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Li LJ, Wu CQ, Ye FL, Xuan Z, Zhang XL, Li JP, Zhou J, Su ZZ. Histopathological diagnosis of microvascular invasion in hepatocellular carcinoma: Is it reliable? World J Gastroenterol 2025; 31:98928. [PMID: 39926219 PMCID: PMC11718611 DOI: 10.3748/wjg.v31.i5.98928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Revised: 11/05/2024] [Accepted: 12/12/2024] [Indexed: 12/30/2024] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a critical prognostic factor for postoperative hepatocellular carcinoma recurrence, but the reliability of its current pathological diagnosis remains uncertain. AIM To evaluate the accuracy of current 7-point sampling methods and propose an optimal pathological protocol using whole-mount slide imaging (WSI) for better MVI detection. METHODS We utilized 40 New Zealand white rabbits to establish VX2 liver tumor models. The entire tumor-containing liver lobe was subsequently obtained, following which five different sampling protocols (A-E) were employed to evaluate the detection rate, accuracy, quantity, and distribution of MVI, with the aim of identifying the optimal sampling method. RESULTS VX2 liver tumor models were successfully established in 37 rabbits, with an incidence of MVI of 81.1% (30/37). The detection rates [27% (10/37), 43% (16/37), 62% (23/37), 68% (25/37), and 93% (14/15)] and quantity (15, 36, 107, 125, and 395) of MVI increased significantly from protocols A to E. The distribution of MVI showed fewer MVIs farther away from the tumor, but the percentage of MVI detected quantity gradually increased from 6.7% to 48.3% in the distant nonneoplastic liver tissue from protocols A to E. Protocol C was identified as the optimal sampling method by comparing them in sequence. The sampling protocol of three consecutive interval WSIs at the tumor center (WSI3) was further screened to determine the optimal number of WSIs. Protocol A (7-point sampling method) exhibited only 46% accuracy and a high false-negative rate of 67%. Notably, the WSI3 protocol improved the accuracy to 78% and decreased the false-negative rate to 27%. CONCLUSION The current 7-point sampling method has a high false-negative rate in MVI detection. In contrast, the WSI3 protocol provides a practical and effective approach to improve MVI diagnostic accuracy, which is crucial for hepatocellular carcinoma diagnosis and treatment planning.
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Affiliation(s)
- Liu-Jun Li
- Department of Ultrasound, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan Province, China
- Department of Ultrasound, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
| | - Chao-Qun Wu
- Department of Ultrasound, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
| | - Fei-Le Ye
- Department of Ultrasound, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
| | - Zhou Xuan
- Department of Pathology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
| | - Xiao-Li Zhang
- Department of Pathology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan Province, China
| | - Jian-Ping Li
- Department of Pathology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan Province, China
| | - Jia Zhou
- Department of Ultrasound, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan Province, China
| | - Zhong-Zhen Su
- Department of Ultrasound, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging and Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, Guangdong Province, China
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Famularo S, Penzo C, Maino C, Milana F, Oliva R, Marescaux J, Diana M, Romano F, Giuliante F, Ardito F, Grazi GL, Donadon M, Torzilli G. Preoperative detection of hepatocellular carcinoma's microvascular invasion on CT-scan by machine learning and radiomics: A preliminary analysis. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2025; 51:108274. [PMID: 38538504 DOI: 10.1016/j.ejso.2024.108274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 02/20/2024] [Accepted: 03/16/2024] [Indexed: 08/22/2024]
Abstract
INTRODUCTION Microvascular invasion (MVI) is the main risk factor for overall mortality and recurrence after surgery for hepatocellular carcinoma (HCC).The aim was to train machine-learning models to predict MVI on preoperative CT scan. METHODS 3-phases CT scans were retrospectively collected among 4 Italian centers. DICOM files were manually segmented to detect the liver and the tumor(s). Radiomics features were extracted from the tumoral, peritumoral and healthy liver areas in each phase. Principal component analysis (PCA) was performed to reduce the dimensions of the dataset. Data were divided between training (70%) and test (30%) sets. Random-Forest (RF), fully connected MLP Artificial neural network (neuralnet) and extreme gradient boosting (XGB) models were fitted to predict MVI. Prediction accuracy was estimated in the test set. RESULTS Between 2008 and 2022, 218 preoperative CT scans were collected. At the histological specimen, 72(33.02%) patients had MVI. First and second order radiomics features were extracted, obtaining 672 variables. PCA selected 58 dimensions explaining >95% of the variance.In the test set, the XGB model obtained Accuracy = 68.7% (Sens: 38.1%, Spec: 83.7%, PPV: 53.3% and NPV: 73.4%). The neuralnet showed an Accuracy = 50% (Sens: 52.3%, Spec: 48.8%, PPV: 33.3%, NPV: 67.7%). RF was the best performer (Acc = 96.8%, 95%CI: 0.91-0.99, Sens: 95.2%, Spec: 97.6%, PPV: 95.2% and NPV: 97.6%). CONCLUSION Our model allowed a high prediction accuracy of the presence of MVI at the time of HCC diagnosis. This could lead to change the treatment allocation, the surgical extension and the follow-up strategy for those patients.
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Affiliation(s)
- Simone Famularo
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France.
| | - Camilla Penzo
- Pole d'Expertise de la Regulation Numérique (PEReN), Paris, France
| | - Cesare Maino
- Department of Radiology, San Gerardo Hospital, Monza, Italy
| | - Flavio Milana
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Riccardo Oliva
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France
| | - Jacques Marescaux
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France
| | - Michele Diana
- IRCAD, Research Institute Against Cancer of the Digestive System, 1 Place de l'Hôpital, Strasbourg, 67091, France; Department of General, Digestive and Endocrine Surgery, University Hospital of Strasbourg, France; ICube Lab, Photonics for Health, Strasbourg, France
| | - Fabrizio Romano
- School of Medicine and Surgery, University of Milan-Bicocca, Department of Surgery, San Gerardo Hospital, Monza, Italy
| | - Felice Giuliante
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy
| | - Francesco Ardito
- Hepatobiliary Surgery Unit, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Catholic University of the Sacred Heart, Rome, Italy
| | - Gian Luca Grazi
- Division of Hepatobiliarypancreatic Unit, IRCCS - Regina Elena National Cancer Institute, Rome, Italy
| | - Matteo Donadon
- Department of Health Sciences, Università del Piemonte Orientale, Novara, Italy; Department of General Surgery, University Maggiore Hospital Della Carità, Novara, Italy
| | - Guido Torzilli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; Department of Hepatobiliary and General Surgery, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
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Gu M, Zhang S, Zou W, Zhao X, Chen H, He R, Jia N, Song K, Liu W, Wang P. Advancing microvascular invasion diagnosis: a multi-center investigation of novel MRI-based models for precise detection and classification in early-stage small hepatocellular carcinoma (≤ 3 cm). Abdom Radiol (NY) 2024:10.1007/s00261-024-04463-w. [PMID: 39333413 DOI: 10.1007/s00261-024-04463-w] [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: 04/29/2024] [Revised: 06/11/2024] [Accepted: 06/15/2024] [Indexed: 09/29/2024]
Abstract
PURPOSE This study aimed to develop two preoperative magnetic resonance imaging (MRI) based models for detecting and classifying microvascular invasion (MVI) in early-stage small hepatocellular carcinoma (sHCC) patients. METHODS MVI is graded as M0 (no invasion), M1 (invasion of five or fewer vessels located within 1 cm of the tumor's peritumoral region), and M2 (invasion of more than five vessels or those located more than 1 cm from the tumor's surface). This study enrolled 395 early-stage sHCC (≤ 3 cm) patients from three centers who underwent preoperative gadopentetate-enhanced MRI. From the first two centers, 310 patients were randomly divided into training (n = 217) and validation (n = 93) cohorts in a 7:3 ratio to develop the first model for predicting MVI presence. Among these, 153 patients with identified MVI were further divided into training (n = 112) and validation (n = 41) cohorts, using the same ratio, to construct the second model for MVI classification. An independent test cohort of 85 patients from the third center to validate both models. Univariate and multivariate logistic regression analyses identified independent predictors of MVI and its classification in the training cohorts. Based on these predictors, two nomograms were developed and assessed for their discriminative ability, calibration, and clinical usefulness. Besides, considering the two models are supposed applied in a serial fashion in the real clinical setting, we evaluate the performance of the two models together on the test cohorts by applying them simultaneously. Kaplan-Meier survival curve analysis was employed to assess the correlation between predicted MVI status and early recurrence, similar to the association observed with actual MVI status and early recurrence. RESULTS The MVI detection nomogram, with platelet count (PLT), activated partial thromboplastin time (APTT), rim arterial phase hyperenhancement (Rim APHE) and arterial peritumoral enhancement, achieved area under the curve (AUC) of 0.827, 0.761 and 0.798 in the training, validation, and test cohorts, respectively. The MVI classification nomogram, integrating Total protein (TP), Shape, Arterial peritumoral enhancement and enhancement pattern, achieved AUC of 0.824, 0.772, and 0.807 across the three cohorts. When the two models were applied on the test cohorts in a serial fashion, they both demonstrated good performance, which means the two models had good clinical applicability. Calibration and decision curve analysis (DCA) results affirmed the model's reliability and clinical utility. Notably, early recurrence was more prevalent in the MVI grade 2 (M2) group compared to the MVI-absent and M1 groups, regardless of the actual or predicted MVI status. CONCLUSIONS The nomograms exhibited excellent predictive performance for detecting and classifying MVI in patients with early-stage sHCC, particularly identifying high-risk M2 patients preoperatively.
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Affiliation(s)
- Mengting Gu
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Sisi Zhang
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Shanghai, Naval Military Medical University, Shanghai, China
| | - Wenjie Zou
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Xingyu Zhao
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Huilin Chen
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - RuiLin He
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Ningyang Jia
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Shanghai, Naval Military Medical University, Shanghai, China
| | - Kairong Song
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Shanghai, Naval Military Medical University, Shanghai, China
| | - Wanmin Liu
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Peijun Wang
- Department of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
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Saleh GA, Denewar FA, Ali KM, Saleh M, Ali MA, Shehta A, Mansour M. Inter-observer reliability and predictive values of triphasic computed tomography for microvascular invasion in hepatocellular carcinoma. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2024; 55:176. [DOI: 10.1186/s43055-024-01354-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 08/28/2024] [Indexed: 02/11/2025] Open
Abstract
Abstract
Background
Hepatocellular carcinoma (HCC) is the most frequent primary liver tumor globally and a leading cause of mortality in cirrhotic patients. Our study aimed to estimate the diagnostic performance of triphasic CT and inter-observer reliability in the preoperative detection of microvascular invasion (MVI) in HCC. Two independent radiologists accomplished a retrospective analysis for 99 patients with HCC to assess the CT features for MVI in each lesion. Postoperative histopathology was considered the gold standard.
Results
Multivariate regression analysis revealed that incomplete or absent tumor capsules, presence of TTPV, and absence of hypodense halo were statistically significant independent predictors of MVI. There was excellent agreement among observers in evaluating peritumoral enhancement, identifying intratumoral arteries, hypodense halo, TTPV, and macrovascular invasion. Also, our results revealed moderate agreement in assessing the tumor margin and tumor capsule.
Conclusion
Triphasic CT features of MVI are reliable imaging predictors that may be helpful for standard preoperative interpretation of HCC.
