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Akabane M, Imaoka Y, Kawashima J, Pawlik TM. Advancing precision medicine in hepatocellular carcinoma: current challenges and future directions in liquid biopsy, immune microenvironment, single nucleotide polymorphisms, and conversion therapy. Hepat Oncol 2025; 12:2493457. [PMID: 40260687 PMCID: PMC12026093 DOI: 10.1080/20450923.2025.2493457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2025] [Accepted: 04/11/2025] [Indexed: 04/24/2025] Open
Abstract
Hepatocellular carcinoma (HCC) remains a health concern characterized by heterogeneity and high mortality. Surgical resection, radiofrequency ablation, trans-arterial chemoembolization, and liver transplantation offer potentially curative treatments for early-stage disease, but recurrence remains high. Most patients present with advanced-stage HCC, where locoregional therapies are less effective, and systemic treatments-primarily multi-kinase inhibitors and immune checkpoint inhibitors-often yield limited responses. Precision medicine aims to tailor therapy to molecular and genetic profiles, yet its adoption in HCC is hindered by inter-/intra-tumoral heterogeneity and limited biopsy availability. Advances in molecular diagnostics support reintroducing tissue sampling to better characterize genetic, epigenetic, and immunological features. Liquid biopsy offers a minimally invasive method for capturing real-time tumor evolution, overcoming spatial and temporal heterogeneity. Artificial intelligence and machine learning are revolutionizing biomarker discovery, risk stratification, and treatment planning by integrating multi-omics data. Immunological factors such as tumor-infiltrating lymphocytes, natural killer cells, macrophages, and fibroblasts have emerged as determinants of HCC progression and treatment response. Conversion therapy-combining systemic agents with locoregional treatments-has showndemonstrated promise in downstaging unresectable HCC. Ongoing efforts to refine biomarker-driven approaches and optimize multi-modality regimens underscore precision medicine's potential to improve outcomes. PubMed (January 2002-February 2025) was searched for relevant studies.
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Affiliation(s)
- Miho Akabane
- Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Yuki Imaoka
- Division of Abdominal Transplant, Department of Surgery, Stanford University, CA, USA
| | - Jun Kawashima
- Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
| | - Timothy M. Pawlik
- Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA
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Li Q, Chang X, Gu J, Yang Y, Ouyang J, Zhou Y, Zhao H, Zhou J. Adjuvant Transarterial Chemoembolization in Resected Macrotrabecular-massive Hepatocellular Carcinoma (ATAC-MACRO): A Multicenter Real-world Retrospective Study. Acad Radiol 2025; 32:2585-2595. [PMID: 39848885 DOI: 10.1016/j.acra.2024.12.053] [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: 08/23/2024] [Revised: 12/08/2024] [Accepted: 12/22/2024] [Indexed: 01/25/2025]
Abstract
RATIONALE AND OBJECTIVES The purpose of this study was to demonstrate the impact of postoperative adjuvant transarterial chemoembolization (TACE) on the prognosis of patients with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC). MATERIALS AND METHODS This retrospective study used the clinical records of patients with resected MTM-HCC with/without adjuvant TACE at three centers between January 2015 and December 2022. The primary end point was recurrence free survival (RFS). The secondary end points were overall survival (OS) and safety. RESULTS A total of 559 eligible patients were classified into the adjuvant TACE group and the observation group. After propensity score matching analysis, both RFS (HR 0.62 [95% CI, 0.48 to 0.80]; P < 0.001) and OS (HR 0.59 [95% CI, 0.42 to 0.84]; P = 0.013) in the adjuvant TACE group were significantly better than the observation group. By Cox regression models, mALBI grade, types of hepatectomy, number, satellite lesion, without adjuvant TACE were identified as independent risk factors for RFS, and mALBI grade, number, maximum tumor size, satellite lesion, microvascular invasion, high AFP level, without adjuvant TACE were identified as independent risk factors for OS. The incidence of surgery-related adverse events (AEs) had no significant difference between the two groups (P = 0.609). The majority of AEs associated with adjuvant TACE were grade I (84.4%), and no treatment-related deaths occurred in either group. CONCLUSIONS Adjuvant TACE significantly improved the RFS and OS of patients with resected MTM-HCC with acceptable toxicity.
