Collapse
|
|
20
|
Wang H, Lu Y, Liu R, Wang L, Liu Q, Han S. A Non-Invasive Nomogram for Preoperative Prediction of Microvascular Invasion Risk in Hepatocellular Carcinoma. Front Oncol 2022; 11:745085. [PMID: 35004273 PMCID: PMC8739965 DOI: 10.3389/fonc.2021.745085] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 12/01/2021] [Indexed: 12/24/2022] Open
Abstract
Background Microvascular invasion (MVI) is a significant predictive factor for early recurrence, metastasis, and poor prognosis of hepatocellular carcinoma. The aim of the present study is to identify preoperative factors for predicting MVI, in addition to develop and validate non-invasive nomogram for predicting MVI. Methods A total of 381 patients with resected HCC were enrolled and divided into a training cohort (n = 267) and a validation cohort (n = 114). Serum VEGF-A level was examined by enzyme-linked immunosorbent assay (ELISA). Risk factors for MVI were assessed based on univariate and multivariate analyses in the training cohort. A nomogram incorporating independent risk predictors was established and validated. Result The serum VEGF-A levels in the MVI positive group (n = 198) and MVI negative group (n = 183) were 215.25 ± 105.68 pg/ml and 86.52 ± 62.45 pg/ml, respectively (P <0.05). Serum VEGF-A concentration ≥138.30 pg/ml was an independent risk factor of MVI (OR: 33.088; 95%CI: 12.871–85.057; P <0.001). Higher serum concentrations of AFP and VEGF-A, lower lymphocyte count, peritumoral enhancement, irregular tumor shape, and intratumoral artery were identified as significant predictors for MVI. The nomogram indicated excellent predictive performance with an AUROC of 0.948 (95% CI: 0.923–0.973) and 0.881 (95% CI: 0.820–0.942) in the training and validation cohorts, respectively. The nomogram showed a good model fit and calibration. Conclusions Higher serum concentrations of AFP and VEGF-A, lower lymphocyte count, peritumoral enhancement, irregular tumor shape, and intratumoral artery are promising markers for MVI prediction in HCC. A reliable non-invasive nomogram which incorporated blood biomarkers and imaging risk factors was established and validated. The nomogram achieved desirable effectiveness in preoperatively predicting MVI in HCC patients.
Collapse
Affiliation(s)
- Huanhuan Wang
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Ye Lu
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Runkun Liu
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Liang Wang
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Qingguang Liu
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shaoshan Han
- Department of Hepatobiliary Surgery, The first Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| |
Collapse
|
|
21
|
Tang Y, Wang T, Ju W, Li F, Zhang Q, Chen Z, Gong J, Zhao Q, Wang D, Chen M, Guo Z, He X. Ischemic-Free Liver Transplantation Reduces the Recurrence of Hepatocellular Carcinoma After Liver Transplantation. Front Oncol 2021; 11:773535. [PMID: 34966679 PMCID: PMC8711268 DOI: 10.3389/fonc.2021.773535] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 11/22/2021] [Indexed: 12/12/2022] Open
Abstract
Ischemia reperfusion injury (IRI) is an adverse factor for hepatocellular carcinoma (HCC) recurrence after liver transplantation. Ischemic-free liver transplantation (IFLT) is a novel transplant procedure that can largely reduce or even prevent IRI, but the clinical relevance of IFLT and the recurrence of HCC after liver transplantation are still unknown. This retrospective study compared survival outcomes, HCC recurrence, perioperative data and IRI severity following liver transplantation (LT). 30 patients received IFLT and 196 patients received conventional liver transplantation (CLT) were chosen for the entire cohort between June 2017 and August 2020. A 1:3 propensity score matching was performed, 30 IFLT recipients and 85 matched CLT patients were enrolled in propensity-matched cohorts. An univariate and multivariate Cox regression analysis was performed, and showed surgical procedure (CLT vs IFLT) was an independent prognostic factor (HR 3.728, 95% CI 1.172-11.861, P=0.026) for recurrence free survival (RFS) in HCC patients following liver transplantation. In the Kaplan–Meier analysis, the RFS rates at 1 and 3 years after LT in recipients with HCC in the IFLT group were significantly higher than those in the CLT group both in the entire cohort and propensity-matched cohort (P=0.006 and P=0.048, respectively). In addition, patients in the IFLT group had a lower serum lactate level, lower serum ALT level and serum AST level on postoperative Day 1. LT recipients with HCC in the IFLT group had a lower incidence of early allograft dysfunction than LT recipients with HCC in the CLT group. Histological analysis showed no obvious hepatocyte necrosis or apoptosis in IFLT group. In conclusion, IFLT can significantly reduce IRI damage and has the potential to be a useful strategy to reduce HCC recurrence after liver transplantation.
Collapse
Affiliation(s)
- Yunhua Tang
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Tielong Wang
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Weiqiang Ju
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Fangcong Li
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Qi Zhang
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Zhitao Chen
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Jinlong Gong
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Qiang Zhao
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Dongping Wang
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Maogen Chen
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Zhiyong Guo
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| | - Xiaoshun He
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China.,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China
| |
Collapse
|
|
22
|
Wang J, Ding ZW, Chen K, Liu YZ, Li N, Hu MG. A predictive and prognostic model for hepatocellular carcinoma with microvascular invasion based TCGA database genomics. BMC Cancer 2021; 21:1337. [PMID: 34911488 PMCID: PMC8675478 DOI: 10.1186/s12885-021-09047-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 11/15/2021] [Indexed: 02/08/2023] Open
Abstract
Background Microvascular invasion (MVI) adversely affects postoperative long-term survival outcomes in patients with hepatocellular carcinoma (HCC). There is no study addressing genetic changes in HCC patients with MVI. We first screened differentially expressed genes (DEGs) in patients with and without MVI based on TCGA data, established a prediction model and explored the prognostic value of DEGs for HCC patients with MVI. Methods In this paper, gene expression and clinical data of liver cancer patients were downloaded from the TCGA database. The DEG analysis was conducted using DESeq2. Using the least absolute shrinkage and selection operator, MVI-status-related genes were identified. A Kaplan-Meier survival analysis was performed using these genes. Finally, we validated two genes, HOXD9 and HOXD10, using two sets of HCC tissue microarrays from 260 patients. Results Twenty-three MVI-status-related key genes were identified. Based on the key genes, we built a classification model using random forest and time-dependent receiver operating characteristic (ROC), which reached 0.814. Then, we performed a survival analysis and found ten genes had a significant difference in survival time. Simultaneously, using two sets of 260 patients’ HCC tissue microarrays, we validated two key genes, HOXD9 and HOXD10. Our study indicated that HOXD9 and HOXD10 were overexpressed in HCC patients with MVI compared with patients without MVI, and patients with MVI with HOXD9 and 10 overexpression had a poorer prognosis than patients with MVI with low expression of HOXD9 and 10. Conclusion We established an accurate TCGA database-based genomics prediction model for preoperative MVI risk and studied the prognostic value of DEGs for HCC patients with MVI. These DEGs that are related to MVI warrant further study regarding the occurrence and development of MVI. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-09047-1.
Collapse
Affiliation(s)
- Jin Wang
- Faculty of Hepato-Biliary-Pancreatic Surgery, Chinese People's Liberation Army (PLA) General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Zhi-Wen Ding
- Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, 225 Changhai Road, Shanghai, 200433, China
| | - Kuang Chen
- Faculty of Hepato-Biliary-Pancreatic Surgery, Chinese People's Liberation Army (PLA) General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Yan-Zhe Liu
- Faculty of Hepato-Biliary-Pancreatic Surgery, Chinese People's Liberation Army (PLA) General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Nan Li
- Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, 225 Changhai Road, Shanghai, 200433, China.
| | - Ming-Gen Hu
- Faculty of Hepato-Biliary-Pancreatic Surgery, Chinese People's Liberation Army (PLA) General Hospital, 28 Fuxing Road, Beijing, 100853, China.
| |
Collapse
|
|
23
|
Gong XQ, Tao YY, Wu Y, Liu N, Yu X, Wang R, Zheng J, Liu N, Huang XH, Li JD, Yang G, Wei XQ, Yang L, Zhang XM. Progress of MRI Radiomics in Hepatocellular Carcinoma. Front Oncol 2021; 11:698373. [PMID: 34616673 PMCID: PMC8488263 DOI: 10.3389/fonc.2021.698373] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/31/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world and the third leading cause of cancer-related death. Although the diagnostic scheme of HCC is currently undergoing refinement, the prognosis of HCC is still not satisfactory. In addition to certain factors, such as tumor size and number and vascular invasion displayed on traditional imaging, some histopathological features and gene expression parameters are also important for the prognosis of HCC patients. However, most parameters are based on postoperative pathological examinations, which cannot help with preoperative decision-making. As a new field, radiomics extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes noninvasively before surgery, rendering it a powerful aid for making personalized treatment decisions preoperatively. OBJECTIVE This study reviewed the workflow of radiomics and the research progress on magnetic resonance imaging (MRI) radiomics in the diagnosis and treatment of HCC. METHODS A literature review was conducted by searching PubMed for search of relevant peer-reviewed articles published from May 2017 to June 2021.The search keywords included HCC, MRI, radiomics, deep learning, artificial intelligence, machine learning, neural network, texture analysis, diagnosis, histopathology, microvascular invasion, surgical resection, radiofrequency, recurrence, relapse, transarterial chemoembolization, targeted therapy, immunotherapy, therapeutic response, and prognosis. RESULTS Radiomics features on MRI can be used as biomarkers to determine the differential diagnosis, histological grade, microvascular invasion status, gene expression status, local and systemic therapeutic responses, and prognosis of HCC patients. CONCLUSION Radiomics is a promising new imaging method. MRI radiomics has high application value in the diagnosis and treatment of HCC.