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Yao WW, Zhang HW, Ma YP, Lee JM, Lee RT, Wang YL, Liu XL, Shen XP, Huang B, Lin F. Comparative analysis of the performance of hepatobiliary agents in depicting MRI features of microvascular infiltration in hepatocellular carcinoma. Abdom Radiol (NY) 2024; 49:2242-2249. [PMID: 38824474 DOI: 10.1007/s00261-024-04311-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/21/2024] [Accepted: 03/23/2024] [Indexed: 06/03/2024]
Abstract
OBJECTIVE To compare the ability to depict MRI features of hepatobiliary agents in microvascular infiltration (MVI) of hepatocellular carcinoma (HCC) during different stages of dynamic enhancement MRI. MATERIALS AND METHODS A retrospective study included 111 HCC lesions scanned with either Gd-EOB-DTPA or Gd-BOPTA. All cases underwent multiphase dynamic contrast-enhanced scanning before surgery, including arterial phase (AP), portal venous phase (PVP), transitional phase (TP), delayed phase (DP), and hepatobiliary phase (HBP). Two abdominal radiologists independently evaluated MRI features of MVI in HCC, such as peritumoral hyperenhancement, incomplete capsule, non-smooth tumor margins, and peritumoral hypointensity. Finally, the results were reviewed by the third senior abdominal radiologist. Chi-square (χ2) Inspection for comparison between groups. P < 0.05 is considered statistically significant. Receiver operating characteristic (ROC) curve was used to evaluate correlation with pathology, and the area under the curve (AUC) and 95% confidence interval (95% CI) were calculated. RESULTS Among the four MVI evaluation signs, Gd-BOPTA showed significant differences in displaying two signs in the HBP (P < 0.05:0.000, 0.000), while Gd-EOB-DTPA exhibited significant differences in displaying all four signs (P < 0.05:0.005, 0.006, 0.000, 0.002). The results of the evaluations of the two contrast agents in the DP phase with incomplete capsulation showed the highest correlation with pathology (AUC: 0.843, 0.761). By combining the four MRI features, Gd-BOPTA and Gd-EOB-DTPA have correlated significantly with pathology, and Gd-BOPTA is better (AUC: 0.9312vs0.8712). CONCLUSION The four features of hepatobiliary agent dynamic enhancement MRI demonstrate a good correlation with histopathological findings in the evaluation of MVI in HCC, and have certain clinical significance.
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Affiliation(s)
- Wei-Wei Yao
- Shantou University Medical College, No. 22, Xinling Road, Shantou, China
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, 1st Hai Yuan Road, Shenzhen, China
| | - Han-Wen Zhang
- Department of Radiology, Health Science Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, 3002 SunGangXi Road, Shenzhen, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510282, People's Republic of China
| | - Yu-Pei Ma
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, 1st Hai Yuan Road, Shenzhen, China
| | - Jia-Min Lee
- Department of Pathology, The University of Hong Kong-Shenzhen Hospital, 1st Hai Yuan Road, Shenzhen, China
| | - Rui-Ting Lee
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, 1st Hai Yuan Road, Shenzhen, China
| | - Yu-Li Wang
- Department of Radiology, Health Science Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, 3002 SunGangXi Road, Shenzhen, China
| | - Xiao-Lei Liu
- Department of Radiology, Health Science Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, 3002 SunGangXi Road, Shenzhen, China
| | - Xin-Ping Shen
- Department of Radiology, The University of Hong Kong-Shenzhen Hospital, 1st Hai Yuan Road, Shenzhen, China.
| | - Biao Huang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510282, People's Republic of China.
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou, Guangdong, China.
| | - Fan Lin
- Department of Radiology, Health Science Center, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, 3002 SunGangXi Road, Shenzhen, China.
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Lei Y, Feng B, Wan M, Xu K, Cui J, Ma C, Sun J, Yao C, Gan S, Shi J, Cui E. Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model. Abdom Radiol (NY) 2024; 49:1397-1410. [PMID: 38433144 DOI: 10.1007/s00261-024-04202-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 01/04/2024] [Accepted: 01/12/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS A total of 287 patients with HCC from our institution and 58 patients from another individual institution were included. Among these, 119 patients with only CT data and 116 patients with only MRI data were selected for single-modality deep learning model development, after which select parameters were migrated for MDL model development with transfer learning (TL). In addition, 110 patients with simultaneous CT and MRI data were divided into a training cohort (n = 66) and a validation cohort (n = 44). We input the features extracted from DenseNet121 into an extreme learning machine (ELM) classifier to construct a classification model. RESULTS The area under the curve (AUC) of the MDL model was 0.844, which was superior to that of the single-phase CT (AUC = 0.706-0.776, P < 0.05), single-sequence MRI (AUC = 0.706-0.717, P < 0.05), single-modality DL model (AUCall-phase CT = 0.722, AUCall-sequence MRI = 0.731; P < 0.05), clinical (AUC = 0.648, P < 0.05), but not to that of the delay phase (DP) and in-phase (IP) MRI and portal venous phase (PVP) CT models. The MDL model achieved better performance than models described above (P < 0.05). When combined with clinical features, the AUC of the MDL model increased from 0.844 to 0.871. A nomogram, combining deep learning signatures (DLS) and clinical indicators for MDL models, demonstrated a greater overall net gain than the MDL models (P < 0.05). CONCLUSION The MDL model is a valuable noninvasive technique for preoperatively predicting MVI in HCC.
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Affiliation(s)
- Yan Lei
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
- Zunyi Medical University, 1 Xiaoyuan Road, Zunyi, People's Republic of China
| | - Bao Feng
- Laboratory of Intelligent Detection and Information Processing, School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin, People's Republic of China
| | - Meiqi Wan
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
- Zunyi Medical University, 1 Xiaoyuan Road, Zunyi, People's Republic of China
| | - Kuncai Xu
- Laboratory of Intelligent Detection and Information Processing, School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin, People's Republic of China
| | - Jin Cui
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
| | - Changyi Ma
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
| | - Junqi Sun
- Department of Radiology, Yuebei People's Hospital, 133 Huimin Street, Shaoguan, People's Republic of China
| | - Changyin Yao
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
- Guangdong Medical University, 2 Wenming East Road, Zhanjiang, People's Republic of China
| | - Shiman Gan
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China
- Guangdong Medical University, 2 Wenming East Road, Zhanjiang, People's Republic of China
| | - Jiangfeng Shi
- Laboratory of Intelligent Detection and Information Processing, School of Electronic Information and Automation, Guilin University of Aerospace Technology, 2 Jinji Road, Guilin, People's Republic of China
| | - Enming Cui
- Department of Radiology, Jiangmen Central Hospital, 23 Beijie Haibang Street, Jiangmen, People's Republic of China.
- Zunyi Medical University, 1 Xiaoyuan Road, Zunyi, People's Republic of China.
- Guangdong Medical University, 2 Wenming East Road, Zhanjiang, People's Republic of China.
- Jiangmen Key Laboratory of Artificial Intelligence in Medical Image Computation and Application, 23 Beijie Haibang Street, Jiangmen, People's Republic of China.
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Tchilikidi KY. Actuality and underlying mechanisms of systemic immune-inflammation index and geriatric nutritional risk index prognostic value in hepatocellular carcinoma. World J Gastrointest Surg 2024; 16:260-265. [PMID: 38463345 PMCID: PMC10921210 DOI: 10.4240/wjgs.v16.i2.260] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/26/2023] [Accepted: 02/03/2024] [Indexed: 02/25/2024] Open
Abstract
This editorial contains comments on the article "Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer" in a recent issue of the World Journal of Gastrointestinal Surgery. It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immune-inflammation index (SII) and geriatric nutritional risk index (GNRI) prediction features valuable. There are few publications on both SII and GNRI together in hepatocellular carcinoma (HCC) and patient prognosis after radical surgery. Neutrophils release cytokines, chemokines, and enzymes, degrade extracellular matrix, reduce cell adhesion, and create conditions for tumor cell invasion. Neutrophils promote the adhesion of tumor cells to endothelial cells, through physical anchoring. That results in the migration of tumor cells. Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs. Platelets can form a protective film on the surface of tumor cells. This allows avoiding blood flow damage as well as immune system attack. It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness. High SII is also associated with macro- and microvascular invasion and increased numbers of circulating tumor cells. A high GNRI was associated with significantly better progression-free and overall survival. HCC patients are a very special population that requires increased attention. SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings. The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features. Those features provide tumor nutrition, growth, and distribution throughout the body, such as vascular invasion. On the other hand, they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings. The article is of considerable interest. It would be helpful to continue the study follow-up to 2 years and longer. External validation of the data is needed.
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Affiliation(s)
- Konstantin Y Tchilikidi
- Department of Surgery with Postgraduate Education, Altai State Medical University, Barnaul 656031, Russia
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You H, Wang J, Ma R, Chen Y, Li L, Song C, Dong Z, Feng S, Zhou X. Clinical Interpretability of Deep Learning for Predicting Microvascular Invasion in Hepatocellular Carcinoma by Using Attention Mechanism. Bioengineering (Basel) 2023; 10:948. [PMID: 37627833 PMCID: PMC10451856 DOI: 10.3390/bioengineering10080948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 07/26/2023] [Accepted: 08/03/2023] [Indexed: 08/27/2023] Open
Abstract
Preoperative prediction of microvascular invasion (MVI) is essential for management decision in hepatocellular carcinoma (HCC). Deep learning-based prediction models of MVI are numerous but lack clinical interpretation due to their "black-box" nature. Consequently, we aimed to use an attention-guided feature fusion network, including intra- and inter-attention modules, to solve this problem. This retrospective study recruited 210 HCC patients who underwent gadoxetate-enhanced MRI examination before surgery. The MRIs on pre-contrast, arterial, portal, and hepatobiliary phases (hepatobiliary phase: HBP) were used to develop single-phase and multi-phase models. Attention weights provided by attention modules were used to obtain visual explanations of predictive decisions. The four-phase fusion model achieved the highest area under the curve (AUC) of 0.92 (95% CI: 0.84-1.00), and the other models proposed AUCs of 0.75-0.91. Attention heatmaps of collaborative-attention layers revealed that tumor margins in all phases and peritumoral areas in the arterial phase and HBP were salient regions for MVI prediction. Heatmaps of weights in fully connected layers showed that the HBP contributed the most to MVI prediction. Our study firstly implemented self-attention and collaborative-attention to reveal the relationship between deep features and MVI, improving the clinical interpretation of prediction models. The clinical interpretability offers radiologists and clinicians more confidence to apply deep learning models in clinical practice, helping HCC patients formulate personalized therapies.
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Affiliation(s)
| | | | | | | | | | | | | | - Shiting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58th the Second Zhongshan Road, Guangzhou 510080, China; (H.Y.); (J.W.); (R.M.); (Y.C.); (L.L.); (C.S.); (Z.D.)
| | - Xiaoqi Zhou
- Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58th the Second Zhongshan Road, Guangzhou 510080, China; (H.Y.); (J.W.); (R.M.); (Y.C.); (L.L.); (C.S.); (Z.D.)
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Harmath CB. Beyond LI-RADS: Decoding the Prognostic Value of MRI Findings in HCC. Radiology 2023; 307:e223309. [PMID: 36786709 DOI: 10.1148/radiol.223309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Affiliation(s)
- Carla B Harmath
- From the Abdominal Imaging Section, Department of Radiology, The University of Chicago, 5841 S Maryland Ave, Chicago, IL 60639
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Wang T, Li Z, Yu H, Duan C, Feng W, Chang L, Yu J, Liu F, Gao J, Zang Y, Luo Z, Liu H, Zhang Y, Zhou X. Prediction of microvascular invasion in hepatocellular carcinoma based on preoperative Gd-EOB-DTPA-enhanced MRI: Comparison of predictive performance among 2D, 2D-expansion and 3D deep learning models. Front Oncol 2023; 13:987781. [PMID: 36816963 PMCID: PMC9936232 DOI: 10.3389/fonc.2023.987781] [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: 07/06/2022] [Accepted: 01/20/2023] [Indexed: 02/05/2023] Open
Abstract
Purpose To evaluate and compare the predictive performance of different deep learning models using gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in predicting microvascular invasion (MVI) in hepatocellular carcinoma. Methods The data of 233 patients with pathologically confirmed hepatocellular carcinoma (HCC) treated at our hospital from June 2016 to June 2021 were retrospectively analyzed. Three deep learning models were constructed based on three different delineate methods of the region of interest (ROI) using the Darwin Scientific Research Platform (Beijing Yizhun Intelligent Technology Co., Ltd., China). Manual segmentation of ROI was performed on the T1-weighted axial Hepatobiliary phase images. According to the ratio of 7:3, the samples were divided into a training set (N=163) and a validation set (N=70). The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of three models, and their sensitivity, specificity and accuracy were assessed. Results Among 233 HCC patients, 109 were pathologically MVI positive, including 91 men and 18 women, with an average age of 58.20 ± 10.17 years; 124 patients were MVI negative, including 93 men and 31 women, with an average age of 58.26 ± 10.20 years. Among three deep learning models, 2D-expansion-DL model and 3D-DL model showed relatively good performance, the AUC value were 0.70 (P=0.003) (95% CI 0.57-0.82) and 0.72 (P<0.001) (95% CI 0.60-0.84), respectively. In the 2D-expansion-DL model, the accuracy, sensitivity and specificity were 0.7143, 0.739 and 0.688. In the 3D-DL model, the accuracy, sensitivity and specificity were 0.6714, 0.800 and 0.575, respectively. Compared with the 3D-DL model (based on 3D-ResNet), the 2D-DL model is smaller in scale and runs faster. The frames per second (FPS) for the 2D-DL model is 244.7566, which is much larger than that of the 3D-DL model (73.3374). Conclusion The deep learning model based on Gd-EOB-DTPA-enhanced MRI could preoperatively evaluate MVI in HCC. Considering that the predictive performance of 2D-expansion-DL model was almost the same as the 3D-DL model and the former was relatively easy to implement, we prefer the 2D-expansion-DL model in practical research.