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Affiliation(s)
- Qingjun Li
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China (Q.L., J.O., Y.Z., J.Z.)
| | - Xu Chang
- Department of Interventional Therapy II, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China (X.C.)
| | - Jiaye Gu
- School of Ophthalmology & Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China (J.G.)
| | - Yi Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (Y.Y., H.Z.)
| | - Jingzhong Ouyang
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China (Q.L., J.O., Y.Z., J.Z.)
| | - Yanzhao Zhou
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China (Q.L., J.O., Y.Z., J.Z.)
| | - Hong Zhao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (Y.Y., H.Z.)
| | - Jinxue Zhou
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China (Q.L., J.O., Y.Z., J.Z.).
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Zhou XQ, Huang S, Shi XM, Liu S, Zhang W, Shi L, Lv MH, Tang XW. Global trends in artificial intelligence applications in liver disease over seventeen years. World J Hepatol 2025; 17:101721. [PMID: 40177211 PMCID: PMC11959664 DOI: 10.4254/wjh.v17.i3.101721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Revised: 01/01/2025] [Accepted: 02/10/2025] [Indexed: 03/26/2025] Open
Abstract
BACKGROUND In recent years, the utilization of artificial intelligence (AI) technology has gained prominence in the field of liver disease. AIM To analyzes AI research in the field of liver disease, summarizes the current research status and identifies hot spots. METHODS We searched the Web of Science Core Collection database for all articles and reviews on hepatopathy and AI. The time spans from January 2007 to August 2023. We included 4051 studies for further collection of information, including authors, countries, institutions, publication years, keywords and references. VOS viewer, CiteSpace, R 4.3.1 and Scimago Graphica were used to visualize the results. RESULTS A total of 4051 articles were analyzed. China was the leading contributor, with 1568 publications, while the United States had the most international collaborations. The most productive institutions and journals were the Chinese Academy of Sciences and Frontiers in Oncology. Keywords co-occurrence analysis can be roughly summarized into four clusters: Risk prediction, diagnosis, treatment and prognosis of liver diseases. "Machine learning", "deep learning", "convolutional neural network", "CT", and "microvascular infiltration" have been popular research topics in recent years. CONCLUSION AI is widely applied in the risk assessment, diagnosis, treatment, and prognosis of liver diseases, with a shift from invasive to noninvasive treatment approaches.
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Affiliation(s)
- Xue-Qin Zhou
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Shu Huang
- Department of Gastroenterology, Lianshui People' Hospital of Kangda College Affiliated to Nanjing Medical University, Huaian 223499, Jiangsu Province, China
| | - Xia-Min Shi
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Sha Liu
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Wei Zhang
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Lei Shi
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Mu-Han Lv
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
| | - Xiao-Wei Tang
- Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China.
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Hwang YJ, Lee H, Hong SK, Yu SJ, Kim H. Membranous Overexpression of Fibronectin Predicts Microvascular Invasion and Poor Survival Outcomes in Patients with Hepatocellular Carcinoma. Gut Liver 2025; 19:275-285. [PMID: 39778882 PMCID: PMC11907257 DOI: 10.5009/gnl240254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 09/05/2024] [Accepted: 09/06/2024] [Indexed: 01/11/2025] Open
Abstract
Background/Aims Fibronectin (FN) has recently been identified as being overexpressed in patients with hepatocellular carcinoma (HCC) and deemed a promising biomarker of vascular invasion. The aim of this study was to examine the patterns of FN expression in HCC cells and their clinicopathological significance, such as their association with vascular invasion and angiogenesis patterns. Methods Immunohistochemical analysis of FN was conducted using tissue microarrays from 258 surgically resected HCCs and matched nontumorous liver tissues. Three distinct FN expression patterns were observed: cytoplasmic, membranous, and sinusoidal. Moderate or strong expression was considered FN-positive. Results Cytoplasmic or sinusoidal FN expression was significantly more common in HCC cells than in the adjacent liver tissue (p<0.001). FN expression was detected in the membranes of HCC cells and absent in nonneoplastic hepatocytes (p<0.001). Overall survival and disease-free survival in patients with HCC cells with membranous FN expression were significantly shorter than those in patients without membranous FN expression. Membranous FN expression in HCC was significantly associated with high serum alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) levels, infiltrative gross type, poor Edmondson-Steiner grade, major vessel invasion, microvascular invasion, macrotrabecular massive subtype, advanced T stage, and vessel-encapsulating tumor cluster pattern. Sinusoidal pattern of FN expression in HCC was significantly associated with high serum AFP and PIVKA-II levels, infiltrative gross type, large tumor size, microvascular invasion, macrotrabecular massive subtype, and vessel-encapsulating tumor cluster patterns. Conclusions Evaluating FN expression in HCC cells may be useful for identifying aggressive cases of HCC with vascular invasion via biopsy.