Collapse
Affiliation(s)
- Xue-Qin Gong
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Yun-Yun Tao
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Yao–Kun Wu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ning Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xi Yu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Ran Wang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Jing Zheng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Nian Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Hua Huang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Jing-Dong Li
- Department of Hepatocellular Surgery, Institute of Hepato-Biliary-Intestinal Disease, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Gang Yang
- Department of Hepatocellular Surgery, Institute of Hepato-Biliary-Intestinal Disease, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Qin Wei
- School of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| |
Collapse
|
|
24
|
Zhang D, Wei Q, Wu GG, Zhang XY, Lu WW, Lv WZ, Liao JT, Cui XW, Ni XJ, Dietrich CF. Preoperative Prediction of Microvascular Invasion in Patients With Hepatocellular Carcinoma Based on Radiomics Nomogram Using Contrast-Enhanced Ultrasound. Front Oncol 2021; 11:709339. [PMID: 34557410 PMCID: PMC8453164 DOI: 10.3389/fonc.2021.709339] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 08/13/2021] [Indexed: 01/27/2023] Open
Abstract
PURPOSE This study aimed to develop a radiomics nomogram based on contrast-enhanced ultrasound (CEUS) for preoperatively assessing microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS A retrospective dataset of 313 HCC patients who underwent CEUS between September 20, 2016 and March 20, 2020 was enrolled in our study. The study population was randomly grouped as a primary dataset of 192 patients and a validation dataset of 121 patients. Radiomics features were extracted from the B-mode (BM), artery phase (AP), portal venous phase (PVP), and delay phase (DP) images of preoperatively acquired CEUS of each patient. After feature selection, the BM, AP, PVP, and DP radiomics scores (Rad-score) were constructed from the primary dataset. The four radiomics scores and clinical factors were used for multivariate logistic regression analysis, and a radiomics nomogram was then developed. We also built a preoperative clinical prediction model for comparison. The performance of the radiomics nomogram was evaluated via calibration, discrimination, and clinical usefulness. RESULTS Multivariate analysis indicated that the PVP and DP Rad-score, tumor size, and AFP (alpha-fetoprotein) level were independent risk predictors associated with MVI. The radiomics nomogram incorporating these four predictors revealed a superior discrimination to the clinical model (based on tumor size and AFP level) in the primary dataset (AUC: 0.849 vs. 0.690; p < 0.001) and validation dataset (AUC: 0.788 vs. 0.661; p = 0.008), with a good calibration. Decision curve analysis also confirmed that the radiomics nomogram was clinically useful. Furthermore, the significant improvement of net reclassification index (NRI) and integrated discriminatory improvement (IDI) implied that the PVP and DP radiomics signatures may be very useful biomarkers for MVI prediction in HCC. CONCLUSION The CEUS-based radiomics nomogram showed a favorable predictive value for the preoperative identification of MVI in HCC patients and could guide a more appropriate surgical planning.
Collapse
Affiliation(s)
- Di Zhang
- Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China
| | - Qi Wei
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ge-Ge Wu
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xian-Ya Zhang
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wen-Wu Lu
- Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China
| | - Wen-Zhi Lv
- Department of Artificial Intelligence, Julei Technology Company, Wuhan, China
| | - Jin-Tang Liao
- Department of Diagnostic Ultrasound, Xiang Ya Hospital, Central South University, Changsha, China
| | - Xin-Wu Cui
- Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xue-Jun Ni
- Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China
| | | |
Collapse
|
|
25
|
Kim K, Kim SJ. Diagnostic test accuracies of F-18 FDG PET/CT for prediction of microvascular invasion of hepatocellular carcinoma: A meta-analysis. Clin Imaging 2021; 79:251-258. [PMID: 34157501 DOI: 10.1016/j.clinimag.2021.06.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/04/2021] [Accepted: 06/11/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE The aim of the current meta-analysis was to evaluate diagnostic accuracies of preoperative F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) or positron emission tomography/computed tomography (PET/CT) for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS The scientific database such as PubMed, Cochrane, and Embase database were searched for studies evaluating diagnostic accuracies of preoperative F-18 FDG PET or PET/CT for prediction of MVI in HCC patients up to November 30, 2020. RESULTS Fourteen eligible studies (1276 patients) were enrolled. The pooled sensitivity for F-18 FDG PET or PET/CT was 0.67 (95% CI; 0.57-0.76) with heterogeneity and a pooled specificity of 0.80 (95% CI; 0.74-0.85) with heterogeneity. Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 3.3 (95% CI; 2.5-4.5) and negative likelihood ratio (LR-) of 0.41 (95% CI; 0.31-0.55). The pooled diagnostic odds ratio (DOR) was 8 (95% CI; 5-14). Summary receiver operating characteristic (ROC) curve indicates that the area under the curve was 0.81 (95% CI; 0.78-0.84). CONCLUSION The current meta-analysis showed a low sensitivity and moderate specificity of F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients. F-18 FDG PET or PET/CT might not be useful for the preoperative prediction of MVI in HCC patients and should not be used to exclude MVI. Therefore, cautious application and interpretation should be paid to the F-18 FDG PET or PET/CT for the prediction of MVI in HCC patients preoperatively.
Collapse
Affiliation(s)
- Keunyoung Kim
- Department of Nuclear Medicine, Pusan National University Hospital, Busan 49241, Republic of Korea
| | - Seong-Jang Kim
- Department of Nuclear Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; BioMedical Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea; Department of Nuclear Medicine, College of Medicine, Pusan National University, Yangsan 50612, Republic of Korea.
| |
Collapse
|
|
26
|
Krishnan MS, KD AR, Park J, Arjunan V, Marques FJG, Bermudez A, Girvan OA, Hoang NS, Yin J, Nguyen MH, Kothary N, Pitteri S, Felsher DW, Dhanasekaran R. Genomic Analysis of Vascular Invasion in HCC Reveals Molecular Drivers and Predictive Biomarkers. Hepatology 2021; 73:2342-2360. [PMID: 33140851 PMCID: PMC8115767 DOI: 10.1002/hep.31614] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 09/29/2020] [Accepted: 10/03/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND AIMS Vascular invasion (VI) is a critical risk factor for HCC recurrence and poor survival. The molecular drivers of vascular invasion in HCC are open for investigation. Deciphering the molecular landscape of invasive HCC will help identify therapeutic targets and noninvasive biomarkers. APPROACH AND RESULTS To this end, we undertook this study to evaluate the genomic, transcriptomic, and proteomic profile of tumors with VI using the multiplatform cancer genome atlas (The Cancer Genome Atlas; TCGA) data (n = 373). In the TCGA Liver Hepatocellular Carcinoma cohort, macrovascular invasion was present in 5% (n = 17) of tumors and microvascular invasion in 25% (n = 94) of tumors. Functional pathway analysis revealed that the MYC oncogene was a common upstream regulator of the mRNA, miRNA, and proteomic changes in VI. We performed comparative proteomic analyses of invasive human HCC and MYC-driven murine HCC and identified fibronectin to be a proteomic biomarker of invasive HCC (mouse fibronectin 1 [Fn1], P = 1.7 × 10-11 ; human FN1, P = 1.5 × 10-4 ) conserved across the two species. Mechanistically, we show that FN1 promotes the migratory and invasive phenotype of HCC cancer cells. We demonstrate tissue overexpression of fibronectin in human HCC using a large independent cohort of human HCC tissue microarray (n = 153; P < 0.001). Lastly, we showed that plasma fibronectin levels were significantly elevated in patients with HCC (n = 35; mean = 307.7 μg/mL; SEM = 35.9) when compared to cirrhosis (n = 10; mean = 41.8 μg/mL; SEM = 13.3; P < 0.0001). CONCLUSIONS Our study evaluates the molecular landscape of tumors with VI, identifying distinct transcriptional, epigenetic, and proteomic changes driven by the MYC oncogene. We show that MYC up-regulates fibronectin expression, which promotes HCC invasiveness. In addition, we identify fibronectin to be a promising noninvasive proteomic biomarker of VI in HCC.