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Affiliation(s)
- Tao Wang
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Zhen Li
- School of Medical Imaging, Weifang Medical University, Weifang, Shandong, China
| | - Haiyang Yu
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Chongfeng Duan
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Weihua Feng
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | | | - Jing Yu
- Yizhun Medical AI Co., Ltd, Beijing, China
| | - Fang Liu
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Juan Gao
- Department of Cardiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Yichen Zang
- Department of Ultrasound, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Ziwei Luo
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Hao Liu
- Yizhun Medical AI Co., Ltd, Beijing, China
| | - Yu Zhang
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
| | - Xiaoming Zhou
- Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China,*Correspondence: Xiaoming Zhou,
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PET-guided attention for prediction of microvascular invasion in preoperative hepatocellular carcinoma on PET/CT. Ann Nucl Med 2023; 37:238-245. [PMID: 36723705 DOI: 10.1007/s12149-023-01822-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/23/2023] [Indexed: 02/02/2023]
Abstract
PURPOSE To achieve PET/CT-based preoperative prediction of microvascular invasion in hepatocellular carcinoma by combining the advantages of PET and CT. METHODS This retrospective study included a total of 100 patients from two institutions who underwent PET/CT imaging. The above patients were divided into a training cohort (n = 70) and a validation cohort (n = 30). This study was based on PET/CT images to evaluate the possibility of microvascular invasion (MVI) of patients. In this study, we proposed a two-branch PET-guided attention network to predict MVI. The model used a two-branch network to extract image features from PET and CT, respectively. The PET-guided attention module aimed to enable the model to focus on the lesion region and reduce the disturbance of irrelevant and redundant information. Model performance was evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) curve. RESULTS The method outperformed the single-modality prediction model for preoperative hepatocyte microvascular invasion, achieving an AUC of 0.907. On the validation set, accuracy reached 0.846, precision reached 0.881, recall 0.793, and F1-score 0.835. CONCLUSION The model exploits the particularities of the molecular metabolic function of PET and the anatomical structure of CT and can strongly improve the accuracy of clinical diagnosis of MVI.
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TED: Two-stage expert-guided interpretable diagnosis framework for microvascular invasion in hepatocellular carcinoma. Med Image Anal 2022; 82:102575. [DOI: 10.1016/j.media.2022.102575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 07/08/2022] [Accepted: 08/11/2022] [Indexed: 12/16/2022]
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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.
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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
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Shi H, Duan Y, Shi J, Zhang W, Liu W, Shen B, Liu F, Mei X, Li X, Yuan Z. Role of preoperative prediction of microvascular invasion in hepatocellular carcinoma based on the texture of FDG PET image: A comparison of quantitative metabolic parameters and MRI. Front Physiol 2022; 13:928969. [PMID: 36035488 PMCID: PMC9412047 DOI: 10.3389/fphys.2022.928969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/13/2022] [Indexed: 11/15/2022] Open
Abstract
Objective: To investigate the role of prediction microvascular invasion (mVI) in hepatocellular carcinoma (HCC) by 18F-FDG PET image texture analysis and hybrid criteria combining PET/CT and multi-parameter MRI. Materials and methods: Ninety-seven patients with HCC who received the examinations of MRI and 18F-FDG PET/CT were retrospectively included in this study and were randomized into training and testing cohorts. The lesion image texture features of 18F-FDG PET were extracted using MaZda software. The optimal predictive texture features of mVI were selected, and the classification procedure was conducted. The predictive performance of mVI by radiomics classier in training and testing cohorts was respectively recorded. Next, the hybrid model was developed by integrating the 18F-FDG PET image texture, metabolic parameters, and MRI parameters to predict mVI through logistic regression. Furthermore, the diagnostic performance of each time was recorded. Results: The 18F-FDG PET image radiomics classier showed good predicted performance in both training and testing cohorts to discriminate HCC with/without mVI, with an AUC of 0.917 (95% CI: 0.824–0.970) and 0.771 (95% CI: 0.578, 0.905). The hybrid model, which combines radiomics classier, SUVmax, ADC, hypovascular arterial phase enhancement pattern on contrast-enhanced MRI, and non-smooth tumor margin, also yielded better predictive performance with an AUC of 0.996 (95% CI: 0.939, 1.000) and 0.953 (95% CI: 0.883, 1.000). The differences in AUCs between radiomics classier and hybrid classier were significant in both training and testing cohorts (DeLong test, both p < 0.05). Conclusion: The radiomics classier based on 18F-FDG PET image texture and the hybrid classier incorporating 18F-FDG PET/CT and MRI yielded good predictive performance, which might provide a precise prediction of HCC mVI preoperatively.
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Affiliation(s)
- Huazheng Shi
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Ying Duan
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Jie Shi
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital, The Second Military Medical University, Shanghai, China
| | - Wenrui Zhang
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Weiran Liu
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Bixia Shen
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Fufu Liu
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Xin Mei
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
| | - Xiaoxiao Li
- Shanghai Universal Cloud Medical Imaging Diagnostic Center, Shanghai, China
- *Correspondence: Zheng Yuan, ; Xiaoxiao Li,
| | - Zheng Yuan
- Department of Radiology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- *Correspondence: Zheng Yuan, ; Xiaoxiao Li,
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Preoperative application of systemic inflammatory biomarkers combined with MR imaging features in predicting microvascular invasion of hepatocellular carcinoma. Abdom Radiol (NY) 2022; 47:1806-1816. [PMID: 35267069 DOI: 10.1007/s00261-022-03473-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate whether systemic inflammatory biomarkers compared with the imaging features interpreted by radiologists can offer complementary value for predicting the risk of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). METHODS A total of 156 patients with histologically confirmed HCC between Jan 2018 and Dec 2020 were retrospectively enrolled in the primary cohort. Preoperative clinical-inflammatory biomarkers and MR imaging of the patients were recorded and then evaluated as an inflammatory score (Inflam-score) and imaging feature score (Radio-score). Six Inflam-scores and 12 Radio-scores were determined from each patient by univariate analysis. Logistic regression was performed to select risk factors for MVI and establish a predictive nomogram. Decision curve analysis was applied to estimate the incremental value of the Inflam-score to the Radio-score for predicting MVI. RESULTS Four Radio-scores and 2 Inflam-scores, namely, larger tumor size, non-smooth tumor margin, presence of satellite nodules, presence of peritumoral enhance, higher neutrophil-lymphocyte ratio (NLR), and lower prognostic nutritional index (PNI), were significantly associated with MVI (p < 0.05). An MVI risk prediction nomogram was then constructed with an area under the curve (AUC) of 0.868 (95% CI 0.806-0.931). Adding Inflam-scores to Radio-scores improved the sensitivity of the model from 60.9 to 80.4% in receiver operating characteristic (ROC) curve analysis and led to a net benefit in decision curve analysis. CONCLUSION Systemic inflammatory biomarkers are complementary tools that provide additional benefit to conventional imaging estimation for predicting MVI in HCC patients.
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Wang Y, Luo S, Jin G, Fu R, Yu Z, Zhang J. Preoperative clinical-radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using
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F-FDG PET/CT. BMC Med Imaging 2022; 22:70. [PMID: 35428272 PMCID: PMC9013080 DOI: 10.1186/s12880-022-00796-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/05/2022] [Indexed: 11/10/2022] Open
Abstract
PURPOSE To develop a clinical-radiomics nomogram by incorporating radiomics score and clinical predictors for preoperative prediction of microvascular invasion in hepatocellular carcinoma. METHODS A total of 97 HCC patients were retrospectively enrolled from Shanghai Universal Medical Imaging Diagnostic Center and Changhai Hospital Affiliated to the Second Military Medical University. 909 CT and 909 PET slicers from 97 HCC patients were divided into a training cohort (N = 637) and a validation cohort (N = 272). Radiomics features were extracted from each CT or PET slicer, and features selection was performed with least absolute shrinkage and selection operator regression and radiomics score was also generated. The clinical-radiomics nomogram was established by integrating radiomics score and clinical predictors, and the performance of the models were evaluated from its discrimination ability, calibration ability, and clinical usefulness. RESULTS The radiomics score consisted of 45 selected features, and age, the ratio of maximum to minimum tumor diameter, and18 F-FDG uptake status were independent predictors of microvascular invasion. The clinical-radiomics nomogram showed better performance for MVI detection (0.890 [0.854, 0.927]) than the clinical nomogram (0.849 [0.804, 0.893]) (p < 0.05 ). Both nomograms showed good calibration and the clinical-radiomics nomogram's clinical practicability outperformed the clinical nomogram. CONCLUSIONS With the combination of radiomics score and clinical predictors, the clinical-radiomics nomogram can significantly improve the predictive efficacy of microvascular invasion in hepatocellular carcinoma (p < 0.05 ) compared with clinical nomogram.
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Affiliation(s)
- Yutao Wang
- The Affiliated Hospital of Medical School, Ningbo University, Ningbo, Zhejiang Province 315020 China
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai University, Building 8, 406 Guilin Road, Xuhui District, Shanghai, 201103 China
| | - Shuying Luo
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, Zhejiang Province 315211 China
| | - Gehui Jin
- Medical School, Ningbo University, Ningbo, Zhejiang Province 315211 China
| | - Randi Fu
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, Zhejiang Province 315211 China
| | - Zhongfei Yu
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai University, Building 8, 406 Guilin Road, Xuhui District, Shanghai, 201103 China
| | - Jian Zhang
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai University, Building 8, 406 Guilin Road, Xuhui District, Shanghai, 201103 China
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Çelebi F, Görmez A, Serkan Ilgun A, Tokat Y, Cem Balcı N. The role of 18F- FDG PET/MRI in preoperative prediction of MVI in patients with HCC. Eur J Radiol 2022; 149:110196. [DOI: 10.1016/j.ejrad.2022.110196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 12/12/2022]
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Zhao Y, Wu L, Qin H, Li Q, Shen C, He Y, Yang H. Preoperative combi-elastography for the prediction of early recurrence after curative resection of hepatocellular carcinoma. Clin Imaging 2021; 79:173-178. [PMID: 34087717 DOI: 10.1016/j.clinimag.2021.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/07/2021] [Accepted: 05/21/2021] [Indexed: 01/27/2023]
Abstract
PURPOSE To estimate the prognostic value of preoperative combi-elastography for early recurrence (ER) of hepatocellular carcinoma (HCC) after radical resection. METHODS A total of 94 HCC patients undergoing hepatectomy from January to August 2019 were included. The combined elastography (ARIETTA 850, Hitachi Healthcare) was used for real-time tissue elastography and shear wave measurement analysis. Six elastography related indicators were calculated. The patients were randomly divided into a training and a validation group in a 7:3 ratio and prediction model was assessed about discrimination capability by using area under the receiver operating curve. Univariate and multivariate analyses were performed to determine the prognostic value of clinicopathological factors, laboratory tests, and elastography for HCC ER. RESULTS The Vs, E, F, and A indexes were significantly higher in patients with ER than in those without ER (P = 0.002, P = 0.002, P < 0.001, and P < 0.001, respectively). Multivariate logistic regression analysis indicated that microvascular invasion (MVI, odds ratio [OR] = 3.964, 95% confidence interval [CI] = 1.326-11.845; P = 0.010) and the F index (OR = 9.533, 95%CI = 1.921-47.296; P = 0.006) were independent predictors of ER in HCC. A ER prediction model based on laboratory tests, MVI and F index were moderate [area under curves (AUCs) in training and validation cohort were 0.829(95%CI: 0.723-0.935; P < 0.001) and 0.846 (95%CI: 0.699-0.994; P = 0.002), respectively]. CONCLUSION Preoperative combi-elastography analysis could be used as a potential prognostic tool for HCC ER and assist in clinical decision-making.