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Affiliation(s)
- Yoon Jung Hwang
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
- Department of Pathology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Hyejung Lee
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
| | - Suk Kyun Hong
- Department of Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Su Jong Yu
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine and Biomedical Research Institute, Center for Medical Innovation, Seoul National University Hospital, Seoul, Korea
| | - Haeryoung Kim
- Department of Pathology, Seoul National University College of Medicine, Seoul, Korea
- Department of Pathology, Seoul National University Hospital, Seoul, Korea
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Zheng T, Sheng L, Wu Y, Zhu X, Yang Y, Zhang X, Bashir MR, Ronot M, Sun HC, Wang Y, Song B, Jiang H. Imaging-based prediction of early recurrence and neoadjuvant therapy outcomes for resectable beyond Milan HCC. Eur J Radiol 2025; 184:111945. [PMID: 39874618 DOI: 10.1016/j.ejrad.2025.111945] [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: 08/28/2024] [Revised: 12/29/2024] [Accepted: 01/21/2025] [Indexed: 01/30/2025]
Abstract
PURPOSE To develop and validate an MRI-based model for predicting postoperative early (≤2 years) recurrence-free survival (RFS) in patients receiving upfront surgical resection (SR) for beyond Milan hepatocellular carcinoma (HCC) and to assess the model's performance in separate patients receiving neoadjuvant therapy for similar-stage tumors. METHOD This single-center retrospective study included consecutive patients with resectable BCLC A/B beyond Milan HCC undergoing upfront SR or neoadjuvant therapy. All images were independently evaluated by three blinded radiologists. In patients receiving upfront SR, an MRI-based Early Recurrence Outside Milan (EROM) score was developed and validated for predicting early RFS via Cox regression analyses and compared with the BCLC staging system. In separate patients undergoing neoadjuvant therapy, interval tumor progression rate and postoperative early RFS were compared between EROM-predicted high- and low-risk groups. RESULTS 279 patients (median, 56 years; 236 men) were included, 220 (78.9 %) undergoing upfront SR and 59 (21.1 %) received transarterial chemoembolization-based neoadjuvant therapy. Alpha-fetoprotein > 20 ng/mL (HR, 2.03; P = 0.007), size of the largest tumor (HR, 1.10; P = 0.016), infiltrative appearance (HR, 2.20; P = 0.032), and < 50 % arterial phase hyperenhancement (HR, 1.74; P = 0.023) formed the EROM score, with superior testing dataset C-index than the BCLC system (0.69 vs. 0.52, P < 0.001). The EROM-predicted high-risk (>15.3 points) patients had higher tumor progression (25.0 % vs. 0.0 %, P = 0.033) and lower postoperative 2-year RFS (16.0 % vs. 39.3 %, P = 0.025) rates after neoadjuvant therapy. CONCLUSIONS In patients with resectable beyond Milan HCC, EROM allowed noninvasive prediction of postoperative early RFS and informed interval tumor progression risks after neoadjuvant therapy.
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Affiliation(s)
- Tianying Zheng
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China
| | - Liuji Sheng
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China
| | - Yuanan Wu
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China
| | - Xiaomei Zhu
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China
| | - Yang Yang
- Cancer Center, West China Hospital Sichuan University Chengdu Sichuan China
| | - Xiaoyun Zhang
- Division of Liver Surgery, Department of General Surgery, West China Hospital Sichuan University Chengdu Sichuan China
| | - Mustafa R Bashir
- Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center Durham NC USA
| | - Maxime Ronot
- Université Paris Cité, UMR 1149, CRI, Paris & Service de Radiologie, Hôpital Beaujon, APHP.Nord Clichy France
| | - Hui-Chuan Sun
- Department of Liver Surgery, Liver Cancer Institute and Zhongshan Hospital, Fudan University Shanghai China
| | - Yanshu Wang
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China.
| | - Bin Song
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China; Department of Radiology Sanya People's Hospital Sanya Hainan China.
| | - Hanyu Jiang
- Department of Radiology, West China Hospital Sichuan University Chengdu Sichuan China.