Collapse
Affiliation(s)
- Maya S. Krishnan
- Division of Oncology, Department of Medicine, Stanford University, Stanford, CA
| | - Anand Rajan KD
- Department of Pathology, University of Iowa, Iowa City, IA, USA
| | - Jangho Park
- Division of Oncology, Department of Medicine, Stanford University, Stanford, CA
| | - Vinodhini Arjunan
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University, Stanford, CA
| | | | - Abel Bermudez
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford University, CA
| | - Olivia A. Girvan
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford University, CA
| | - Nam S. Hoang
- Division of Interventional Radiology, Department of Radiology, Stanford University, Stanford, CA
| | - Jun Yin
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Mindie H. Nguyen
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University, Stanford, CA
| | - Nishita Kothary
- Division of Interventional Radiology, Department of Radiology, Stanford University, Stanford, CA
| | - Sharon Pitteri
- Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford University, CA
| | - Dean W. Felsher
- Division of Oncology, Department of Medicine, Stanford University, Stanford, CA
| | - Renumathy Dhanasekaran
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University, Stanford, CA
| |
Collapse
|
|
27
|
Dai H, Lu M, Huang B, Tang M, Pang T, Liao B, Cai H, Huang M, Zhou Y, Chen X, Ding H, Feng ST. Considerable effects of imaging sequences, feature extraction, feature selection, and classifiers on radiomics-based prediction of microvascular invasion in hepatocellular carcinoma using magnetic resonance imaging. Quant Imaging Med Surg 2021; 11:1836-1853. [PMID: 33936969 PMCID: PMC8047362 DOI: 10.21037/qims-20-218] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Accepted: 12/02/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Microvascular invasion (MVI) has a significant effect on the prognosis of hepatocellular carcinoma (HCC), but its preoperative identification is challenging. Radiomics features extracted from medical images, such as magnetic resonance (MR) images, can be used to predict MVI. In this study, we explored the effects of different imaging sequences, feature extraction and selection methods, and classifiers on the performance of HCC MVI predictive models. METHODS After screening against the inclusion criteria, 69 patients with HCC and preoperative gadoxetic acid-enhanced MR images were enrolled. In total, 167 features were extracted from the MR images of each sequence for each patient. Experiments were designed to investigate the effects of imaging sequence, number of gray levels (Ng), quantization algorithm, feature selection method, and classifiers on the performance of radiomics biomarkers in the prediction of HCC MVI. We trained and tested these models using leave-one-out cross-validation (LOOCV). RESULTS The radiomics model based on the images of the hepatobiliary phase (HBP) had better predictive performance than those based on the arterial phase (AP), portal venous phase (PVP), and pre-enhanced T1-weighted images [area under the receiver operating characteristic (ROC) curve (AUC) =0.792 vs. 0.641/0.634/0.620, P=0.041/0.021/0.010, respectively]. Compared with the equal-probability and Lloyd-Max algorithms, the radiomics features obtained using the Uniform quantization algorithm had a better performance (AUC =0.643/0.666 vs. 0.792, P=0.002/0.003, respectively). Among the values of 8, 16, 32, 64, and 128, the best predictive performance was achieved when the Ng was 64 (AUC =0.792 vs. 0.584/0.697/0.677/0.734, P<0.001/P=0.039/0.001/0.137, respectively). We used a two-stage feature selection method which combined the least absolute shrinkage and selection operator (LASSO) and recursive feature elimination (RFE) gradient boosting decision tree (GBDT), which achieved better stability than and outperformed LASSO, minimum redundancy maximum relevance (mRMR), and support vector machine (SVM)-RFE (stability =0.967 vs. 0.837/0.623/0.390, respectively; AUC =0.850 vs. 0.792/0.713/0.699, P=0.142/0.007/0.003, respectively). The model based on the radiomics features of HBP images using the GBDT classifier showed a better performance for the preoperative prediction of MVI compared with logistic regression (LR), SVM, and random forest (RF) classifiers (AUC =0.895 vs. 0.850/0.834/0.884, P=0.558/0.229/0.058, respectively). With the optimal combination of these factors, we established the best model, which had an AUC of 0.895, accuracy of 87.0%, specificity of 82.5%, and sensitivity of 93.1%. CONCLUSIONS Imaging sequences, feature extraction and selection methods, and classifiers can have a considerable effect on the predictive performance of radiomics models for HCC MVI.
Collapse
Affiliation(s)
- Houjiao Dai
- Medical AI Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Shenzhen University Clinical Research Center for Neurological Diseases, Shenzhen University General Hospital, Shenzhen, China
| | - Minhua Lu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Shenzhen University Clinical Research Center for Neurological Diseases, Shenzhen University General Hospital, Shenzhen, China
| | - Mimi Tang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Tiantian Pang
- School of Computer Science and Software Engineering, Jilin University, Changchun, China
| | - Bing Liao
- Department of Pathology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huasong Cai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Mengqi Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yongjin Zhou
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Marshall Laboratory of Biomedical Engineering, Shenzhen, China
| | - Xin Chen
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Huijun Ding
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| |
Collapse
|
|
28
|
Yang J, Zhu S, Yong J, Xia L, Qian X, Yang J, Hu X, Li Y, Wang C, Peng W, Zhang L, Deng M, Pan W. A Nomogram for Preoperative Estimation of Microvascular Invasion Risk in Hepatocellular Carcinoma: Single-Center Analyses With Internal Validation. Front Oncol 2021; 11:616976. [PMID: 33747929 PMCID: PMC7970183 DOI: 10.3389/fonc.2021.616976] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/25/2021] [Indexed: 12/21/2022] Open
Abstract
Background Microvascular invasion (MVI) is highly associated with poor prognosis in patients with liver cancer. Predicting MVI before surgery is helpful for surgeons to better make surgical plan. In this study, we aim at establishing a nomogram to preoperatively predict the occurrence of microvascular invasion in liver cancer. Method A total of 405 patients with postoperative pathological reports who underwent curative hepatocellular carcinoma resection in the Third Affiliated Hospital of Sun Yat-sen University from 2013 to 2015 were collected in this study. Among these patients, 290 were randomly assigned to the development group while others were assigned to the validation group. The MVI predictive factors were selected by Lasso regression analysis. Nomogram was established to preoperatively predict the MVI risk in HCC based on these predictive factors. The discrimination, calibration, and effectiveness of nomogram were evaluated by internal validation. Results Lasso regression analysis revealed that discomfort of right upper abdomen, vascular invasion, lymph node metastases, unclear tumor boundary, tumor necrosis, tumor size, higher alkaline phosphatase were predictive MVI factors in HCC. The nomogram was established with the value of AUROC 0.757 (0.716–0.809) and 0.768 (0.703–0.814) in the development and the validation groups. Well-fitted calibration was in both development and validation groups. Decision curve analysis confirmed that the predictive model provided more benefit than treat all or none patients. The predictive model demonstrated sensitivity of 58.7%, specificity of 80.7% at the cut-off value of 0.312. Conclusion Nomogram was established for predicting preoperative risk of MVI in HCC. Better treatment plans can be formulated according to the predicted results.
Collapse
Affiliation(s)
- Jiarui Yang
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shuguang Zhu
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Juanjuan Yong
- Department of Pathology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Long Xia
- Department of Hepatic Surgery and Liver Transplantation Center, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiangjun Qian
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jiawei Yang
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Xueqiao Hu
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yuxuan Li
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chusi Wang
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.,Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wenguang Peng
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Lei Zhang
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Meihai Deng
- Department of Hepatobiliary Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Weidong Pan
- Department of Biliary-Pancreatic Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| |
Collapse
|
|
29
|
Chen G, Wang R, Zhang C, Gui L, Xue Y, Ren X, Li Z, Wang S, Zhang Z, Zhao J, Zhang H, Yao C, Wang J, Liu J. Integration of pre-surgical blood test results predict microvascular invasion risk in hepatocellular carcinoma. Comput Struct Biotechnol J 2021; 19:826-834. [PMID: 33598098 PMCID: PMC7848436 DOI: 10.1016/j.csbj.2021.01.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/07/2021] [Accepted: 01/08/2021] [Indexed: 12/12/2022] Open
Abstract
Microvascular invasion (MVI) is one of the most important factors leading to poor prognosis for hepatocellular carcinoma (HCC) patients, and detection of MVI prior to surgical operation could great benefit patient's prognosis and survival. Since it is still lacking effective non-invasive strategy for MVI detection before surgery, novel MVI determination approaches were in urgent need. In this study, complete blood count, blood test and AFP test results are utilized to perform preoperative prediction of MVI based on a novel interpretable deep learning method to quantify the risk of MVI. The proposed method termed as "Interpretation based Risk Prediction" can estimate the MVI risk precisely and achieve better performance compared with the state-of-art MVI risk estimation methods with concordance indexes of 0.9341 and 0.9052 on the training cohort and the independent validation cohort, respectively. Moreover, further analyses of the model outputs demonstrate that the quantified risk of MVI from our model could serve as an independent preoperative risk factor for both recurrence-free survival and overall survival of HCC patients. Thus, our model showed great potential in quantification of MVI risk and prediction of prognosis for HCC patients.
Collapse
Affiliation(s)
- Geng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Rendong Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Chen Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Lijia Gui
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Yuan Xue
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Xianlin Ren
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, China
| | - Zhenli Li
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, China
| | - Sijia Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Zhenxi Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Jing Zhao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Huqing Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Cuiping Yao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Jing Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China
| | - Jingfeng Liu
- The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, China
| |
Collapse
|
|
30
|
Abstract
The diagnosis of hepatocellular carcinoma relies largely on non-invasive imaging, and is well suited for radiomics analysis. Radiomics is an emerging method for quantification of tumor heterogeneity by mathematically analyzing the spatial distribution and relationships of gray levels in medical images. The published studies on radiomics analysis of HCC provide encouraging data demonstrating potential utility for prediction of tumor biology, molecular profiles, post-therapy response, and outcome. The combination of radiomics data and clinical/laboratory information provides added value in many studies. Radiomics is a multi-step process that requires optimization and standardization, the development of semi-automated or automated segmentation methods, robust data quality control, and refinement of algorithms and modeling approaches for high-throughput data analysis. While radiomics remains largely in the research setting, the strong associations of predictive models and nomograms with certain pathologic, molecular, and immune markers with tumor aggressiveness and patient outcomes, provide great potential for clinical applications to inform optimized treatment strategies and patient prognosis.