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Affiliation(s)
- Yujia Zhao
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Linyong Wu
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Hui Qin
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Qing Li
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | | | - Yun He
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Hong Yang
- Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China.
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Wu Y, Tu C, Shao C. The value of preoperative systemic immune-inflammation index in predicting vascular invasion of hepatocellular carcinoma: a meta-analysis. ACTA ACUST UNITED AC 2021; 54:e10273. [PMID: 33656054 PMCID: PMC7917783 DOI: 10.1590/1414-431x202010273] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 11/25/2020] [Indexed: 01/17/2023]
Abstract
Vascular invasion and systemic immune-inflammation index (SII) are risk factors for the prognosis of patients with hepatocellular carcinoma. At present, the correlation between the two is not clear. This meta-analysis explored the relationship between preoperative SII and vascular invasion in patients with hepatocellular carcinoma. According to the search formula, the Pubmed, Embase, Cochrane, Web of Science, and CNKI databases were searched for the relevant research until March 2020. After the quality evaluation of the included literature, the odds ratio (OR) and its corresponding 95% confidence interval (CI) were used as the effect measure. Stata 15. 0 software was used for statistical analysis. The meta-analysis eventually included seven retrospective cohort studies of 3583 patients with hepatocellular carcinoma. The results showed that the choice of SII cut-off value affects SII's efficiency in predicting the risk of vascular invasion. In the cohort of studies with appropriate SII cut-off value, the high SII preoperative group had a higher risk of vascular invasion (OR=2.62; 95%CI: 2.07-3.32; P=0.000) and microvascular invasion (OR=1.82; 95%CI: 1.01-3.25; P=0.045) than the low SII group. The tumor diameter (OR=2.88; 95%CI: 1.73-4. 80; P=0.000) of the high SII group was larger than that of the low SII group. There was no publication bias in this study (Begg's test, P=0.368). As a routine, cheap, and easily available index, SII can provide a certain reference value for clinicians to evaluate vascular invasion before operation.
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Affiliation(s)
- YiFeng Wu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China
| | - ChaoYong Tu
- Department of Hepatobiliary and Pancreatic Surgery, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Municipal Central Hospital, Lishui, Zhejiang Province, China
| | - ChuXiao Shao
- Department of Hepatobiliary and Pancreatic Surgery, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Municipal Central Hospital, Lishui, Zhejiang Province, China
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Dynamic Contrast-Enhanced Ultrasound Radiomics for Hepatocellular Carcinoma Recurrence Prediction After Thermal Ablation. Mol Imaging Biol 2021; 23:572-585. [PMID: 33483803 DOI: 10.1007/s11307-021-01578-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 12/23/2020] [Accepted: 01/05/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a radiomics model based on dynamic contrast-enhanced ultrasound (CEUS) to predict early and late recurrence in patients with a single HCC lesion ≤ 5 cm in diameter after thermal ablation. PROCEDURES We enrolled patients who underwent thermal ablation for HCC in our hospital from April 2004 to April 2017. Radiomics based on two branch convolution recurrent network was utilized to analyze preoperative dynamic CEUS image of HCC lesions to establish CEUS model, in comparison to the conventional ultrasound (US), clinical, and combined models. Clinical follow-up of HCC recurrence after ablation were taken as reference standard to evaluate the predicted performance of CEUS model and other models. RESULTS We finally analyzed 318 patients (training cohort: test cohort = 255:63). The combined model showed better performance for early recurrence than CUES (in training cohort, AUC, 0.89 vs. 0.84, P < 0.001; in test cohort, AUC, 0.84 vs. 0.83, P = 0.272), US (P < 0.001), or clinical model (P < 0.001). For late recurrence prediction, the combined model showed the best performance than the CEUS (C-index, in training cohort, 0.77 vs. 0.76, P = 0.009; in test cohort, 0.77 vs. 0.68, P < 0.001), US (P < 0.001), or clinical model (P < 0.001). CONCLUSIONS The CEUS model based on dynamic CEUS radiomics performed well in predicting early HCC recurrence after ablation. The combined model combining CEUS, US radiomics, and clinical factors could stratify the high risk of late recurrence.
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Li Y, Zhang Y, Fang Q, Zhang X, Hou P, Wu H, Wang X. Radiomics analysis of [ 18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma. Eur J Nucl Med Mol Imaging 2021; 48:2599-2614. [PMID: 33416951 DOI: 10.1007/s00259-020-05119-9] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/15/2020] [Indexed: 12/16/2022]
Abstract
As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [18F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC). METHODS Patients (N = 80) with BCLC0-A HCC who underwent [18F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated. RESULTS To predict MVI, the [18F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799-0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [18F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761-0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses. CONCLUSION The newly developed [18F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [18F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.
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Affiliation(s)
- Youcai Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Yin Zhang
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, Guangdong Province, China
| | - Qi Fang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Xiaoyao Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Peng Hou
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Hubing Wu
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, Guangdong Province, China.
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
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CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma. J Digit Imaging 2020; 33:1365-1375. [PMID: 32968880 DOI: 10.1007/s10278-020-00386-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 08/29/2020] [Accepted: 09/14/2020] [Indexed: 12/15/2022] Open
Abstract
The objective of this study was to determine the clinical value of computed tomography (CT) image-based texture analysis in predicting microvascular invasion of primary hepatocellular carcinoma (HCC). CT images of patients with HCC from May 2017 to May 2019 confirmed by surgery and histopathology were retrospectively analyzed. Image features including tumor margin, tumor capsule, peritumoral enhancement, hypoattenuating halo, intratumoral arteries, and tumor-liver differences were assessed. All patients were divided into microvascular invasion (MVI)-negative group (n = 34) and MVI-positive group (n = 68). Preoperative CT images were further imported into MaZda software, where the regions of interest of the lesions were manually delineated. Texture features of lesions based on pre-contrast, arterial, portal, and equilibrium phase CT images were extracted. Thirty optimal texture parameters were selected from each phase by Fisher's coefficient (Fisher), classification error probability combined with average correlation coefficient (POE+ACC), and mutual information (MI). Finally, receiver operating characteristic curve analysis was performed. The results showed that the Edmonson-Steiner grades, tumor size, tumor margin, and intratumoral artery characteristics were significantly different between the two groups (P = 0.012, < 0.001, < 0.001, = 0.003, respectively). There were 58 parameters with significant differences between the MVI-negative and MVI-positive groups (P < 0.001 for all). Among them, 12, 14, 17, and 15 parameters were derived from the pre-contrast phase, arterial phase, portal phase, and equilibrium phase respectively. According to the ROC analysis, optimal texture parameters based on the pre-contrast, arterial, portal, and equilibrium phases were 135dr_GLevNonU (AUC, 0.766; the cutoff value, 1055.00), Vertl_RLNonUni (AUC, 0.764; the cutoff value, 5974.38), 45dgr_GLevNonU (AUC, 0.762; the cutoff value, 924.34), and Vertl_RLNonUni (AUC, 0.754; the cutoff value, 4868.80), respectively. Texture analysis of preoperative CT images may be used as a non-invasive method to predict microvascular invasion in patients with primary hepatocellular carcinomas, and further to guide the treatment and evaluate prognosis. The most valuable parameters were derived from the gray-level run-length matrix.
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Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology. Eur Radiol 2020; 30:5327-5336. [PMID: 32367417 DOI: 10.1007/s00330-020-06895-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 03/04/2020] [Accepted: 04/14/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To assess the accuracy of gadobenate-enhanced MRI for predicting microvascular invasion (MVI) in patients operated for hepatocellular carcinoma (HCC). METHODS The 164 patients who met the inclusion criteria were assigned to one of two groups: the MVI-positive group and the MVI-negative group. Imaging results were compared between the two groups using the Kruskal test, chi-square test, independent sample t test, and logistic regression analysis. RESULTS Differences in the capsule (p = 0.037) and margin (p = 0.004) of the tumor, rim enhancement (p = 0.002), peritumoral enhancement in the arterial phase (p < 0.001), and peritumoral hypointensity in the hepatobiliary phase (HBP) (p < 0.001) were statistically significant. The results of multivariate analysis identified rim enhancement in the arterial phase (odds ratio (OR) = 2.115; 95% confidence interval (CI), 1.002-4.464; p = 0.049) and peritumoral hypointensity in the HBP (OR = 5.836; 95% CI, 2.442-13.948; p < 0.001) as independent risk factors for MVI. Use of the two predictors in combination identified 32.79% (20/61) of HCCs with MVI with a specificity of 95.15% (98/103). CONCLUSIONS Rim enhancement in the arterial phase and peritumoral hypointensity in the HBP were identified as independent risk factors for MVI in patients with HCC. KEY POINTS • Rim enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for microvascular invasion in patients with HCC. • Use of the two predictors in combination had a sensitivity of 32.79% and a specificity of 95.15% for predicting microvascular invasion.
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Abstract
OBJECTIVE To investigate whether subclassification of microscopic vascular invasion (MiVI) affects the long-term outcome after curative surgical resection or liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). SUMMARY OF BACKGROUND DATA The most important factor for TNM staging in HCC is MiVI, which includes all vascular invasions detected on microscopic examination. However, there is a broad spectrum of current definitions for MiVI. METHODS In total, 412 consecutive patients with HCC who underwent curative surgical resection without any preoperative treatment or gross vascular invasion were histologically evaluated for MiVI. Patients with MiVI were subclassified into 2 groups: microvessel invasion (MI; n = 164) only and microscopic portal vein invasion (MPVI; n = 36). Clinicopathologic features were compared between 2 groups (MI vs MPVI), whereas disease-free survival (DFS) and overall survival (OS) after resection were analyzed among 3 groups (no vascular invasion [NVI] vs MI vs MPVI). These subclassifications were validated in a cohort of 197 patients with HCC who underwent LT. RESULTS The MPVI group showed more aggressive tumor characteristics, such as higher tumor marker levels (alpha-fetoprotein, P = 0.006; protein induced by vitamin K absence-II, P = 0.001) and poorer differentiation (P = 0.011), than the MI group. In multivariate analysis, both MI and MPVI were independent prognostic factors for DFS (P = 0.001 and <0.001, respectively) and OS (P = 0.005 and <0.001, respectively). In the validation cohort, 5-year DFS was 89%, 67.9%, and 0% in the NVI, MI, and MPVI groups, respectively (P < 0.001), whereas 5-year OS was 79.1%, 55.0%, and 15.4%, respectively (P < 0.001). CONCLUSIONS Based on subclassification of MiVI in HCC, MPVI was associated with more aggressive clinicopathologic characteristics and poorer survival than MI only. Therefore, the original MiVI classification should be divided into MI and MPVI.
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Lahan-Martins D, Perales SR, Gallani SK, da Costa LBE, Lago EAD, Boin IDFSF, Caserta NMG, de Ataide EC. Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters? Radiol Bras 2019; 52:287-292. [PMID: 31656344 PMCID: PMC6808613 DOI: 10.1590/0100-3984.2018.0123] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Objective To investigate whether quantitative computed tomography (CT) measurements
can predict microvascular invasion (MVI) in hepatocellular carcinoma
(HCC). Materials and Methods This was a retrospective analysis of 200 cases of surgically proven HCCs in
125 consecutive patients evaluated between March 2010 and November 2017. We
quantitatively measured regions of interest in lesions and adjacent areas of
the liver on unenhanced CT scans, as well as in the arterial, portal venous,
and equilibrium phases on contrast-enhanced CT scans. Enhancement profiles
were analyzed and compared with histopathological references of MVI.