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Chai T, Tong Y, Yu Y, Hu B, Cui GB. Diagnostic Values of Magnetic Resonance Imaging and Computed Tomography for Predicting Macrotrabecular-Massive Hepatocellular Carcinoma Subtype: A Meta-analysis. Acad Radiol 2025:S1076-6332(25)00082-0. [PMID: 39920007 DOI: 10.1016/j.acra.2025.01.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2024] [Revised: 01/20/2025] [Accepted: 01/22/2025] [Indexed: 02/09/2025]
Abstract
BACKGROUND The diagnostic accuracy of magnetic resonance imaging (MRI) vs. computed tomography (CT) for predicting macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is yet to be ascertained. Therefore, this meta-analysis aimed to summarise the diagnostic accuracies of MRI and CT for MTM-HCC. METHODS A comprehensive literature search of PubMed and Embase was conducted up to 20 August 2024, to evaluate the diagnostic performance of MRI and CT for the diagnosis of MTM-HCC. Pooled sensitivity and specificity were calculated for MRI and CT using a bivariate random-effects model. Subgroup analyses based on different covariates were conducted to compare the diagnostic performances of MRI and CT. RESULTS 15 studies involving 2299 patients, including 706 with MTM-HCC and 1593 with non-MTM-HCC were analysed. Comparative analysis revealed no significant differences between MRI and CT in pooled sensitivity (66% vs. 82%, respectively) and specificity (88% vs. 79%, respectively) for the diagnosis of MTM-HCC (P=0.53), with comparable areas under the summary receiver operating characteristic curves of 0.87 and 0.86, respectively. In the subgroup analysis of imaging methods within radiomics, CT had significantly higher sensitivity and specificity than MRI (98% vs. 85% [sensitivity], 83% vs. 79% [specificity], P=0.01). In the other subgroups, including age, the most common aetiology of liver disease, the proportion of patients with cirrhosis, and tumour size, there were no significant differences (all P>0.05). CONCLUSION CT and MRI had comparable predictive performances for the non-invasive diagnosis of MTM-HCC. In the subgroup of radiomics-based imaging methods, CT outperformed MRI. Nevertheless, multicenter prospective studies with uniform design are needed to confirm these findings.
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Affiliation(s)
- Tian Chai
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi Province, China
| | - Yao Tong
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi Province, China
| | - Ying Yu
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi Province, China
| | - Bo Hu
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi Province, China
| | - Guang-Bin Cui
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, Shaanxi Province, China.
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Sangro B, Argemi J, Ronot M, Paradis V, Meyer T, Mazzaferro V, Jepsen P, Golfieri R, Galle P, Dawson L, Reig M. EASL Clinical Practice Guidelines on the management of hepatocellular carcinoma. J Hepatol 2025; 82:315-374. [PMID: 39690085 DOI: 10.1016/j.jhep.2024.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2024] [Accepted: 08/29/2024] [Indexed: 12/19/2024]
Abstract
Liver cancer is the third leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) accounting for approximately 90% of primary liver cancers. Advances in diagnostic and therapeutic tools, along with improved understanding of their application, are transforming patient treatment. Integrating these innovations into clinical practice presents challenges and necessitates guidance. These clinical practice guidelines offer updated advice for managing patients with HCC and provide a comprehensive review of pertinent data. Key updates from the 2018 EASL guidelines include personalised surveillance based on individual risk assessment and the use of new tools, standardisation of liver imaging procedures and diagnostic criteria, use of minimally invasive surgery in complex cases together with updates on the integrated role of liver transplantation, transitions between surgical, locoregional, and systemic therapies, the role of radiation therapies, and the use of combination immunotherapies at various stages of disease. Above all, there is an absolute need for a multiparametric assessment of individual risks and benefits, considering the patient's perspective, by a multidisciplinary team encompassing various specialties.
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Zhou T, Han X, Xiao C, Lei X, Lan X, Wei X, Liang Y, Wu H. Diagnostic accuracy of preoperative MRI in assessing macrotrabecular-massive subtype of hepatocellular carcinoma: a systematic review and meta-analysis. Eur Radiol 2025:10.1007/s00330-024-11344-9. [PMID: 39836200 DOI: 10.1007/s00330-024-11344-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 10/23/2024] [Accepted: 12/08/2024] [Indexed: 01/22/2025]
Abstract
OBJECTIVES To determine the value of preoperative magnetic resonance imaging (MRI) in predicting macrotrabecular-massive hepatocellular carcinoma (MTM-HCC). MATERIALS AND METHODS A search was conducted on PubMed, Web of Science, Cochrane Library databases, and Embase for studies evaluating the performance of MRI in assessing MTM-HCC. The quality assessment of diagnostic studies (QUADAS-2) tool was used to assess the risk of bias. Diagnostic accuracy measures, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR), were pooled. Summary receiver operating characteristic (SROC) curves with the area under the curve (AUC) were generated. Meta-regression analysis was performed to explore potential sources of heterogeneity. RESULTS A total of ten eligible studies including 2074 lesions in 2053 patients were analyzed. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.65 (0.52, 0.76), 0.88 (0.80, 0.94), 5.6 (3.70, 8.60), 0.40 (0.30, 0.53), 14 (10, 20), and 0.84 (0.81, 0.87), respectively. High heterogeneity was observed (I2 was 78.61% and 90.95% for sensitivity and specificity, respectively) along with a threshold effect (Spearman's correlation coefficient = 0.927, p < 0.001). Meta-regression analysis demonstrated that the MRI method (radiomics or non-radiomics) affected the heterogeneity. CONCLUSION MRI has diagnostic value for MTM-HCC due to its higher specificity and moderate sensitivity, but its clinical application remains suboptimal due to significant heterogeneity. Thus, further prospective studies with large sample sizes are needed to confirm these results. KEY POINTS Question What is the value of MRI for preoperatively predicting MTM-HCC? Findings Meta-regression analyses revealed that the MRI method (radiomics or non-radiomics) is a significant factor contributing to heterogeneity. Clinical relevance This study demonstrates the high diagnostic accuracy of MRI for early detection of MTM-HCC, which can assist in guiding individualized management.