Collapse
|
|
31
|
Zhang C, Zhao R, Chen F, Zhu Y, Chen L. Preoperative prediction of microvascular invasion in non-metastatic hepatocellular carcinoma based on nomogram analysis. Transl Oncol 2020; 14:100875. [PMID: 32979686 PMCID: PMC7516277 DOI: 10.1016/j.tranon.2020.100875] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 01/27/2023] Open
Abstract
Purpose The presence of microvascular invasion (MVI) is an unfavorable prognostic factor for hepatocellular carcinoma (HCC). This study aimed to construct a nomogram-based preoperative prediction model of MVI, thereby assisting to preoperatively select proper surgical procedures. Methods A total of 714 non-metastatic HCC patients undergoing radical hepatectomy were retrospectively selected from Zhongshan Hospital between 2010 and 2018, followed by random assignment into training (N = 520) and validation cohorts (N = 194). Nomogram-based prediction model for MVI risk was constructed by incorporating independent risk factors of MVI presence identified from multivariate backward logistic regression analysis in the training cohort. The performance of nomogram was evaluated by calibration curve and ROC curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram. Results In total, 503 (70.4%) patients presented MVI. Multivariate analysis in the training cohort revealed that age (OR: 0.98), alpha-fetoprotein (≥400 ng/mL) (OR: 2.34), tumor size (>5 cm) (OR: 3.15), cirrhosis (OR: 2.03) and γ-glutamyl transpeptidase (OR: 1.61) were significantly associated with MVI presence. The incorporation of five risk factors into a nomogram-based preoperative estimation of MVI risk demonstrated satisfactory discriminative capacity, with C-index of 0.702 and 0.690 in training and validation cohorts, respectively. Calibration curve showed good agreement between actual and predicted MVI risks. Finally, DCA revealed the clinical utility of the nomogram. Conclusion The nomogram showed a satisfactory discriminative capacity of MVI risk in HCC patients, and could be used to preoperatively estimate MVI risk, thereby establishing more rational therapeutic strategies.
Collapse
Affiliation(s)
- Chihao Zhang
- Department of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Baoshan, Shanghai, China
| | - Ran Zhao
- Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China
| | - Fancheng Chen
- Zhongshan Hospital, School of Medicine, Fudan University, Shanghai, China
| | - Yiming Zhu
- Department of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Baoshan, Shanghai, China.
| | - Liubo Chen
- Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education, Key Laboratory of Molecular Biology in Medical Sciences, Zhejiang Province, China), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| |
Collapse
|
|
32
|
Verna EC, Patel YA, Aggarwal A, Desai AP, Frenette C, Pillai AA, Salgia R, Seetharam A, Sharma P, Sherman C, Tsoulfas G, Yao FY. Liver transplantation for hepatocellular carcinoma: Management after the transplant. Am J Transplant 2020; 20:333-347. [PMID: 31710773 DOI: 10.1111/ajt.15697] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Revised: 10/03/2019] [Accepted: 10/21/2019] [Indexed: 02/05/2023]
Abstract
Hepatocellular carcinoma (HCC) is an increasingly common indication for liver transplantation (LT) in the United States and in many parts of the world. In the last decade, significant work has been done to better understand how to risk stratify LT candidates for recurrence of HCC following transplant using a combination of biomarker and imaging findings. However, despite the high frequency of HCC in the LT population, guidance regarding posttransplant management is lacking. In particular, there is no current evidence to support specific post-LT surveillance strategies, leading to significant heterogeneity in practices. In addition, there are no current recommendations regarding recurrence prevention, including immunosuppression regimen or secondary prevention with adjuvant chemotherapy. Finally, guidance on treatment of disease recurrence is also lacking and there is significant controversy about the use of immunotherapy in transplant recipients due to the risk of rejection. Thus, outcomes for patients with recurrence are poor. This paper therefore provides a comprehensive review of the current literature on post-LT management of patients with HCC and identifies gaps in our current knowledge that are in urgent need of further investigation.
Collapse
Affiliation(s)
- Elizabeth C Verna
- Center for Liver Disease and Transplantation, Columbia University, New York, New York, USA
| | - Yuval A Patel
- Division of Gastroenterology, Department of Medicine, Duke University, Durham, North Carolina, USA
| | - Avin Aggarwal
- Department of Medicine, Division of Gastroenterology and Hepatology, University of Arizona College of Medicine, Tuscon, Arizona, USA
| | - Archita P Desai
- Division of Gastroenterology, Department of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Catherine Frenette
- Scripps Center for Organ Transplantation, Scripps Green Hospital, La Jolla, California, USA
| | - Anjana A Pillai
- Center for Liver Diseases, University of Chicago Medicine, Chicago, Illinois, USA
| | - Reena Salgia
- Department of Gastroenterology/Hepatology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Anil Seetharam
- Transplant Hepatology, University of Arizona College of Medicine, Phoenix, Arizona, USA
| | - Pratima Sharma
- Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Courtney Sherman
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| | - Georgios Tsoulfas
- Department of Surgery, Aristotle University School of Medicine, Thessaloniki, Greece
| | - Francis Y Yao
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, San Francisco, California, USA
| |
Collapse
|
|
33
|
Nomogram to Assist in Surgical Plan for Hepatocellular Carcinoma: a Prediction Model for Microvascular Invasion. J Gastrointest Surg 2019; 23:2372-2382. [PMID: 30820799 DOI: 10.1007/s11605-019-04140-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2018] [Accepted: 01/23/2019] [Indexed: 01/31/2023]
Abstract
BACKGROUND Microvascular invasion (MVI) relates to poor survival in hepatocellular carcinoma (HCC) patients. In this study, we aim at developing a nomogram for MVI prediction and potential assistance in surgical planning. METHODS A total of 357 patients were assigned to training (n = 257) and validation (n = 100) cohort. Univariate and multivariate analyses were used to reveal preoperative predictors for MVI. A nomogram incorporating independent predictors was constructed and validated. Disease-free survival was compared between patients, and the potential of the predicted MVI in making surgical procedure was also explored. RESULTS Pathological examination confirmed MVI in 140 (39.2%) patients. Imaging features including larger tumor, intra-tumoral artery, tumor type, and higher serum AFP independently correlated with MVI. The nomogram showed desirable performance with an AUROC of 0.803 (95% CI, 0.746-0.860) and 0.814 (95% CI, 0.720-0.908) in the training and validation cohorts, respectively. Good calibration were also revealed by calibration curve in both cohorts. The decision curve analysis indicated that the prediction nomogram was of promising usefulness in clinical work. In addition, survival analysis revealed that patients with positive-predicted MVI suffered a higher risk of early recurrence (P < 0.01). There was no difference in disease-free survival between anatomic or non-anatomic resection in large HCC or small HCC without nomogram-predicted MVI. However, anatomic resection improved disease-free survival in small HCC with nomogram-predicted MVI. CONCLUSIONS The nomogram obtained desirable results in predicting MVI. Patients with predicted MVI were associated with early recurrence and anatomic resection was recommended for small HCC patients with predicted MVI.
Collapse
|
|
34
|
Abstract
To discuss the prognostic correlation between hepatitis B virus DNA (HBV DNA) level and HBV-related hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI).Data from HCC patients undergoing hepatectomy with pathological evidence of MVI were retrospectively collected and 1:1 propensity scoring matching (PSM) analysis was performed. According to the HBV DNA levels before and after surgery, the disease-free survival (DFS) and overall survival (OS) were evaluated using the Kaplan-Meier method, and the Cox proportional hazards regression was used to analyze the risk factors associated with the postoperative prognosis. After 1:1 PSM, 139 pairs of patients were enrolled in the high preoperative HBV DNA level group (H group) and low preoperative HBV DNA level group (L group), and after operation, patients with high preoperative HBV DNA levels were divided into the persistently high HBV DNA level group (P group) and the decreased HBV DNA level group (D group).According to the multivariate analysis, the HBV DNA level of 2000 IU/ml or greater before operation was significantly associated with the DFS (hazard ratio, 1.322; 95%CI, 1.016-1.721) and OS (hazard ratio, 1.390; 95%CI, 1.023-1.888). A persistent HBV DNA level of 2,000 IU/ml or greater after operation was also the independent risk factor of DFS (hazard ratio, 1.421; 95%CI, 1.018-1.984) and OS (hazard ratio, 1.545; 95%CI, 1.076-2.219).For the HBV-related HCC patients with MVI, preoperative high HBV DNA copies are prognostication of poorer prognosis, and effective antivirus treatment would significantly improve the patients' prognosis.