Univariate and multivariate logistic regression analyses were used in order
to evaluate CT parameters as potential predictors of MVI. Results Of the 200 HCCs, 77 (38.5%) showed evidence of MVI on histopathological
analysis. There was no statistical difference between HCCs with MVI and
those without, in terms of the percentage attenuation ratio in the portal
venous phase (114.7 vs. 115.8) and equilibrium phase (126.7 vs. 128.2), as
well as in terms of the relative washout ratio, also in the portal venous
and equilibrium phases (15.0 vs. 8.2 and 31.4 vs. 26.3, respectively). Conclusion Quantitative dynamic CT parameters measured in the preoperative period do
not appear to correlate with MVI in HCC.
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Affiliation(s)
- Daniel Lahan-Martins
- Hospital de Clínicas da Universidade Estadual de Campinas (HC-Unicamp), Campinas, SP, Brazil
| | - Simone Reges Perales
- Hospital de Clínicas da Universidade Estadual de Campinas (HC-Unicamp), Campinas, SP, Brazil
| | - Stephanie Kilaris Gallani
- Faculdade de Ciências Médicas da Universidade Estadual de Campinas (FCM-Unicamp), Campinas, SP, Brazil
| | | | | | | | | | - Elaine Cristina de Ataide
- Faculdade de Ciências Médicas da Universidade Estadual de Campinas (FCM-Unicamp), Campinas, SP, Brazil
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Lu W, Tang H, Yang Z, Jiang K, Chen Y, Lu S. Clinical predictors of small solitary hepatitis B virus-related hepatocellular carcinoma microinvasion. ANZ J Surg 2019; 89:E438-E442. [PMID: 31508888 DOI: 10.1111/ans.15403] [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: 06/01/2019] [Revised: 07/17/2019] [Accepted: 07/18/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Microinvasion serves as a reliable indicator of poor prognosis after hepatectomy or transplantation for hepatocellular carcinoma (HCC). However, microinvasion is difficult to detect with current imaging modalities and is usually diagnosed histopathologically. The aim of this study is to identify the preoperative clinical predictors of microinvasion of small solitary hepatitis B virus (HBV)-related HCC. METHODS From January 2000 to December 2009, 110 patients with HBV-related small primary solitary HCC (tumour diameter ≤3.0 cm) who underwent hepatectomy at Chinese PLA General Hospital were enrolled. The independent predictors of microinvasion, such as microvascular invasion and microscopic satellite nodules, were analysed. The prognosis of patients with microinvasion was compared with that of patients without microinvasion. RESULTS Of the 110 patients, 31 (28.2%) exhibited microinvasion. Among them, 16 (51.6%) had microvascular invasion with microscopic satellite nodules, five (16.1%) had microscopic satellite nodules without microvascular invasion and 10 (32.3%) had microvascular invasion without microscopic satellite nodules. Two independent predictors of microinvasion were identified: serum alpha-fetoprotein >20 ng/mL and a viral load of >104 copies/mL. Patients without microinvasion exhibited a significantly better prognostic outcome compared with those with microinvasion. CONCLUSION Regarding HBV-related small HCC, patients presenting with alpha-fetoprotein levels >20 ng/mL and a high viral load (HBV-DNA >104 copies/mL) are at substantial risk for microinvasion.
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Affiliation(s)
- Wenping Lu
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Haowen Tang
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Zhanyu Yang
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Kai Jiang
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yongliang Chen
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shichun Lu
- Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, China
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Ni M, Zhou X, Lv Q, Li Z, Gao Y, Tan Y, Liu J, Liu F, Yu H, Jiao L, Wang G. Radiomics models for diagnosing microvascular invasion in hepatocellular carcinoma: which model is the best model? Cancer Imaging 2019; 19:60. [PMID: 31455432 PMCID: PMC6712704 DOI: 10.1186/s40644-019-0249-x] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 08/14/2019] [Indexed: 12/16/2022] Open
Abstract
Objectives To explore the feasibility of diagnosing microvascular invasion (MVI) with radiomics, to compare the diagnostic performance of different models established by each method, and to determine the best diagnostic model based on radiomics. Methods A retrospective analysis was conducted with 206 cases of hepatocellular carcinoma (HCC) confirmed through surgery and pathology in our hospital from June 2015 to September 2018. Among the samples, 88 were MVI-positive, and 118 were MVI-negative. The radiomics analysis process included tumor segmentation, feature extraction, data preprocessing, dimensionality reduction, modeling and model evaluation. Results A total of 1044 sets of texture feature parameters were extracted, and 21 methods were used for the radiomics analysis. All research methods could be used to diagnose MVI. Of all the methods, the LASSO+GBDT method had the highest accuracy, the LASSO+RF method had the highest sensitivity, the LASSO+BPNet method had the highest specificity, and the LASSO+GBDT method had the highest AUC. Through Z-tests of the AUCs, LASSO+GBDT, LASSO+K-NN, LASSO+RF, PCA + DT, and PCA + RF had Z-values greater than 1.96 (p<0.05). The DCA results showed that the LASSO + GBDT method was better than the other methods when the threshold probability was greater than 0.22. Conclusions Radiomics can be used for the preoperative, noninvasive diagnosis of MVI, but different dimensionality reduction and modeling methods will affect the diagnostic performance of the final model. The model established with the LASSO+GBDT method had the optimal diagnostic performance and the greatest diagnostic value for MVI.
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Affiliation(s)
- Ming Ni
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Xiaoming Zhou
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China.
| | - Qian Lv
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Zhiming Li
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Yuanxiang Gao
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Yongqi Tan
- College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China
| | - Jihua Liu
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Fang Liu
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Haiyang Yu
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Linlin Jiao
- Intervention Medical Center, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China
| | - Gang Wang
- Department of Radiology, The Affiliated Hospital of QingDao University, QingDao, ShanDong, China.
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Chou YC, Lao IH, Hsieh PL, Su YY, Mak CW, Sun DP, Sheu MJ, Kuo HT, Chen TJ, Ho CH, Kuo YT. Gadoxetic acid-enhanced magnetic resonance imaging can predict the pathologic stage of solitary hepatocellular carcinoma. World J Gastroenterol 2019; 25:2636-2649. [PMID: 31210715 PMCID: PMC6558433 DOI: 10.3748/wjg.v25.i21.2636] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/30/2019] [Accepted: 05/08/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Although important for determining long-term outcome, pathologic stage of hepatocellular carcinoma (HCC) is difficult to predict before surgery. Current state-of-the-art magnetic resonance imaging (MRI) using gadoxetic acid provides many imaging features that could potentially be used to classify single HCC as pT1 or pT2.
AIM To determine which gadoxetic acid-enhanced MRI (EOB-MRI) findings predict pathologic stage T2 in patients with solitary HCC (cT1).
METHODS Pre-operative EOB-MRI findings were reviewed in a retrospective cohort of patients with solitary HCC. The following imaging features were examined: Hyperintensity in unenhanced T2-weighted images, hypointensity in unenhanced T1-weighted images, arterial enhancement, corona enhancement, washout appearance, capsular appearance, hypointensity in the tumor tissue during the hepatobiliary (HB) phase, peritumoral hypointensity in the HB phase, hypointense rim in the HB phase, intratumoral fat, hyperintensity on diffusion-weighted imaging, hypointensity on apparent diffusion coefficient map, mosaic appearance, nodule-in-nodule appearance, and the margin (smooth or irregular). Surgical pathology was used as the reference method for tumor staging. Univariate and multivariate analyses were performed to identify predictors of microvascular invasion or satellite nodules.
RESULTS There were 39 (34.2%; 39 of 114) and 75 (65.8%; 75 of 114) pathological stage T2 and T1 HCCs, respectively. Large tumor size (≥ 2.3 cm) and two MRI findings, i.e., corona enhancement [odds ratio = 2.67; 95% confidence interval: 1.101-6.480] and peritumoral hypointensity in HB phase images (odds ratio = 2.203; 95% confidence interval: 0.961-5.049) were associated with high risk of pT2 HCC. The positive likelihood ratio was 6.25 (95% confidence interval: 1.788-21.845), and sensitivity of EOB-MRI for detecting pT2 HCC was 86.2% when two or three of these MRI features were present. Small tumor size and hypointense rim in the HB phase were regarded as benign features. Small HCCs with hypointense rim but not associated with aggressive features were mostly pT1 lesions (specificity, 100%).
CONCLUSION Imaging features on EOB-MRI could potentially be used to predict the pathologic stage of solitary HCC (cT1) as pT1 or pT2.
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Affiliation(s)
- Yi-Chen Chou
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - I-Ha Lao
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
- Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Pei-Ling Hsieh
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ying-Ying Su
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Chee-Wai Mak
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ding-Ping Sun
- Department of Surgery, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Food Science and Technology, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Ming-Jen Sheu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Medicinal Chemistry, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Hsing-Tao Kuo
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Senior Citizen Service Management, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Tzu-Ju Chen
- Department of Pathology, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan 717, Taiwan
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
| | - Chung-Han Ho
- Department of Medical Research, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Hospital and Health Care Administration, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Yu-Ting Kuo
- Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
- Department of Radiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
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Shan QY, Hu HT, Feng ST, Peng ZP, Chen SL, Zhou Q, Li X, Xie XY, Lu MD, Wang W, Kuang M. CT-based peritumoral radiomics signatures to predict early recurrence in hepatocellular carcinoma after curative tumor resection or ablation. Cancer Imaging 2019; 19:11. [PMID: 30813956 PMCID: PMC6391838 DOI: 10.1186/s40644-019-0197-5] [Citation(s) in RCA: 124] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 02/17/2019] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment. MATERIALS AND METHODS In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI). RESULTS By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E (P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 (P = 0.01) compared to PT-E. CONCLUSION The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E.
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Affiliation(s)
- Quan-Yuan Shan
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Hang-Tong Hu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Shi-Ting Feng
- Department of Radiology, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Zhen-Peng Peng
- Department of Radiology, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Shu-Ling Chen
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Qian Zhou
- Clinical Trials Unit, the First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Xin Li
- GE Healthcare, Shanghai, China
| | - Xiao-Yan Xie
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Ming-de Lu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China.,Department of Liver Surgery, Division of Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China
| | - Wei Wang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China.
| | - Ming Kuang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, Ultrasomics Artificial Intelligence X-Lab, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China. .,Department of Liver Surgery, Division of Interventional Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China.
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Wang J, Shan Q, Liu Y, Yang H, Kuang S, He B, Zhang Y, Chen J, Zhang T, Glaser KJ, Zhu C, Chen J, Yin M, Venkatesh SK, Ehman RL. 3D MR Elastography of Hepatocellular Carcinomas as a Potential Biomarker for Predicting Tumor Recurrence. J Magn Reson Imaging 2018; 49:719-730. [PMID: 30260529 DOI: 10.1002/jmri.26250] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 06/19/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Preoperative prediction of tumor recurrence is important in the management of patients with hepatocellular carcinoma (HCC). PURPOSE To investigate whether tumor stiffness derived by magnetic resonance elastography (MRE) could predict early recurrence of HCC after hepatic resection. STUDY TYPE Retrospective. POPULATION In all, 99 patients with pathologically confirmed HCCs after surgical resection. FIELD STRENGTH/SEQUENCE 3.0T; preoperative MRE with 60-Hz mechanical vibrations using an active acoustic driver. ASSESSMENT Regions of interest (ROIs) were manually drawn in the tumors to measure mean tumor stiffness. Surgical specimens were reviewed for histological grade, capsule, vascular invasion, and surgical margins. The early recurrence of HCC was defined as that occurring within 2 years after resection. STATISTICAL TESTS Cox proportional hazard models were used to evaluate risk factors associated with the time to early recurrence. RESULTS HCCs with recurrence had higher tumor stiffness, higher rate of advanced T stage, vascular invasion, lower rate of capsule formation, larger tumor size, higher aspartate aminotransferase (AST), and hepatitis B virus (HBV)-DNA level and aspartate aminotransferase / alanine aminotransferase ratio (P = 0.031, 0.007, 0.01, <0.001, 0.015, 0.034, 0.01, and 0.014, respectively) than HCCs without recurrence. Vascular invasion (hazard ratio [HR] = 2.922; 95% confidence interval [CI]: [1.079, 7.914], P = 0.035) and mean tumor stiffness (HR = 1.163; 95% CI: [1.055, 1.282], P = 0.002) were risk factors associated with early recurrence. Each 1-kPa increase in tumor stiffness was associated with a 16.3% increase in the risk for tumor recurrence. DATA CONCLUSION The mean stiffness of HCCs may be a useful, noninvasive, quantitative biomarker for the prediction of early HCC recurrence after hepatic resection. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;49:719-730.