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Affiliation(s)
- Tingwen Zhou
- Guangdong Medical University, Zhanjiang, China
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xiaorui Han
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Chuyin Xiao
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xiaoxiao Lei
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xinxin Lan
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Xinhua Wei
- Guangdong Medical University, Zhanjiang, China
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Yingying Liang
- Guangdong Medical University, Zhanjiang, China
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Hongzhen Wu
- Guangdong Medical University, Zhanjiang, China.
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
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Lu M, Yan Z, Qu Q, Zhu G, Xu L, Liu M, Jiang J, Gu C, Chen Y, Zhang T, Zhang X. Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination. J Magn Reson Imaging 2025; 61:134-147. [PMID: 38647041 DOI: 10.1002/jmri.29400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 04/06/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Proliferative hepatocellular carcinoma (HCC), aggressive with poor prognosis, and lacks reliable MRI diagnosis. PURPOSE To develop a diagnostic model for proliferative HCC using liver imaging reporting and data system (LI-RADS) and assess its prognostic value. STUDY TYPE Retrospective. POPULATION 241 HCC patients underwent hepatectomy (90 proliferative HCCs: 151 nonproliferative HCCs), divided into the training (N = 167) and validation (N = 74) sets. 57 HCC patients received combination therapy with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). FIELD STRENGTH/SEQUENCE 3.0 T, T1- and T2-weighted, diffusion-weighted, in- and out-phase, T1 high resolution isotropic volume excitation and dynamic gadoxetic acid-enhanced imaging. ASSESSMENT LI-RADS v2018 and other MRI features (intratumoral artery, substantial hypoenhancing component, hepatobiliary phase peritumoral hypointensity, and irregular tumor margin) were assessed. A diagnostic model for proliferative HCC was established, stratifying patients into high- and low-risk groups. Follow-up occurred every 3-6 months, and recurrence-free survival (RFS), progression-free survival (PFS) and overall survival (OS) in different groups were compared. STATISTICAL TESTS Fisher's test or chi-square test, t-test or Mann-Whitney test, logistic regression, Harrell's concordance index (C-index), Kaplan-Meier curves, and Cox proportional hazards. Significance level: P < 0.05. RESULTS The diagnostic model, incorporating corona enhancement, rim arterial phase hyperenhancement, infiltrative appearance, intratumoral artery, and substantial hypoenhancing component, achieved a C-index of 0.823 (training set) and 0.804 (validation set). Median follow-up was 32.5 months (interquartile range [IQR], 25.1 months) for postsurgery patients, and 16.8 months (IQR: 13.2 months) for combination-treated patients. 99 patients experienced recurrence, and 30 demonstrated tumor nonresponse. Differences were significant in RFS and OS rates between high-risk and low-risk groups post-surgery (40.3% vs. 65.8%, 62.3% vs. 90.1%, at 5 years). In combination-treated patients, PFS rates differed significantly (80.6% vs. 7.7% at 2 years). DATA CONCLUSION The MR-based model could pre-treatment identify proliferative HCC and assist in prognosis evaluation. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Mengtian Lu
- Nantong University, Nantong, Jiangsu, China
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Zuyi Yan
- Nantong University, Nantong, Jiangsu, China
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Qi Qu
- Nantong University, Nantong, Jiangsu, China
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Guodong Zhu
- Department of Hepatobiliary Surgery, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Lei Xu
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Maotong Liu
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Jifeng Jiang
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Chunyan Gu
- Department of Pathology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Ying Chen
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Tao Zhang
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
| | - Xueqin Zhang
- Department of Radiology, Affiliated Nantong Hospital 3 of Nantong University, Nantong Third People's Hospital, Nantong, Jiangsu, China
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Gopal P, Hu X, Robert ME, Zhang X. The evolving role of liver biopsy: Current applications and future prospects. Hepatol Commun 2025; 9:e0628. [PMID: 39774070 PMCID: PMC11717517 DOI: 10.1097/hc9.0000000000000628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2024] [Accepted: 12/04/2024] [Indexed: 01/11/2025] Open
Abstract
Histopathologic evaluation of liver biopsy has played a longstanding role in the diagnosis and management of liver disease. However, the utility of liver biopsy has been questioned by some, given the improved imaging modalities, increased availability of noninvasive serologic tests, and development of artificial intelligence over the past several years. In this review, we discuss the current and future role of liver biopsy in both non-neoplastic and neoplastic liver diseases in the era of improved noninvasive laboratory, radiologic, and digital technologies.