Collapse
Affiliation(s)
- Lian Li
- Department of Liver Surgery, West China Hospital, Sichuan University, Chengdu
| | - Bo Li
- Department of Liver Surgery, West China Hospital, Sichuan University, Chengdu
| | - Ming Zhang
- Department of Liver Surgery, West China Hospital, Sichuan University, Chengdu
- Department of General Surgery, Mianzhu Hospital of West China hospital, Sichuan University, Mianzhu, Sichuan Province, China
| |
Collapse
|
|
35
|
Segmental Distribution of Hepatocellular Carcinoma Correlates with Microvascular Invasion in Liver Explants Undergoing Transplantation. J Cancer Epidemiol 2019; 2019:8534372. [PMID: 31186641 PMCID: PMC6521314 DOI: 10.1155/2019/8534372] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/12/2019] [Accepted: 04/15/2019] [Indexed: 12/13/2022] Open
Abstract
Introduction Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients is a poor prognostic factor after liver transplantation and/or resection. Any correlation between MVI and segmental location of HCC has yet to be studied. Our aim is to evaluate the segmental location of HCC and any correlation with the presence of MVI, portal vein thrombosis (PVT) in explanted livers, and the recurrence of HCC after transplantation. Another objective of the study is to assess the treatment history (ablation or transarterial chemoembolization (TACE)) and size of the tumor with respect to the risk of MVI. Methods A single center, retrospective chart review, including 98 HCC patients, aged 18 years and older who had liver transplantation in our institute between 2012 and 2017. We reviewed the radiological images of the HCC tumors, the pathological findings of the explanted livers, and the follow-up imaging after transplantation. Results 98 patients with the diagnosis of HCC underwent liver transplantation between 2012 and 2017. The mean age of the cohort was 63 ± 8.2. Males represented 75% and Caucasian race represented 75% of the cohort. The most common etiology of cirrhosis was chronic hepatitis C virus infection followed by alcohol abuse and nonalcoholic steatohepatitis (NASH) with percentages of 50%, 23%, and 10%, respectively. Microvascular invasion was found in 16% of the patients while PVT and the recurrence of HCC were found in 17% and 6 % of the cohort, respectively. MVI was found in 10 single HCC and 6 multifocal HCC. Right lobe HCC had more MVI when compared to the left and multilobar HCC, with percentages of 11%, 2%, and 3%, respectively. Localization of HCC in segment 8 was associated with the highest percentage of MVI when compared to all other segments. The risk of MVI in segment 8 HCC was 3.5 times higher than the risk from the other segments (p=0.002) while no vascular invasion was found in segments 1, 3, and 5. The risk of vascular invasion in untreated HCC is 3 times the risk in treated HCC (P=0.03). Conclusion Our data indicate that the risk of microvascular invasion is highest in tumors localized to segment 8. The size and number of HCC tumors were not associated with an increased risk of microvascular invasion.
Collapse
|
|
36
|
Ma KW, She WH, Chan ACY, Cheung TT, Fung JYY, Dai WC, Lo CM, Chok KSH. Validated model for prediction of recurrent hepatocellular carcinoma after liver transplantation in Asian population. World J Gastrointest Oncol 2019; 11:322-334. [PMID: 31040897 PMCID: PMC6475674 DOI: 10.4251/wjgo.v11.i4.322] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 01/03/2019] [Accepted: 01/08/2019] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Liver transplantation (LT) is regarded as the best treatment for both primary and recurrent hepatocellular carcinoma (HCC). Post-transplant HCC recurrence rate is relatively low but significant, ranging from 10%-30% according to different series. When recurrence happens, it is usually extrahepatic and associated with poor prognosis. A predictive model that allows patient stratification according to recurrence risk can help to individualize post-transplant surveillance protocol and guidance of the use of anti-tumor immunosuppressive agents. AIM To develop a scoring system to predict HCC recurrence after LT in an Asian population. METHODS Consecutive patients having LT for HCC from 1995 to 2016 at our hospital were recruited. They were randomized into the training set and the validation set in a 60:40 ratio. Multivariable Cox regression model was used to identity factors associated with HCC recurrence. A risk score was assigned to each factor according to the odds ratio. Accuracy of the score was assessed by the area under the receiver operating characteristic curve. RESULTS In total, 330 patients were eligible for analysis (183 in training and 147 in validation). Recurrent HCC developed in 14.2% of them. The median follow-up duration was 65.6 mo. The 5-year disease-free and overall survival rates were 78% and 80%, respectively. On multivariate analysis, alpha-fetoprotein > 400 ng/mL [P = 0.012, hazard ratio (HR) 2.92], sum of maximum tumor size and number (P = 0.013, HR 1.15), and salvage LT (P = 0.033, HR 2.08) were found to be independent factors for disease-free survival. A risk score was calculated for each patient with good discriminatory power (c-stat 0.748 and 0.85, respectively, in the training and validation sets). With the derived scores, patients were classified into low- (0-9), moderate- (> 9-14), and high-risk groups (> 14), and the risk of HCC recurrence in the training and validation sets was 10%, 20%, 54% (c-stat 0.67) and 4%, 22%, 62% (c-stat 0.811), accordingly. The risk stratification model was validated with chi-squared goodness-of-fit test (P = 0.425). CONCLUSION A validated predictive model featuring alpha-fetoprotein, salvage LT, and the sum of largest tumor diameter and total number of tumor nodule provides simple and reliable guidance for individualizing postoperative surveillance strategy.
Collapse
Affiliation(s)
- Ka Wing Ma
- Department of Surgery, the University of Hong Kong, Hong Kong, China
| | - Wong Hoi She
- Department of Surgery, the University of Hong Kong, Hong Kong, China
| | - Albert Chi Yan Chan
- Department of Surgery and State Key Laboratory for Liver Research, the University of Hong Kong, 102 Pokfulam Road, Hong Kong, China
| | - Tan To Cheung
- Department of Surgery and State Key Laboratory for Liver Research, the University of Hong Kong, 102 Pokfulam Road, Hong Kong, China
| | - James Yan Yue Fung
- Department of Medicine and State Key Laboratory for Liver Research, The University of Hong Kong, Hong Kong, China
| | - Wing Chiu Dai
- Department of Surgery, the University of Hong Kong, Hong Kong, China
| | - Chung Mau Lo
- Department of Surgery and State Key Laboratory for Liver Research, the University of Hong Kong, 102 Pokfulam Road, Hong Kong, China
| | - Kenneth Siu Ho Chok
- Department of Surgery and State Key Laboratory for Liver Research, the University of Hong Kong, 102 Pokfulam Road, Hong Kong, China
| |
Collapse
|
|
37
|
Ke RS, Cai QC, Chen YT, Lv LZ, Jiang Y. Diagnosis and treatment of microvascular invasion in hepatocellular carcinoma. Eur Surg 2019. [DOI: 10.1007/s10353-019-0573-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
|
|
38
|
Ma X, Wei J, Gu D, Zhu Y, Feng B, Liang M, Wang S, Zhao X, Tian J. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT. Eur Radiol 2019; 29:3595-3605. [PMID: 30770969 DOI: 10.1007/s00330-018-5985-y] [Citation(s) in RCA: 157] [Impact Index Per Article: 26.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 12/05/2018] [Accepted: 12/18/2018] [Indexed: 02/07/2023]
Abstract
OBJECTIVES To develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). METHODS The study included 157 patients with histologically confirmed HCC with or without MVI, and 110 patients were allocated to the training dataset and 47 to the validation dataset. Baseline clinical factor (CF) data were collected from our medical records, and radiomics features were extracted from the artery phase (AP), portal venous phase (PVP) and delay phase (DP) of preoperatively acquired CT in all patients. Radiomics analysis included tumour segmentation, feature extraction, model construction and model evaluation. A final nomogram for predicting MVI of HCC was established. Nomogram performance was assessed via both calibration and discrimination statistics. RESULTS Five AP features, seven PVP features and nine DP features were effective for MVI prediction in HCC radiomics signatures. PVP radiomics signatures exhibited better performance than AP and DP radiomics signatures in the validation datasets, with the AUC 0.793. In the clinical model, age, maximum tumour diameter, alpha-fetoprotein and hepatitis B antigen were effective predictors. The final nomogram integrated the PVP radiomics signature and four CFs. Good calibration was achieved for the nomogram in both the training and validated datasets, with respective C-indexes of 0.827 and 0.820. Decision curve analysis suggested that the proposed nomogram was clinically useful, with a corresponding net benefit of 0.357. CONCLUSIONS The above-described radiomics nomogram can preoperatively predict MVI in patients with HCC and may constitute a usefully clinical tool to guide subsequent personalised treatment. KEY POINTS • No previously reported study has utilised radiomics nomograms to preoperatively predict the MVI of HCC using 3D contrast-enhanced CT imaging. • The combined radiomics clinical factor (CF) nomogram for predicting MVI achieved superior performance than either the radiomics signature or the CF nomogram alone. • Nomograms combing PVP radiomics and CF may be useful as an imaging marker for predicting MVI of HCC preoperatively and could guide personalised treatment.
Collapse
Affiliation(s)
- Xiaohong Ma
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China
| | - Jingwei Wei
- Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Dongsheng Gu
- Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Yongjian Zhu
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China
| | - Bing Feng
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China
| | - Meng Liang
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China
| | - Shuang Wang
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, People's Republic of China.