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Affiliation(s)
- Jin Wang
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Qungang Shan
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Yong Liu
- Department of Pathology, Third Affiliated Hospital, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Hao Yang
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Sichi Kuang
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Bingjun He
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Yao Zhang
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Jingbiao Chen
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Tianhui Zhang
- Department of Radiology, Sun Yat-Sen University (SYSU), Guangzhou, Guangdong, P.R. China
| | - Kevin J Glaser
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Cairong Zhu
- Department of Epidemiology and Biostatistics, West China School of Public Health Sichuan University, Chengdu, P.R. China
| | - Jun Chen
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Sudhakar K Venkatesh
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, Minnesota, USA
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Yang C, Wang H, Tang Y, Rao S, Sheng R, Ji Y, Zeng M. ADC similarity predicts microvascular invasion of bifocal hepatocellular carcinoma. Abdom Radiol (NY) 2018; 43:2295-2302. [PMID: 29392365 DOI: 10.1007/s00261-018-1469-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE This study aimed to investigate whether ADC similarity can predict microvascular invasion (MVI) in patients with bifocal hepatocellular carcinoma (HCC). MATERIALS AND METHODS Between January 2015 and September 2015, 51 patients with two HCC lesions were included. All patients underwent conventional magnetic resonance imaging including diffusion-weighted imaging (DWI) before the HCC lesions were surgically resected; the tumor specimens were examined histopathologically. Similarity between two HCC lesions regarding DWI signal intensity (SI) and ADC value was calculated as the difference between the two lesions: Value Similarity = [1-(|valuelarge lesion-valuesmall lesion|)/(valuelarge lesion + valuesmall lesion)] × 100%. Univariate and multivariate logistic regression analyses were performed to assess the presence of MVI. RESULTS Risk factors significantly related to MVI of bifocal HCC in univariate analysis were cirrhosis (P = 0.010), histological grade (P = 0.040), DWI SI similarity (P = 0.027) and ADC similarity (P = 0.003). In multivariate analysis, cirrhosis (odds ratio 0.068, P = 0.022) and ADC similarity (odds ratio 1.204, P = 0.008) were independent risk factors for MVI of bifocal HCC. CONCLUSION In patients with two HCC lesions, highly similar ADC values for the two HCC lesions may be a preoperative predictor of MVI.
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Affiliation(s)
- Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Heqing Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Yibo Tang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Shengxiang Rao
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Ruofan Sheng
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
- Shanghai Institute of Medical Imaging, Shanghai, China.
- Department of Medical Imaging, Shanghai Medical College, Fudan University, Shanghai, China.
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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: 106] [Impact Index Per Article: 15.1] [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.
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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
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Jue C, Zhifeng W, Zhisheng Z, Lin C, Yayun Q, Feng J, Hao G, Shintaro I, Hisamitsu T, Shiyu G, Yanqing L. Vasculogenic mimicry in hepatocellular carcinoma contributes to portal vein invasion. Oncotarget 2018; 7:77987-77997. [PMID: 27793002 PMCID: PMC5363638 DOI: 10.18632/oncotarget.12867] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 10/12/2016] [Indexed: 01/10/2023] Open
Abstract
Portal vein invasion (PVI) is common in hepatocellular carcinoma (HCC) and largely contributes to tumor recurrence after radical tumor resection or liver transplantation. Vasculogenic mimicry (VM) was an independent vascular system lined with tumor cells and associated with poor prognosis of HCC. The present study was conducted to evaluate the relationship between VM and portal vein invasion. A total of 44 HCC cases receiving anatomic liver resection were included in the study and were divided into groups with and without PVI. The prevalence of VM in each group was examined by CD34-PAS dual staining. The regulatory molecules of VM formation such as Notch1, Vimentin and matrix metalloproteinases (MMPs) were investigated by immunohistochemical staining. Analysis was performed to explore the association of PVI, VM and the VM regulatory molecules. PVI was found in 40.91% (18/44) cases and VM was found in 38.64% (17/44) cases in total samples. The incidence of VM was 72.22% (13/18) in PVI group while it was 15.38% (4/26) in non-PVI group (P<0.001), VM formation was positively correlated with PVI (r=0.574, P<0.001). The VM forming regulatory molecules such as Notch1, Vimentin, MMP-2 and MMP-9 were found to be correlated with PVI in HCC patients. Taken together, our results suggested that VM formation, alone with its regulatory molecules, is the promoting factor of PVI in hepatocellular carcinoma.
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Affiliation(s)
- Chen Jue
- Institution of Integrated Traditional Chinese and Western Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China.,Department of Oncology, The Second People's Hospital of Taizhou Affiliated to Yangzhou University, Taizhou, Jiangsu, China.,Department of Physiology, School of Medicine, Showa University, Tokyo, Japan
| | - Wu Zhifeng
- Department of Oncology, Zhongshan Hospital Affiliated to Fudan University, Shanghai, China
| | - Zhang Zhisheng
- Department of Oncology, The Second People's Hospital of Taizhou Affiliated to Yangzhou University, Taizhou, Jiangsu, China
| | - Cui Lin
- Department of Oncology, The Second People's Hospital of Taizhou Affiliated to Yangzhou University, Taizhou, Jiangsu, China
| | - Qian Yayun
- Institution of Integrated Traditional Chinese and Western Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China
| | - Jin Feng
- Institution of Integrated Traditional Chinese and Western Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China
| | - Gu Hao
- Institution of Integrated Traditional Chinese and Western Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China
| | - Ishikawa Shintaro
- Department of Physiology, School of Medicine, Showa University, Tokyo, Japan
| | - Tadashi Hisamitsu
- Department of Physiology, School of Medicine, Showa University, Tokyo, Japan
| | - Guo Shiyu
- Department of Physiology, School of Medicine, Showa University, Tokyo, Japan
| | - Liu Yanqing
- Institution of Integrated Traditional Chinese and Western Medicine, Medical College, Yangzhou University, Yangzhou, Jiangsu, China
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Hu H, Zheng Q, Huang Y, Huang XW, Lai ZC, Liu J, Xie X, Feng ST, Wang W, Lu MD. A non-smooth tumor margin on preoperative imaging assesses microvascular invasion of hepatocellular carcinoma: A systematic review and meta-analysis. Sci Rep 2017; 7:15375. [PMID: 29133822 PMCID: PMC5684346 DOI: 10.1038/s41598-017-15491-6] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Accepted: 10/27/2017] [Indexed: 12/16/2022] Open
Abstract
Microvascular invasion (MVI) is rarely diagnosed preoperatively in hepatocellular carcinoma (HCC). The aim of this meta-analysis is to assess the diagnostic power of a non-smooth tumor margin on preoperative imaging for MVI. We performed a literature search using the PubMed, Embase and Cochrane Library databases, and 11 studies were included involving 618 MVI-positive cases and 1030 MVI-negative cases. Considerable heterogeneity was found, and was indicated to be attributable to the mean patient ages in the included studies. In subgroups of studies with a mean patient age older than 60 years and studies with computed tomography (CT) as the imaging method (as opposed to magnetic resonance imaging (MRI)), heterogeneity was low, and the diagnostic odds ratio (DOR) of the single two-dimensional imaging feature for MVI was 21.30 (95% CI [12.52, 36.23]) and 28.78 (95% CI [13.92, 59.36]), respectively; this power was equivalent to or greater than that of certain multivariable-based scoring systems. In conclusion, a non-smooth tumor margin on preoperative imaging is of great value for MVI assessment and should be considered for inclusion in future scoring systems.
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Affiliation(s)
- HangTong Hu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Qiao Zheng
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yang Huang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xiao Wen Huang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhi Cheng Lai
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - JingYa Liu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - XiaoYan Xie
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Shi Ting Feng
- Department of Radiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Wei Wang
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Ming De Lu
- Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.,Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Lee S, Kim SH, Lee JE, Sinn DH, Park CK. Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma. J Hepatol 2017; 67:526-534. [PMID: 28483680 DOI: 10.1016/j.jhep.2017.04.024] [Citation(s) in RCA: 328] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 03/22/2017] [Accepted: 04/19/2017] [Indexed: 12/13/2022]
Abstract
BACKGROUND & AIMS This study aimed to identify preoperative magnetic resonance (MR) imaging biomarkers for predicting microvascular invasion (MVI), to determine their diagnostic performance and to evaluate whether they are associated with early recurrence after surgery for single hepatocellular carcinoma (HCC). METHODS The study included 197 patients with surgically resected HCC (≤5cm) who underwent preoperative gadoxetic acid-enhanced MR imaging. Significant MR imaging findings for predicting MVI were identified by univariate and multivariate analyses. Early recurrence rates (<2years) were analyzed with respect to significant imaging findings for predicting MVI. RESULTS Three MR imaging features were independently associated with MVI: arterial peritumoral enhancement (odds ratio [OR]=5.184; 95% confidence interval [CI]: 2.228, 12.063; p<0.001), non-smooth tumor margin (OR=3.555; 95% CI: 1.627, 7.769; p=0.001), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR=4.705; 95% CI: 1.671, 13.246; p=0.003). When two of three findings were combined, the specificity was 92.5% (124/134). When all three findings were satisfied, the specificity was 99.3% (133/134). Early recurrence rates were significantly higher in patients with single HCC, with two or three significant MR imaging findings, compared to those with none (27.9% vs. 12.6%, respectively, p=0.030). CONCLUSIONS A combination of two or more of the following; arterial peritumoral enhancement, non-smooth tumor margin, and peritumoral hypointensity on HBP, can be used as a preoperative imaging biomarker for predicting MVI, with specificity >90%, and is associated with early recurrence after surgery of single HCC. Lay summary: A combination of two or more of the following; arterial peritumoral enhancement, non-smooth tumor margin, and peritumoral hypointensity on hepatobiliary phase, can be used as a preoperative imaging biomarker for predicting microvascular invasion, with specificity >90%, and is associated with early recurrence after curative resection of single HCC.
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Affiliation(s)
- Sunyoung Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, Republic of Korea
| | - Seong Hyun Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, Republic of Korea.
| | - Ji Eun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, Republic of Korea
| | - Dong Hyun Sinn
- Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea, 81 Ilwon-Ro, Gangnam-gu, Seoul, Republic of Korea
| | - Cheol Keun Park
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea, 81 Ilwon-Ro, Gangnam-gu, Seoul, Republic of Korea
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Ahn SY, Lee JM, Joo I, Lee ES, Lee SJ, Cheon GJ, Han JK, Choi BI. Prediction of microvascular invasion of hepatocellular carcinoma using gadoxetic acid-enhanced MR and (18)F-FDG PET/CT. ACTA ACUST UNITED AC 2015; 40:843-51. [PMID: 25253426 DOI: 10.1007/s00261-014-0256-0] [Citation(s) in RCA: 95] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE To identify the gadoxetic acid-enhanced MR and the (18)F-fludeoxyglucose (FDG) PET/CT findings associated with microvascular invasion (MVI) of hepatocellular carcinoma (HCC) in patients who are undergoing liver transplantation (LT). METHODS Fifty-one patients with 78 HCCs underwent LT. Preoperative MRI and (18)F-FDG PET/CT findings were retrospectively analyzed and the association of the imaging findings with MVI was assessed. RESULTS Univariate analysis revealed that hypointensity seen on T1WI (OR = 4.329, p = 0.011), peritumoral enhancement (OR = 7.000, p = 0.008), inhomogeneity on arterial phase (OR = 4.321, p = 0.011), delayed phase (OR = 4.519, p = 0.009) or hepatobiliary phase (OR = 3.564, p = 0.032), and the large tumor size (>5 cm) (OR = 12.091, p = 0.001) showed statistically significant associations with MVI. The ratio of tumor maximum standardized uptake value (SUV) to normal liver mean SUV (TSUVmax/LSUVmean) (2.05 ± 1.43 vs. 1.08 ± 0.37) revealed significantly higher value in the MVI-positive group. Multivariate analysis revealed that peritumoral enhancement and a TSUVmax/LSUVmean of 1.2 or greater had a statistically significant association with MVI, with odds ratios of 10.648 (p = 0.016) and 14.218 (p = 0.001), respectively. CONCLUSIONS Preoperative imaging findings such as peritumoral enhancement seen on gadoxetic acid-enhanced MR and a TSUVmax/LSUVmean of 1.2 or more on (18)F-FDG PET/CT, may suggest the presence of MVI in HCC patients.