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Affiliation(s)
- Purva Gopal
- Deparment of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Xiaobang Hu
- Department of Pathology and Laboratory Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Marie E. Robert
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Xuchen Zhang
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, USA
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11
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Chiang J, Raman SS, Ramakrishnan A, Keshavarz P, Sayre JW, McWilliams JP, Finn RS, Agopian VG, Choi G, Lu DSK. Correlation of Needle Biopsy-Acquired Histopathologic Grade of Hepatocellular Carcinoma with Outcomes after Thermal Ablation. J Vasc Interv Radiol 2025; 36:50-57. [PMID: 39322178 DOI: 10.1016/j.jvir.2024.09.008] [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: 02/27/2024] [Revised: 08/11/2024] [Accepted: 09/14/2024] [Indexed: 09/27/2024] Open
Abstract
PURPOSE To correlate preablation needle biopsy-acquired histopathologic grade of Liver Imaging Reporting and Data System (LI-RADS) 5 hepatocellular carcinoma (HCC) with postablation local tumor control rate, intrahepatic distant tumor progression-free survival, and overall survival. MATERIALS AND METHODS This single-center, retrospective cohort study included adult patients with LI-RADS 5 HCC who underwent a preablation core needle biopsy within 3 months prior to thermal ablation from January 2015 to December 2022. Histopathologic grade from the needle biopsy was evaluated as predictor of local tumor control rate, intrahepatic distant tumor progression-free survival, and overall survival. Kaplan-Meier survival curves were compared using the Gehan generalized Wilcoxon test. RESULTS The study group comprised 133 patients (mean age, 67 years [SD ± 10]; 107 men) with LI-RADS 5 confirmed HCC, stratified into 18 poorly differentiated tumors (median follow-up, 27.7 months; interquartile range [IQR], 15.5-55.4 months) and 115 well-differentiated/moderately differentiated tumors (median follow-up, 29.2 months; IQR, 15.4-59.9 months). No difference in local tumor control rate was noted between the 2 cohorts (hazard ratio [HR], 1.16; 95% CI, 0.32-4.23; P = .898). There was significantly lower intrahepatic distant tumor progression-free survival after thermal ablation in the poorly differentiated cohort (HR, 2.54; 95% CI, 0.92-7.05; P < .001). The overall survival in the poorly differentiated cohort was also lower, although this did not reach statistical significance (HR, 1.77; 95% CI, 0.60-5.26; P = .202). CONCLUSIONS Patients with needle biopsy-proven poorly differentiated LI-RADS 5 HCC had significantly lower intrahepatic distant tumor progression-free survival after thermal ablation compared with those with well-differentiated/moderately differentiated HCC.
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Affiliation(s)
- Jason Chiang
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California.
| | - Steven S Raman
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
| | - Abinaya Ramakrishnan
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Pedram Keshavarz
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - James W Sayre
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Informatics, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Justin P McWilliams
- Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
| | - Richard S Finn
- Division of Hematology/Oncology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
| | - Vatche G Agopian
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
| | - Gina Choi
- Division of Hematology/Oncology, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
| | - David S K Lu
- Division of Interventional Radiology, Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California; Division of Liver and Pancreas Transplantation, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, California; Jonsson Comprehensive Cancer Center, UCLA, Los Angeles, California
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12
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Elias-Neto A, Gonzaga APFC, Braga FA, Gomes NBN, Torres US, D'Ippolito G. Imaging Prognostic Biomarkers in Hepatocellular Carcinoma: A Comprehensive Review. Semin Ultrasound CT MR 2024; 45:454-463. [PMID: 39067621 DOI: 10.1053/j.sult.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide with its incidence on the rise globally. This paper provides a comprehensive review of prognostic imaging markers in HCC, emphasizing their role in risk stratification and clinical decision-making. We explore quantitative and qualitative criteria derived from imaging studies, such as computed tomography (CT) and magnetic resonance imaging (MRI), which can offer valuable insights into the biological behavior of the tumor. While many of these markers are not yet widely integrated into current clinical guidelines, they represent a promising future direction for approaching this highly heterogeneous cancer. However, standardization and validation of these markers remain important challenges. We conclude by emphasizing the importance of ongoing research to enhance clinical practices and improve outcomes for patients with HCC.