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People's Republic of China.
| |
Collapse
|
|
39
|
Rastogi A. Changing role of histopathology in the diagnosis and management of hepatocellular carcinoma. World J Gastroenterol 2018; 24:4000-4013. [PMID: 30254404 PMCID: PMC6148422 DOI: 10.3748/wjg.v24.i35.4000] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 07/23/2018] [Accepted: 08/01/2018] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most common and fatal cancer in the world. HCC frequently presents with advanced disease, has a high recurrence rate and limited treatment options, which leads to very poor prognosis. This warrants urgent improvement in the diagnosis and treatment. Liver biopsy plays very important role in the diagnosis and prognosis of HCC, but with technical advancements and progression in the field of imaging, clinical guidelines have restricted the role of biopsy to very limited situations. Biopsy also has its own problems of needle tract seeding of tumor, small risk of complications, technical and sampling errors along with interpretative errors. Despite this, tissue analysis is often required because imaging is not always specific, limited expertise and lack of advanced imaging in many centers and limitations of imaging in the diagnosis of small, mixed and other variant forms of HCC. In addition, biopsy confirmation is often required for clinical trials of new drugs and targeted therapies. Tissue biomarkers along with certain morphological features, phenotypes and immune-phenotypes that serve as important prognostic and outcome predictors and as decisive factors for therapy decisions, add to the continuing role of histopathology. Advancements in cancer biology and development of molecular classification of HCC with clinic pathological correlation, lead to discovery of HCC phenotypic surrogates of prognostic and therapeutically significant molecular signatures. Thus tissue characteristics and morphology based correlates of molecular subtypes provide invaluable information for management and prognosis. This review thus focuses on the importance of histopathology and resurgence of role of biopsy in the diagnosis, management and prognostication of HCC.
Collapse
Affiliation(s)
- Archana Rastogi
- Department of Pathology, Institute of Liver & Biliary Sciences, New Delhi 110070, India
| |
Collapse
|
|
40
|
Jiang HY, Chen J, Xia CC, Cao LK, Duan T, Song B. Noninvasive imaging of hepatocellular carcinoma: From diagnosis to prognosis. World J Gastroenterol 2018; 24:2348-2362. [PMID: 29904242 PMCID: PMC6000290 DOI: 10.3748/wjg.v24.i22.2348] [Citation(s) in RCA: 105] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 04/18/2018] [Accepted: 04/23/2018] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at molecular, cellular, and histologic levels with key alterations that can be revealed by noninvasive imaging modalities. Therefore, imaging techniques play pivotal roles in the detection, characterization, staging, surveillance, and prognosis evaluation of HCC. Currently, ultrasound is the first-line imaging modality for screening and surveillance purposes. While based on conclusive enhancement patterns comprising arterial phase hyperenhancement and portal venous and/or delayed phase wash-out, contrast enhanced dynamic computed tomography and magnetic resonance imaging (MRI) are the diagnostic tools for HCC without requirements for histopathologic confirmation. Functional MRI techniques, including diffusion-weighted imaging, MRI with hepatobiliary contrast agents, perfusion imaging, and magnetic resonance elastography, show promise in providing further important information regarding tumor biological behaviors. In addition, evaluation of tumor imaging characteristics, including nodule size, margin, number, vascular invasion, and growth patterns, allows preoperative prediction of tumor microvascular invasion and patient prognosis. Therefore, the aim of this article is to review the current state-of-the-art and recent advances in the comprehensive noninvasive imaging evaluation of HCC. We also provide the basic key concepts of HCC development and an overview of the current practice guidelines.
Collapse
Affiliation(s)
- Han-Yu Jiang
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Jie Chen
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Chun-Chao Xia
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Li-Kun Cao
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Ting Duan
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Bin Song
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| |
Collapse
|
|
41
|
Zhao W, Liu W, Liu H, Yi X, Hou J, Pei Y, Liu H, Feng D, Liu L, Li W. Preoperative prediction of microvascular invasion of hepatocellular carcinoma with IVIM diffusion-weighted MR imaging and Gd-EOB-DTPA-enhanced MR imaging. PLoS One 2018; 13:e0197488. [PMID: 29771954 PMCID: PMC5957402 DOI: 10.1371/journal.pone.0197488] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 05/03/2018] [Indexed: 12/21/2022] Open
Abstract
Microvascular invasion (MVI) is regarded as one of the independent risk factors for recurrence and poor prognosis of hepatocellular carcinoma (HCC). The presence of MVI in HCCs was evaluated on the basis of pathological reports of surgical specimens and was defined as tumor within a vascular space lined by endothelium that was visible only on microscopy. The aim of the study was to investigate the usefulness of intravoxel incoherent motion (IVIM) diffusion weighted (DW) magnetic resonance (MR) imaging in predicting MVI of HCC. Preoperative IVIM DW imaging and Gd-EOB-DTPA-enhanced MRI (DCE-MRI) of 51 patients were analyzed. Standard apparent diffusion coefficient (ADC), D (the true diffusion coefficient), D* (the pseudodiffusion coefficient) and f (the perfusion fraction), relative enhancement (RE) and radiological features were evaluated and analyzed. Univariate analysis revealed that HCCs with MVI had a higher portion of an irregular tumor shape than HCCs without MVI (p = 0.009), the Standard ADC, D value were significantly lower in HCCs with MVI (p = 0.022, p = 0.007, respectively). Multivariate analysis revealed that an irregular shape (p = 0.012) and D value ≤ 1.16×10-3mm2/sec (p = 0.048) were independent predictors for MVI. Combining the two factors of an irregular shape and D value, a sensitivity of 94.4% and specificity of 63.6% for predicting MVI was obtained. In conclusion, we found that an irregular shape and D value ≤ 1.16×10-3mm2/sec may suggest the presence of MVI in HCCs.
Collapse
Affiliation(s)
- Wei Zhao
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, P.R. China
| | - Wenguang Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Huaping Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Xiaoping Yi
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Jiale Hou
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Yigang Pei
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Hui Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Deyun Feng
- Department of Pathology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Liyu Liu
- Center for Molecular Medicine, Xiangya Hospital of Centre-South University, Changsha, Hunan, P.R. China
| | - Wenzheng Li
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
- * E-mail:
| |
Collapse
|
|
42
|
Mehta N, Dodge JL, Roberts JP, Yao FY. Validation of the prognostic power of the RETREAT score for hepatocellular carcinoma recurrence using the UNOS database. Am J Transplant 2018; 18:1206-1213. [PMID: 29068145 PMCID: PMC6445634 DOI: 10.1111/ajt.14549] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 09/12/2017] [Accepted: 10/16/2017] [Indexed: 02/06/2023]
Abstract
Researchers in a recent multicenter study developed and validated a novel prognostic index, Risk Estimation of Tumor Recurrence After Transplant (RETREAT), which incorporates α-fetoprotein (AFP) at liver transplantation (LT), microvascular invasion, and the sum of the largest viable tumor and number of tumors on explant. We now aim to evaluate RETREAT in the United Network for Organ Sharing (UNOS) database in patients with hepatocellular carcinoma (HCC) who meet Milan criteria by imaging and underwent LT between 2012 and -2014. On explantation (n = 3276), 13% had microvascular invasion, 30% had no viable tumor, and 15% exceeded Milan criteria. Post-LT survival at 3 years decreased with increasing RETREAT score: 91% for a score of 0, 80% for a score of 3, and 58% for a score ≥5 (P < .001). Post-LT HCC recurrence probability within 3 years increased from 1.6% with RETREAT score of 0% to 29% for a score ≥5 (P < .001). Increasing RETREAT score was also associated with a shorter time to HCC recurrence. RETREAT was superior to Milan criteria (explant) in predicting HCC recurrence by the net reclassification index (P < .001). This study validates the prognostic power of RETREAT, which may help standardize post-LT surveillance, provide a framework for tumor staging and risk stratification, and select candidates for adjuvant therapies.
Collapse
Affiliation(s)
- Neil Mehta
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA, USA
| | - Jennifer L. Dodge
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco, CA, USA
| | - John P. Roberts
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco, CA, USA
| | - Francis Y. Yao
- Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA, USA,Division of Transplant Surgery, Department of Surgery, University of California, San Francisco, CA, USA
| |
Collapse
|
|
43
|
Poté N, Cauchy F, Albuquerque M, Cros J, Soubrane O, Bedossa P, Paradis V. Contribution of virtual biopsy to the screening of microvascular invasion in hepatocellular carcinoma: A pilot study. Liver Int 2018; 38:687-694. [PMID: 28872754 DOI: 10.1111/liv.13585] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 08/31/2017] [Indexed: 12/20/2022]
Abstract
BACKGROUND & AIMS Microvascular invasion (mVI) is a major prognostic factor in hepatocellular carcinoma (HCC) that cannot be detected before surgery. Predictive biomarkers of mVI are thus urgently needed. We have developed an original approach of virtual biopsy to assess the performance of an immunohistochemical panel comprising three biomarkers of mVI (H4K16ac, H4K20me2, PIVKA-II) for the prediction of mVI in HCC core needle biopsies (CNB). METHODS A test set of HCC surgical specimens (n = 64) and an independent validation set of HCC CNB (n = 42) were retrospectively constituted. Immunostainings were first quantified in the test set on the whole tissue section, to determine optimal cut-off values for each marker. From the digitised image of the whole section, three virtual biopsies were provided. Immunostainings and accuracy of the panel for the prediction of mVI were further assessed in virtual biopsies and in the validation set of CNB. RESULTS In virtual biopsies, PIVKA-II/H4K16ac had the best performance for prediction of mVI, with sensitivity, specificity, predictive positive value (PPV), and predictive negative value (PNV) of 30%, 97%, 91%, 56%, respectively. In CNB, PIVKA-II/H4K20me2 showed the best accuracy for prediction of mVI, with sensitivity, specificity, PPV, and NPV of 43%, 95%, 90%, and 62%, respectively. The two panels were independent predictive factors of mVI (PIVKA-II/H4K16ac, P = .037; PIVKA-II/H4K20me2, P = .026). CONCLUSION This study shows that a panel of two markers is able to predict mVI in HCC CNB, and pave the way for the future development of prognostic biomarkers in HCC that could guide the therapeutic strategy.