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Affiliation(s)
- Su Yeon Ahn
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 110-744, Korea
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Renzulli M, Brocchi S, Cucchetti A, Mazzotti F, Mosconi C, Sportoletti C, Brandi G, Pinna AD, Golfieri R. Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of Hepatocellular Carcinoma? Radiology 2015; 279:432-42. [PMID: 26653683 DOI: 10.1148/radiol.2015150998] [Citation(s) in RCA: 279] [Impact Index Per Article: 27.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE To determine the accuracy of imaging features, such as tumor dimension, multinodularity, nonsmooth tumor margins, peritumoral enhancement, and radiogenomic algorithm based on the association between imaging features (internal arteries and hypoattenuating halos) and gene expression that the authors called two-trait predictor of venous invasion (TTPVI), in the prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). MATERIALS AND METHODS This single-center retrospective study was approved by the institutional review board, and the requirement for informed consent was waived. One hundred twenty-five patients (median age, 63 years; interquartile range, 53-71 years) with a diagnosis of HCC and indications for hepatic resection were included. Two observers independently reviewed radiologic images to evaluate the following features for MVI: maximum diameter, number of lesions, tumor margins, TTPVI, and peritumoral enhancement. Interobserver agreement was checked, and diagnostic accuracy of radiologic features was investigated. RESULTS The total number of HCC nodules was 140. Large tumor size, nonsmooth tumor margins, TTPVI, and peritumoral enhancement were significantly related to the presence of MVI (P < .05 in all cases and for both observers). Multinodularity was not significantly related (P = .158). Moreover, the diagnostic accuracy of the three "worrisome" radiologic features (nonsmooth tumor margins, peritumoral enhancement, and TTPVI) was associated with tumor size: The negative predictive value of the absence of worrisome features decreased from 0.84 for observer 1 and 0.91 for observer 2 for tumors smaller than 2 cm to 0.56 and 0.71, respectively, for tumors larger than 5 cm, whereas the presence of all three worrisome features returned to a positive predictive value of 0.95 for observer 1 and 0.96 for observer 2 independent of tumor size, with no significant interobserver differences (P > .10). CONCLUSION "Worrisome" imaging features, such as tumor dimension, nonsmooth tumor margins, peritumoral enhancement, and TTPVI, have high accuracy in the prediction of MVI in HCC.
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Affiliation(s)
- Matteo Renzulli
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Stefano Brocchi
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Alessandro Cucchetti
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Federico Mazzotti
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Cristina Mosconi
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Camilla Sportoletti
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Giovanni Brandi
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Antonio Daniele Pinna
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
| | - Rita Golfieri
- From the Radiology Unit, Department of Diagnostic Medicine and Prevention (M.R., S.B., C.M., C.S., R.G.), Department of Medical and Surgical Sciences (A.C., F.M., A.D.P.), and Department of Specialized, Experimental and Diagnostic Medicine (G.B.), S. Orsola-Malpighi Hospital, University of Bologna, Via Albertoni 15, 40138 Bologna, Italy
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Chevallier P, Baudin G, Anty R, Guibal A, Chassang M, Avril L, Tran A. Treatment of hepatocellular carcinomas by thermal ablation and hepatic transarterial chemoembolization. Diagn Interv Imaging 2015; 96:637-46. [DOI: 10.1016/j.diii.2015.04.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Accepted: 04/13/2015] [Indexed: 12/15/2022]
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Cho ES, Choi JY. MRI features of hepatocellular carcinoma related to biologic behavior. Korean J Radiol 2015; 16:449-64. [PMID: 25995679 PMCID: PMC4435980 DOI: 10.3348/kjr.2015.16.3.449] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Accepted: 02/23/2015] [Indexed: 12/12/2022] Open
Abstract
Imaging studies including magnetic resonance imaging (MRI) play a crucial role in the diagnosis and staging of hepatocellular carcinoma (HCC). Several recent studies reveal a large number of MRI features related to the prognosis of HCC. In this review, we discuss various MRI features of HCC and their implications for the diagnosis and prognosis as imaging biomarkers. As a whole, the favorable MRI findings of HCC are small size, encapsulation, intralesional fat, high apparent diffusion coefficient (ADC) value, and smooth margins or hyperintensity on the hepatobiliary phase of gadoxetic acid-enhanced MRI. Unfavorable findings include large size, multifocality, low ADC value, non-smooth margins or hypointensity on hepatobiliary phase images. MRI findings are potential imaging biomarkers in patients with HCC.
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Affiliation(s)
- Eun-Suk Cho
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 135-720, Korea
| | - Jin-Young Choi
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul 120-752, Korea
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Prediction of microvascular invasion of hepatocellular carcinomas with gadoxetic acid-enhanced MR imaging: Impact of intra-tumoral fat detected on chemical-shift images. Eur J Radiol 2015; 84:1036-43. [PMID: 25818729 DOI: 10.1016/j.ejrad.2015.03.002] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Revised: 02/26/2015] [Accepted: 03/02/2015] [Indexed: 02/01/2023]
Abstract
PURPOSE To investigate the impact of intra-tumoral fat detected by chemical-shift MR imaging in predicting the MVI of HCC. MATERIALS AND METHODS Gadoxetic acid-enhanced MR imaging of 365 surgically proven HCCs from 365 patients (306 men, 59 women; mean age, 55.6 years) were evaluated. HCCs were classified into two groups, fat-containing and non-fat-containing, based on the presence of fat on chemical-shift images. Fat-containing HCCs were subdivided into diffuse or focal fatty change groups. Logistic regression analyses were used to identify clinical and MR findings associated with MVI. RESULTS Based on MR imaging, 66 tumors were classified as fat-containing HCCs and 299 as non-fat-containing HCCs. Among the 66 fat-containing HCCs, 38 (57.6%) showed diffuse fatty changes and 28 (42.4%) showed focal fatty changes. MVI was present in 18 (27.3%) fat-containing HCCs and in 117 (39.1%) non-fat-containing HCCs (P=0.07). Univariate analysis revealed that serum alpha-fetoprotein (AFP) and tumor size were significantly associated with MVI (P<0.001). A multiple logistic regression analysis showed that log AFP (odds ratio 1.178, P=0.0016), tumor size (odds ratio 1.809, P<0.001), and intra-tumoral fat (odds ratio 0.515, P=0.0387) were independent variables associated with MVI. CONCLUSION Intra-tumoral fat detected with MR imaging may suggest lower risk for MVI of HCC and, therefore, a possibly more favorable prognosis, but the clinical value of this finding is uncertain.
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An C, Kim DW, Park YN, Chung YE, Rhee H, Kim MJ. Single Hepatocellular Carcinoma: Preoperative MR Imaging to Predict Early Recurrence after Curative Resection. Radiology 2015; 276:433-43. [PMID: 25751229 DOI: 10.1148/radiol.15142394] [Citation(s) in RCA: 169] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To identify magnetic resonance (MR) imaging features that enable prediction of early recurrence (<2 years) after curative resection of hepatocellular carcinoma (HCC) and to derive a preoperative prediction model. MATERIALS AND METHODS This retrospective study was approved by the institutional review board. The requirement to obtain written informed consent was waived. A total of 268 patients who underwent hepatic resection for a single HCC from January 2008 to August 2011 were divided into two cohorts: a training cohort, which was used to derive a prediction model (n = 187), and a validation cohort (n = 81). All MR images from the training cohort were reviewed by two radiologists. A prediction model was constructed by using MR imaging features that were independently associated with early recurrence with use of multiple logistic regression analysis. The performance of the prediction model in the validation cohort was evaluated with respect to discrimination (ie, whether the relative ranking of individual predictions of subsequent early recurrence is in the correct order). RESULTS In the training cohort, four MR imaging features were independently associated with early recurrence: rim enhancement (odds ratio [OR] = 3.83; 95% confidence interval [CI]: 1.39, 10.52), peritumoral parenchymal enhancement in the arterial phase (OR = 2.64; 95% CI: 1.27, 5.46), satellite nodule (OR = 4.07; 95% CI: 1.09, 15.21), and tumor size (OR = 1.66; 95% CI: 1.31, 2.09). A prediction model derived from these variables showed an area under the receiver operating characteristic curve (AUC) of 0.788 in the prediction of the risk of early recurrence in the training cohort. When applied to the validation cohort, this model showed good discrimination (AUC, 0.783). CONCLUSION The prediction model derived from rim enhancement, peritumoral parenchymal enhancement, satellite nodule, and tumor size can be used preoperatively to estimate the risk of early recurrence after resection of a single HCC.
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Affiliation(s)
- Chansik An
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
| | - Dong Wook Kim
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
| | - Young-Nyun Park
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
| | - Yong Eun Chung
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
| | - Hyungjin Rhee
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
| | - Myeong-Jin Kim
- From the Department of Radiology, Research Institute of Radiological Science (C.A., Y.E.C., H.R., M.J.K.), and Department of Pathology (Y.N.P.), Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-Ro, Seodaemun-Gu, Seoul 120-752, South Korea; and Department of Policy Research Affairs, National Health Insurance Corporation Ilsan Hospital, Goyang, Korea (D.W.K.)
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Ronot M, Vilgrain V. Hepatocellular carcinoma: diagnostic criteria by imaging techniques. Best Pract Res Clin Gastroenterol 2014; 28:795-812. [PMID: 25260309 DOI: 10.1016/j.bpg.2014.08.005] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Revised: 07/12/2014] [Accepted: 08/15/2014] [Indexed: 01/31/2023]
Abstract
Imaging plays a very important role in the diagnosis of HCC. Indeed, in high-risk patients a noninvasive diagnosis can only be obtained by imaging in presence of typical features. These features include arterial enhancement followed by washout during the portal venous and/or delayed phases on CT scan or MRI. This pattern is quite specific and has been endorsed by both Western and Asian diagnostic guidelines. However, its sensitivity is not very high, especially for small lesions. Therefore ancillary signs may be needed to increase the reliability of the diagnosis. Recent hepatobiliary MRI contrast agents seem to be interesting to improve characterization of small nodules in the cirrhotic liver.