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Affiliation(s)
- Abrahão Elias-Neto
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Ana Paula F C Gonzaga
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Fernanda A Braga
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Natália B N Gomes
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Ulysses S Torres
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil; Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil.
| | - Giuseppe D'Ippolito
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil; Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil
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13
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Fuster-Anglada C, Mauro E, Ferrer-Fàbrega J, Caballol B, Sanduzzi-Zamparelli M, Bruix J, Fuster J, Reig M, Díaz A, Forner A. Histological predictors of aggressive recurrence of hepatocellular carcinoma after liver resection. J Hepatol 2024; 81:995-1004. [PMID: 38925272 DOI: 10.1016/j.jhep.2024.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 06/11/2024] [Accepted: 06/17/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND & AIMS Assessment of recurrence risk after liver resection (LR) is critical in hepatocellular carcinoma (HCC), particularly with the advent of effective adjuvant therapy. The aim of this study was to analyze the clinical and pathological factors associated with recurrence, aggressive recurrence, and survival after LR. METHOD We performed a retrospective study in which all single HCC (BCLC-0/A) patients treated with LR between February 2000 and November 2020 were included. The main clinical variables were recorded. Histological features were blindly evaluated by two independent pathologists. Aggressive recurrence was defined as those that exceeded the Milan criteria at 1st recurrence. RESULTS A total of 218 patients were included (30% BCLC 0 and 70% BCLC A), median (IQR) tumor size of 28 (19-42 mm). The prevalence of microvascular invasion and/or satellitosis (mVI/S) was 39%, with a kappa-index between both pathologists of 0.8. After a median follow-up of 49 (23-85) months, 61/218 (28%) patients died, 32/218 (15%) underwent liver transplantation, 127 (58%) developed HCC recurrence. The prevalence of aggressive recurrence was 35% (44/127 Milan-out, with 20 cases at advanced stage), and the 5-year survival rate was 81%. The presence of mVI/S was the only independent predictor of recurrence (hazard ratio [HR] 1.83, 95% CI 1.28-2.61, p <0.001), aggressive recurrence (HR 3.31, 95% CI 1.74-6.29, p <0.001) and mortality (HR 2.23, 95% CI 1.27-3.91, p = 0.005). The macrotrabecular-massive subtype was significantly associated with a higher prevalence of mVI/S, Edmonson Steiner grade III-IV, AFP values and vessels that encapsulate tumor clusters, but not with recurrence, aggressive recurrence, or overall survival. CONCLUSION The presence of mVI/S was the only independent risk factor for aggressive recurrence and mortality. This has important implications for early-stage patient management, especially in the setting of adjuvant immunotherapy or ab initio LT. IMPACT AND IMPLICATIONS Assessment of recurrence risk after liver resection is crucial in patients with hepatocellular carcinoma. Patients with a high risk of recurrence are candidates for liver transplantation as an ab initio indication or for the potential use of adjuvant therapy. Aggressive recurrences, defined as those exceeding the Milan criteria at first recurrence, have a significant impact on overall survival (OS). Fifty-eight percent of patients experienced hepatocellular carcinoma recurrence, with a prevalence of aggressive recurrence at the first occurrence standing at 35%. After a median follow-up of 49 (23-85) months, 61 (28%) patients died, and 32 (15%) underwent liver transplantation, resulting in a 5-year OS rate of 81%. Microvascular invasion and/or satellitosis was present in 39% of our cohort and was the only independent predictor of recurrence, aggressive recurrence, and OS on multivariate analysis. This is important as it could be used to guide therapeutic management.