Collapse
Affiliation(s)
- Nicolas Poté
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France.,Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France
| | - François Cauchy
- Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France.,Department of Liver Transplantation and Hepatobiliary Surgery, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France
| | - Miguel Albuquerque
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France
| | - Jérôme Cros
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France.,Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France
| | - Olivier Soubrane
- Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France.,Department of Liver Transplantation and Hepatobiliary Surgery, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France
| | - Pierre Bedossa
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France.,Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France
| | - Valérie Paradis
- Department of Pathology, Beaujon Hospital, Assistance Publique-Hôpitaux de Paris, Clichy, France.,Centre de Recherche sur l'inflammation, UMR 1149, INSERM-Paris Diderot University, Paris, France
| |
Collapse
|
|
44
|
Wang X, Ma C, Zong Z, Xiao Y, Li N, Guo C, Zhang L, Shi Y. A20 inhibits the motility of HCC cells induced by TNF-α. Oncotarget 2018; 7:14742-54. [PMID: 26909601 PMCID: PMC4924748 DOI: 10.18632/oncotarget.7521] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Accepted: 01/26/2016] [Indexed: 02/06/2023] Open
Abstract
Metastasis of hepatocellular carcinoma (HCC) can be facilitated by TNF-α, a prototypical inflammatory cytokine in the HCC microenvironment. A20 is a negative regulator of NF-κB signaling pathway. In the present study we ask whether A20 plays a role in HCC metastasis. We found that A20 expression was downregulated in the invasive cells of microvascular invasions (MVI) compared with the noninvasive cells in 89 tissue samples from patients with HCC by immunochemistry methods. Overexpression of A20 in HCC cell lines inhibited their motility induced by TNF-α. Furthermore, the overexpression of A20 inhibited epithelial-mesenchymal transition (EMT), FAK activation and RAC1 activity. By contrast, knockdown of A20 in one HCC cell line results in the converse. In addition, the overexpression of A20 restrained the formation of MVI in HCC xenograft in nude mice treated with TNF-α. All the results suggested that A20 functioned as a negative regulator in motility of HCC cells induced by TNF-α.
Collapse
Affiliation(s)
- Xianteng Wang
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| | - Chao Ma
- Department of Pathology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhaoyun Zong
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| | - Ying Xiao
- Laboratory of Cellular and Molecular Medicine, Shandong University School of Medicine, Jinan, China
| | - Na Li
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| | - Chun Guo
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| | - Lining Zhang
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| | - Yongyu Shi
- Department of Immunology, Shandong University School of Medicine, Jinan, China
| |
Collapse
|
|
45
|
Ye JZ, Chen JZ, Li ZH, Bai T, Chen J, Zhu SL, Li LQ, Wu FX. Efficacy of postoperative adjuvant transcatheter arterial chemoembolization in hepatocellular carcinoma patients with microvascular invasion. World J Gastroenterol 2017; 23:7415-7424. [PMID: 29151695 PMCID: PMC5685847 DOI: 10.3748/wjg.v23.i41.7415] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 09/09/2017] [Accepted: 09/19/2017] [Indexed: 02/06/2023] Open
Abstract
AIM To investigate the efficacy and safety of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in preventing tumor recurrence and improving survival in Barcelona Clinic Liver Cancer (BCLC) early (A) and intermediate (B) stage hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI).
METHODS A total of 519 BCLC A or B HCC patients treated by liver resection alone or followed by PA-TACE between January 2012 and December 2015 were studied retrospectively. Univariate and multivariate analyses were performed to investigate the risk factors for recurrence-free survival (RFS) and overall survival (OS). Multiple logistic regression was used to identify the clinicopathological characteristics associated with MVI. The rates of RFS and OS were compared among patients with or without MVI treated with liver resection alone or followed by PA-TACE.
RESULTS Univariate and multivariate analyses demonstrated that serum AFP level > 400 ng/mL, tumor size > 5 cm, tumor capsule invasion, MVI, and major hepatectomy were risk factors for poor OS. Tumor capsule invasion, MVI, tumor size > 5 cm, HBV-DNA copies > 1 x 104 IU/mL, and multinodularity were risk factors for poor RFS. Multiple logistic regression identified serum AFP level > 400 ng/mL, tumor size > 5 cm, and tumor capsule invasion as independent predictors of MVI. Both OS and DFS were significantly improved in patients with MVI who received PA-TACE as compared to those who underwent liver resection alone. Patients without MVI did not show a significant difference in OS and RFS between those treated by liver resection alone or followed by PA-TACE.
CONCLUSION PA-TACE is a safe adjuvant intervention and can efficiently prevent tumor recurrence and improve the survival of BCLC early- and intermediate-stage HCC patients with MVI.
Collapse
MESH Headings
- Antineoplastic Combined Chemotherapy Protocols/administration & dosage
- Carcinoma, Hepatocellular/mortality
- Carcinoma, Hepatocellular/pathology
- Carcinoma, Hepatocellular/therapy
- Chemoembolization, Therapeutic/adverse effects
- Chemoembolization, Therapeutic/methods
- Chemotherapy, Adjuvant/adverse effects
- Chemotherapy, Adjuvant/methods
- Disease-Free Survival
- Female
- Follow-Up Studies
- Hepatectomy
- Humans
- Incidence
- Liver Neoplasms/mortality
- Liver Neoplasms/pathology
- Liver Neoplasms/therapy
- Male
- Microvessels/pathology
- Middle Aged
- Neoplasm Invasiveness/pathology
- Neoplasm Recurrence, Local/epidemiology
- Neoplasm Recurrence, Local/pathology
- Neoplasm Recurrence, Local/prevention & control
- Neoplasm Staging
- Postoperative Complications/epidemiology
- Postoperative Complications/etiology
- Prognosis
- Retrospective Studies
- Treatment Outcome
Collapse
Affiliation(s)
- Jia-Zhou Ye
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jun-Ze Chen
- Department of General Surgery, The Ninth Affiliated Hospital of Guangxi Medical University, Beihai 536000, Guangxi Zhuang Autonomous Region, China
| | - Zi-Hui Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Tao Bai
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jie Chen
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Shao-Liang Zhu
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Le-Qun Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Fei-Xiang Wu
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| |
Collapse
|
|
46
|
Wait Time of Less Than 6 and Greater Than 18 Months Predicts Hepatocellular Carcinoma Recurrence After Liver Transplantation: Proposing a Wait Time "Sweet Spot". Transplantation 2017; 101:2071-2078. [PMID: 28353492 DOI: 10.1097/tp.0000000000001752] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND It has been postulated that short wait time before liver transplant (LT) for hepatocellular carcinoma (HCC) results in the inclusion of tumors with aggressive biology, but prolonged wait time could result in a shift to more aggressive tumor behavior. We therefore test the hypothesis that a wait time "sweet spot" exists with a lower risk for HCC recurrence compared with the other 2 extremes. METHODS This multicenter study included 911 patients from 3 LT centers with short, medium, and long wait times (median of 4, 7, and 13 months, respectively) who received Model for End Stage Liver Disease exception listing for HCC from 2002 to 2012. RESULTS Wait time, defined as time from initial HCC diagnosis to LT, was less than 6 months in 32.4%, 6 to 18 months in 53.7%, and greater than 18 months in 13.9%. Waitlist dropout was observed in 18.4% at a median of 11.3 months. Probability of HCC recurrence at 1 and 5 years were 6.4% and 15.5% with wait time of less than 6 or greater than 18 months (n = 343) versus 4.5% and 9.8% with wait time of 6 to 18 months (n = 397), respectively (P = 0.049). When only pre-LT factors were considered, wait time of less than 6 or greater than 18 months (HR, 1.6; P = 0.043) and AFP greater than 400 at HCC diagnosis (HR, 3.0; P < 0.001) predicted HCC recurrence in multivariable analysis. CONCLUSIONS This large multicenter study provides evidence of an association between very short (<6 months) or very long (>18 months) wait times and an increased risk for HCC recurrence post-LT. The so-called sweet spot of 6 to 18 months should be the target to minimize HCC recurrence.