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Affiliation(s)
- Maxime Ronot
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, Hauts-de-Seine, France; University Paris Diderot, Sorbonne Paris Cité, Paris, France; INSERM U1149, centre de recherche biomédicale Bichat-Beaujon, CRB3, Paris, France.
| | - Valérie Vilgrain
- Department of Radiology, APHP, University Hospitals Paris Nord Val de Seine, Beaujon, Clichy, Hauts-de-Seine, France; University Paris Diderot, Sorbonne Paris Cité, Paris, France; INSERM U1149, centre de recherche biomédicale Bichat-Beaujon, CRB3, Paris, France
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C-reactive protein may be a prognostic factor in hepatocellular carcinoma with malignant portal vein invasion. World J Surg Oncol 2013; 11:92. [PMID: 23618082 PMCID: PMC3644266 DOI: 10.1186/1477-7819-11-92] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2012] [Accepted: 03/26/2013] [Indexed: 02/07/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) has a high predilection for portal vein invasion, and the prognosis of HCC with malignant portal vein invasion is extremely poor. The objective of this study was to investigate the outcomes and the prognostic factor of recurrence in HCC patients with malignant portal vein invasion. Methods We retrospectively reviewed the clinicopathologic data and outcomes of 83 HCC patients with malignant portal vein invasion and 1,056 patients without portal vein invasion who underwent liver resection. Results Increased serum alkaline phosphatase (ALP) levels, increased maximum tumor size, and intrahepatic metastasis were predisposing factors for malignant portal vein invasion by multivariate analysis. The median disease-free survival and overall survival of HCC patients with malignant portal vein invasion was 4.5 months and 25 months, respectively. The 1-year, 2-year, and 3-year disease-free survival rates were 30.6%, 26.1%, and 21.2%, respectively, and the overall survival rates for HCC patients with malignant portal vein invasion were 68.6%, 54.2%, and 41.6%, respectively. The initial detection site was the lung in HCC patients with portal vein invasion and the liver in HCC patients without portal vein invasion. C-reactive protein (CRP) was a significant independent predictor of tumor recurrence in HCC with malignant portal vein invasion after surgery. Conclusions Increased ALP levels, increased maximum tumor size, and intrahepatic metastasis were independent predictors of malignant portal vein invasion in HCC. CRP level was closely associated with the predisposing factor of tumor recurrence in HCC patients with malignant portal vein invasion after a surgical resection, and lung metastasis was common.
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Chang IS, Shin SW, Cho SK, Rhim H, Choi D, Park KB, Park HS, Choo SW, Do YS, Choo IW. Evolution of portal vein tumor thromboses in patients with hepatocellular carcinoma: CT findings and transition of serum tumor markers. Clin Imaging 2012; 36:489-95. [DOI: 10.1016/j.clinimag.2011.11.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2011] [Accepted: 11/21/2011] [Indexed: 01/09/2023]
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KANNO KIMINORI, KANNO SHOJI, NITTA HIROYUKI, UESUGI NORIYUKI, SUGAI TAMOSTU, MASUDA TOMOYUKI, WAKABAYASHI GO, MAESAWA CHIHAYA. Overexpression of histone deacetylase 6 contributes to accelerated migration and invasion activity of hepatocellular carcinoma cells. Oncol Rep 2012; 28:867-73. [DOI: 10.3892/or.2012.1898] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2012] [Accepted: 05/18/2012] [Indexed: 11/06/2022] Open
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Yamashita YI, Tsuijita E, Takeishi K, Fujiwara M, Kira S, Mori M, Aishima S, Taketomi A, Shirabe K, Ishida T, Maehara Y. Predictors for microinvasion of small hepatocellular carcinoma ≤ 2 cm. Ann Surg Oncol 2011; 19:2027-34. [PMID: 22203184 DOI: 10.1245/s10434-011-2195-0] [Citation(s) in RCA: 115] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Indexed: 12/15/2022]
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) ≤ 2 cm in diameter is considered to have a low potential for malignancy. METHODS A retrospective review was undertaken of 149 patients with primary solitary HCC ≤ 2 cm who underwent initial hepatic resection between 1994 and 2010. The independent predictors of the microinvasion (MI) such as portal venous, hepatic vein, or bile duct infiltration and/or intrahepatic metastasis were identified by multivariate analysis. Prognosis of patients with HCC ≤ 2 cm accompanied by MI was compared to that of patients with HCC ≤ 2 cm without MI. RESULTS Forty-three patients with HCC ≤ 2 cm had MI in patients (28.9%). Three independent predictors of the MI were revealed: invasive gross type (simple nodular type with extranodular growth or confluent multinodular type), des-γ-carboxy prothrombin (DCP) >100 mAU/ml, and poorly differentiated. Disease-free survival rates of patients with HCC ≤ 2 cm with MI (3 year 44%) were significantly worse than those for HCC ≤ 2 cm without MI (3 year 72%). This disadvantage of disease-free survival rate of patients with HCC ≤ 2 cm with MI could be dissolved by hepatic resection with a wide tumor margin of ≥ 5 mm (P = 0.04). CONCLUSIONS Even in cases of HCC ≤ 2 cm, patients who are suspected of having invasive gross type tumors in preoperative imaging diagnosis or who have a high DCP level (>100 mAU/ml) are at risk for MI. Therefore, in such patients, hepatic resection with a wide tumor margin should be recommended.
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Affiliation(s)
- Yo-ichi Yamashita
- Department of Surgery, Hiroshima Red Cross Hospital and Atomic Bomb Survivors Hospital, Hiroshima, Japan.
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A non-smooth tumor margin in the hepatobiliary phase of gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging predicts microscopic portal vein invasion, intrahepatic metastasis, and early recurrence after hepatectomy in patients with hepatocellular carcinoma. JOURNAL OF HEPATO-BILIARY-PANCREATIC SCIENCES 2011; 18:575-85. [PMID: 21360083 DOI: 10.1007/s00534-010-0369-y] [Citation(s) in RCA: 132] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
BACKGROUND The value of the hepatobiliary phase of gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) in patients with hepatocellular carcinoma (HCC) has not been evaluated in detail. METHODS Between 2008 and 2009, 61 patients with HCC within the Milan criteria underwent Gd-EOB-DTPA-enhanced MRI and hepatectomy. The tumor margin was determined preoperatively based on hepatobiliary phase images. Microscopic portal vein invasion (MPVI), intrahepatic metastasis (IM), and recurrence of HCC within 1 year after hepatectomy were evaluated in 24 patients with non-smooth margins at the periphery of the tumor and 37 patients with smooth margins. RESULTS The number of patients with MPVI and IM of HCC was significantly higher among those with non-smooth margins (42 and 38%, respectively) than among those with smooth margins (3%; p = 0.0002 and 5%; p = 0.0042, respectively). A non-smooth margin was identified as a significant predictor of MPVI (odds ratio 18.814, p = 0.024) and IM (odds ratio 6.498, p = 0.036) of HCC on multivariate analysis. Furthermore, a non-smooth margin was identified as a significant predictor of recurrence within 1 year after hepatectomy (odds ratio 4.306, p = 0.04) on multivariate analysis. CONCLUSIONS A non-smooth tumor margin in the hepatobiliary phase of Gd-EOB-DTPA-enhanced MRI is useful to predict MPVI, IM, and early recurrence of HCC after hepatectomy.
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Kim MJ, Lee M, Choi JY, Park YN. Imaging features of small hepatocellular carcinomas with microvascular invasion on gadoxetic acid-enhanced MR imaging. Eur J Radiol 2011; 81:2507-12. [PMID: 22137613 DOI: 10.1016/j.ejrad.2011.11.014] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2011] [Revised: 11/02/2011] [Accepted: 11/03/2011] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Detection of hepatocellular carcinomas (HCCs) before microvascular invasion (MVI) occurs is important due to the poor outcomes associated with MVI. We retrospectively investigated the imaging features of small HCCs with MVI on gadoxetic acid-enhanced MR imaging. METHODS Fifty patients (40 men and 10 women; mean age, 54 years) with 58 surgically proven small (2 cm or less) HCCs were evaluated by gadoxetic acid-enhanced MRI. Signal intensities on imaging sequences and the presence of the typical dynamic enhancement pattern (arterial enhancement and washout) were assessed. Fisher's exact tests were performed to evaluate the relationships between the presence of MVI, tumor size, and imaging findings. RESULTS None of the 12 small HCCs with diameters of 1cm or less had MVI, while 15 (33%) of the 46 small HCCs with diameters of 1.1-2.0 cm had MVI (p=0.025, Fisher's exact test). Among the small HCCs with diameters of 1.1-2.0 cm, all HCCs with MVI showed the typical dynamic pattern and hyperintensity on T2- and diffusion-weighted images. Most HCCs (54 lesions, 93%) were hypointense on hepatobiliary phase images regardless of the presence of MVI. CONCLUSIONS All small HCCs with MVI showed typical dynamic pattern and hyperintensity on T2-weighted and diffusion-weighted images, while atypical dynamic pattern and size of less than 1cm in diameter may suggest absence of MVI.
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Affiliation(s)
- Myeong-Jin Kim
- Department of Radiology and Research Institute of Radiological Science, Yonsei University Severance Hospital, Seoul, South Korea.
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Kim KA, Kim MJ, Jeon HM, Kim KS, Choi JS, Ahn SH, Cha SJ, Chung YE. Prediction of microvascular invasion of hepatocellular carcinoma: usefulness of peritumoral hypointensity seen on gadoxetate disodium-enhanced hepatobiliary phase images. J Magn Reson Imaging 2011; 35:629-34. [PMID: 22069244 DOI: 10.1002/jmri.22876] [Citation(s) in RCA: 152] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2011] [Accepted: 10/06/2011] [Indexed: 02/06/2023] Open
Abstract
PURPOSE To determine whether peritumoral hypointensity seen on hepatobiliary phase images of preoperative gadoxetate disodium-enhanced magnetic resonance imaging (EOB-MRI) is useful for predicting microvascular invasion of hepatocellular carcinoma (HCC). MATERIALS AND METHODS This study was approved by the Institutional Review Board. In all, 104 HCC masses in 104 patients who had undergone EOB-MRI and liver surgery within 1 month after EOB-MRI were evaluated. Two radiologists independently recorded the presence of a peritumoral hypointensity on hepatobiliary phase. Interobserver agreement was assessed and consensus records were used. Tumor size was measured. A chi-square test and independent t-test were used for univariate analysis. Multiple logistic regression was performed to determine factors for predicting microvascular invasion. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of peritumoral hypointensity were calculated. RESULTS Sixty HCCs had microvascular invasion and 44 did not. Interobserver agreement in determining peritumoral hypointensity was excellent (κ = 0.83). By univariate analysis, peritumoral hypointensity and tumor size were significant for predicting microvascular invasion of HCC. On multiple logistic regression analysis, only peritumoral hypointensity was significant in predicting microvascular invasion of HCC (P = 0.013). The sensitivity, specificity, PPV, and NPV of peritumoral hypointensity were 38.3%, 93.2%, 88.5%, and 52.6%, respectively. CONCLUSION Peritumoral hypointensity on the hepatobiliary phase of EOB-MRI is not sensitive but has high specificity for predicting microvascular invasion of HCC.
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Affiliation(s)
- Kyung Ah Kim
- Department of Radiology, Yonsei University College of Medicine, Seoul, Korea
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Chou CT, Chen RC, Lee CW, Ko CJ, Wu HK, Chen YL. Prediction of microvascular invasion of hepatocellular carcinoma by pre-operative CT imaging. Br J Radiol 2011; 85:778-83. [PMID: 21828149 DOI: 10.1259/bjr/65897774] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE The aim of this study was to diagnose microvascular invasion in patients with solitary hepatocellular carcinoma (HCC) from pre-operative CT imaging. METHODS 102 patients with solitary HCC who underwent curative hepatectomy were retrospectively included in our study. The pre-operative 3-phase CT imaging and laboratory data for the 102 patients were reviewed. Tumour size, tumour margin, peritumoral enhancement and α-fetoprotein level were assessed. Surgical pathology was reviewed; tumour differentiation, liver fibrosis score and microvascular invasion were recorded. RESULTS The histopathological results revealed that 50 HCCs were positive and the other 52 were negative for microvascular invasion. Univariate analysis revealed that tumour size (p = 0.036), higher Edmondson-Steiner grade (p = 0.047) and non-smooth tumour margin (p < 0.001) showed statistically significant associations with microvascular invasion. Multivariate logistic regression analysis showed that non-smooth tumour margin had a statistically significant association with microvascular invasion only (p < 0.001). The sensitivity, specificity, positive predictive value and negative predictive value of the non-smooth tumour margin in the prediction of microvascular invasion were 66%, 86.5%, 82.5% and 72.6%, respectively. CONCLUSION Non-smooth tumour margin in pre-operative CT had a statistically significant association with microvascular invasion. More aggressive treatment should be considered in HCC patients with suspected positive microvascular invasion.
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Affiliation(s)
- C-T Chou
- Department of Radiology, Chang-Hua Christian Hospital, Chang-Hua City, Taiwan.
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