Collapse
|
|
47
|
Zhao J, Li X, Zhang K, Yin X, Meng X, Han L, Zhang X. Prediction of microvascular invasion of hepatocellular carcinoma with preoperative diffusion-weighted imaging: A comparison of mean and minimum apparent diffusion coefficient values. Medicine (Baltimore) 2017; 96:e7754. [PMID: 28816952 PMCID: PMC5571689 DOI: 10.1097/md.0000000000007754] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The aim of the study was to investigate the value of preoperative diffusion-weighted imaging (DWI) in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC), using and comparing mean and minimum apparent diffusion coefficient (ADC) values.Preoperative MR images of 318 patients with HCC confirmed by surgical pathology were retrospectively analyzed. All patients underwent preoperative DWI on a 1.5 Tesla MRI scanner. The mean and minimum ADC values of the tumors were measured. Interobserver agreements were assessed by the intraclass correlation coefficient (ICC). The ADC values were compared in HCCs between with and without MVI. ROC curves of ADC values were obtained and then compared in distinguishing HCCs with MVI from those without MVI.There were 211 HCCs with MVI and 107 HCCs without MVI. ICC for the measurements of the mean and minimum ADC values between both observers was 0.88 (95% CI 0.85 - 0.90) and 0.88 (95% CI 0.85 - 0.90), respectively. The mean and minimum ADC values of HCCs with MVI were lower than those of HCCs without MVI (P = .00, .00, respectively). With a cut-off value of 0.98 × 10 mm/s, the minimum ADC (MinADC) showed a sensitivity of 62.56% and a specificity of 65.42% in predicting MVI, whereas the mean ADC provided a sensitivity of 79.15% and a specificity of 50.47% with a cut-off value of 1.19 × 10 mm/s. No significant difference existed between MinADC and mean ADC for their diagnostic performances in the prediction of MVI (P = .48).DWI could preoperatively provide quantitative parameters for predicting MVI of HCC.
Collapse
Affiliation(s)
- Jinkun Zhao
- Department of Radiology, The Second Hospital of Tianjin Medical University
| | - Xubin Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huan-hu-xi Road, Hexi District, Tianjin
| | - Kun Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huan-hu-xi Road, Hexi District, Tianjin
| | - Xiaoyu Yin
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huan-hu-xi Road, Hexi District, Tianjin
| | - Xiangfu Meng
- Department of Radiology, Linyi Traditional Chinese Medicine Hospital, Shandong, China
| | - Lizhu Han
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Huan-hu-xi Road, Hexi District, Tianjin
| | - Xuening Zhang
- Department of Radiology, The Second Hospital of Tianjin Medical University
| |
Collapse
|
|
48
|
Chen DH, Wu QW, Li XD, Wang SJ, Zhang ZM. SYPL1 overexpression predicts poor prognosis of hepatocellular carcinoma and associates with epithelial-mesenchymal transition. Oncol Rep 2017; 38:1533-1542. [DOI: 10.3892/or.2017.5843] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Accepted: 06/07/2017] [Indexed: 02/07/2023] Open
|
|
49
|
Abbate V, Marcantoni M, Giuliante F, Vecchio FM, Gatto I, Mele C, Saviano A, Arciuolo D, Gaetani E, Ferrari MC, Giarretta I, Ardito F, Riccardi L, Nicoletti A, Ponziani FR, Gasbarrini A, Pompili M, Pola R. HepPar1-Positive Circulating Microparticles Are Increased in Subjects with Hepatocellular Carcinoma and Predict Early Recurrence after Liver Resection. Int J Mol Sci 2017; 18:E1043. [PMID: 28498353 PMCID: PMC5454955 DOI: 10.3390/ijms18051043] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 04/14/2017] [Accepted: 05/01/2017] [Indexed: 12/19/2022] Open
Abstract
Circulating microparticles (MPs) are novel potential biomarkers in cancer patients. Their role in hepatocellular carcinoma (HCC) is under intensive investigation. In this study, we tested the hypothesis that MPs expressing the antigen HepPar1 are increased in the blood of subjects with HCC and may serve as markers of early recurrence after liver resection (LR). We studied 15 patients affected by HCC undergoing LR, and used flow cytometry to assess the number of circulating HepPar1+ MPs. Ten subjects without HCC (five with liver cirrhosis and five with healthy livers) were used as controls. After LR, HCC patients underwent a follow-up to check for early recurrence, which occurred in seven cases. The number of circulating HepPar1+ MPs was significantly higher in subjects affected by HCC, compared to individuals without cancer (p < 0.01). We also found that, among HCC patients, the number of circulating HepPar1+ MPs, measured before LR, was significantly higher in those who displayed early recurrence compared to those without recurrence (p = 0.02). Of note, other types of circulating MPs, such as those derived from endothelial cells (CD144+) or those produced by the activated endothelium (CD144+/CD62+), were not associated with HCC, nor could they predict HCC recurrence. HepPar1+ MPs deserve further investigation as novel biomarkers of disease and prognosis in HCC patients.
Collapse
Affiliation(s)
- Valeria Abbate
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Margherita Marcantoni
- Division of Vascular Medicine, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Felice Giuliante
- Hepatobiliary Surgery Unit, and Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Fabio M Vecchio
- Department of Pathology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Ilaria Gatto
- Division of Vascular Medicine, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Caterina Mele
- Hepatobiliary Surgery Unit, and Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Antonio Saviano
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Damiano Arciuolo
- Department of Pathology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Eleonora Gaetani
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Maria C Ferrari
- Division of Vascular Medicine, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Igor Giarretta
- Division of Vascular Medicine, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Francesco Ardito
- Hepatobiliary Surgery Unit, and Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Laura Riccardi
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Alberto Nicoletti
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Francesca R Ponziani
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Antonio Gasbarrini
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Maurizio Pompili
- Division of Internal Medicine and Gastroenterology, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| | - Roberto Pola
- Division of Vascular Medicine, Catholic University School of Medicine, A. Gemelli University Hospital, Rome 00168, Italy.
| |
Collapse
|
|
50
|
Mehta N, Heimbach J, Harnois DM, Sapisochin G, Dodge JL, Lee D, Burns JM, Sanchez W, Greig PD, Grant DR, Roberts JP, Yao FY. Validation of a Risk Estimation of Tumor Recurrence After Transplant (RETREAT) Score for Hepatocellular Carcinoma Recurrence After Liver Transplant. JAMA Oncol 2017; 3:493-500. [PMID: 27838698 DOI: 10.1001/jamaoncol.2016.5116] [Citation(s) in RCA: 278] [Impact Index Per Article: 34.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance Several factors are associated with increased hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT), but no reliable risk score has been established to determine the individual risk for HCC recurrence. Objective We aimed to develop and validate a Risk Estimation of Tumor Recurrence After Transplant (RETREAT) score for patients with HCC meeting Milan criteria by imaging. Design, Setting, and Participants Predictors of recurrence were tested in a development cohort of 721 patients who underwent LT between 2002 and 2012 at 3 academic transplant centers (University of California-San Francisco; Mayo Clinic, Rochester; and Mayo Clinic, Jacksonville) to create the RETREAT score. This was subsequently validated in a cohort of 341 patients also meeting Milan criteria by imaging who underwent LT at the University of Toronto transplant center using the C concordance statistic and net reclassification index. Main Outcomes and Measures Characteristics associated with post-LT HCC recurrence. Results A total of 1061 patients participated in the study; 77.8% (825) were men, and the median (IQR) age was 58.2 (53.3-63.9) years in the development cohort and 56.4 (51.7-61.0) years in the validation cohort (P < .001). In the development cohort of 721 patients (542 men), median α-fetoprotein (AFP) level at the time of LT was 8.3 ng/mL; 9.4% had microvascular invasion (n = 68), and 22.1% were beyond Milan criteria on explant (n = 159) owing to understaging by pretransplantation imaging. Cumulative probabilities of HCC recurrence at 1 and 5 years were 5.7% and 12.8%, respectively. On multivariable Cox proportional hazards regression, 3 variables were independently associated with HCC recurrence: microvascular invasion, AFP at time of LT, and the sum of the largest viable tumor diameter and number of viable tumors on explant. The RETREAT score was created using these 3 variables, with scores ranging from 0 to 5 or higher that were highly predictive of HCC recurrence (C statistic, 0.77). RETREAT was able to stratify 5-year post-LT recurrence risk ranging from less than 3% with a score of 0 to greater than 75% with a score of 5 or higher. The validation cohort (n = 340; 283 men) had significantly higher microvascular invasion (23.8% [n = 81], P < .001), explant beyond Milan criteria (37.3% [n = 159], P < .001), and HCC recurrence at 5 years (17.9% [n = 159], P = .03). RETREAT showed good model discrimination (C statistic, 0.82; 95% CI, 0.77-0.86) and superior recurrence risk classification compared with explant Milan criteria (net reclassification index, 0.40; P = .001) in the validation cohort. Conclusions and Relevance We have developed and validated a simple and novel prognostic score that may improve post-LT HCC surveillance strategies and help identify patients who may benefit from future adjuvant therapies.
Collapse
Affiliation(s)
- Neil Mehta
- Division of Gastroenterology, Department of Medicine, University of California-San Francisco
| | - Julie Heimbach
- Division of Transplantation, Department of Surgery, Mayo Clinic, Rochester, Minnesota
| | - Denise M Harnois
- Department of Transplantation, Mayo Clinic, Jacksonville, Florida
| | - Gonzalo Sapisochin
- Multi-Organ Transplant Program, Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Jennifer L Dodge
- Division of Transplant Surgery, Department of Surgery, University of California-San Francisco
| | - David Lee
- Department of Transplantation, Mayo Clinic, Jacksonville, Florida
| | - Justin M Burns
- Department of Transplantation, Mayo Clinic, Jacksonville, Florida
| | - William Sanchez
- Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, Minnesota
| | - Paul D Greig
- Multi-Organ Transplant Program, Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - David R Grant
- Multi-Organ Transplant Program, Division of General Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - John P Roberts
- Division of Transplant Surgery, Department of Surgery, University of California-San Francisco
| | - Francis Y Yao
- Division of Gastroenterology, Department of Medicine, University of California-San Francisco5Division of Transplant Surgery, Department of Surgery, University of California-San Francisco
| |
Collapse
|