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Affiliation(s)
- Carla Fuster-Anglada
- Pathology Department. CDB. Liver Oncology Unit. Hospital Clinic Barcelona. Barcelona. Spain; Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain
| | - Ezequiel Mauro
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain
| | - Joana Ferrer-Fàbrega
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Hepatobiliopancreatic Surgery and Liver and Pancreatic Transplantation Unit, Department of Surgery. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona. Spain; Universitat de Barcelona, Barcelona, Spain
| | - Berta Caballol
- Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain
| | - Marco Sanduzzi-Zamparelli
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain
| | - Jordi Bruix
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Universitat de Barcelona, Barcelona, Spain; Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain
| | - Josep Fuster
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Hepatobiliopancreatic Surgery and Liver and Pancreatic Transplantation Unit, Department of Surgery. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona. Spain; Universitat de Barcelona, Barcelona, Spain
| | - María Reig
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Universitat de Barcelona, Barcelona, Spain; Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain
| | - Alba Díaz
- Pathology Department. CDB. Liver Oncology Unit. Hospital Clinic Barcelona. Barcelona. Spain; Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Universitat de Barcelona, Barcelona, Spain.
| | - Alejandro Forner
- Barcelona Clinic Liver Cancer (BCLC) group. IDIBAPS. Barcelona. Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, Spain; Universitat de Barcelona, Barcelona, Spain; Liver Unit. Liver Oncology Unit. ICMDM. Hospital Clinic Barcelona. Barcelona, Spain.
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Zhang Z, Zhang W, He C, Xie J, Liang F, Zhao Y, Tan L, Lai S, Jiang X, Wei X, Zhen X, Yang R. Identification of macrotrabecular-massive hepatocellular carcinoma through multiphasic CT-based representation learning method. Med Phys 2024; 51:9017-9030. [PMID: 39311438 DOI: 10.1002/mp.17401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 07/17/2024] [Accepted: 08/21/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive subtype of HCC and is associated with poor survival. PURPOSE To investigate the performance of a representation learning-based feature fusion strategy that employs a multiphase contrast-enhanced CT (mpCECT)-based latent feature fusion (MCLFF) model for MTM-HCC identification. METHODS A total of 206 patients (54 MTM HCC, 152 non-MTM HCC) who underwent preoperative mpCECT with surgically confirmed HCC between July 2017 and December 2022 were retrospectively included from two medical centers. Multiphasic radiomics features were extracted from manually delineated volume of interest (VOI) of all lesions on each mpCECT phase. Representation learning based MCLFF model was built to fuse multiphasic features for MTM HCC prediction, and compared with competing models using other fusion methods. Conventional imaging features and clinical factors were also evaluated and analyzed. Prediction performance was validated by ROC analysis and statistical comparisons on an internal validation and an external testing dataset. RESULTS Fusion of radiomics features from the arterial phase (AP) and portal venous phase (PAP) using MCLFF demonstrated superior performance in MTM HCC prediction, with a higher AUC of 0.857 compared with all competing models in the internal validation set. Integration of multiple radiological or clinical features further improved the overall performance, with the highest AUCs of 0.857 and 0.836 respectively achieved in the internal validation and external testing set. CONCLUSIONS Multiphasic radiomics features of AP and PVP fused by the MCLFF have demonstrated substantial potential in the accurate prediction of MTM HCC. Clinical factors and Radiological features in mpCECT contribute incremental values to the developed MCLFF strategy.
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Affiliation(s)
- Zhenyang Zhang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Wanli Zhang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Chutong He
- Medical Imaging Center, Jinan University First Affiliated Hospital, Guangzhou, Guangdong, China
| | - Jincheng Xie
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Fangrong Liang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yandong Zhao
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Lilian Tan
- Department of Radiology, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Shengsheng Lai
- School of Medical Equipment, Guangdong Food and Drug Vocational College, Guangzhou, Guangdong, China
| | - Xinqing Jiang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xinhua Wei
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Xin Zhen
- School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
- Medical Big Data Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Ruimeng Yang
- Department of Radiology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Department of Radiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
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15
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Eftimie Spitz R, Manole S, Surdea-Blaga T, Caraiani C, Burz C. Macrotrabecular-Massive Hepatocellular Carcinoma: A Case Report. Cureus 2024; 16:e75989. [PMID: 39835031 PMCID: PMC11743052 DOI: 10.7759/cureus.75989] [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] [Accepted: 12/18/2024] [Indexed: 01/22/2025] Open
Abstract
Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a rare and aggressive molecular subtype of hepatocellular carcinoma (HCC) associated with a poor prognosis. Unlike typical HCC, which commonly arises in the context of cirrhosis, MTM-HCC can develop in non-cirrhotic livers, presenting unique diagnostic and therapeutic challenges. This case report describes a 35-year-old male who presented with persistent epigastric pain, fatigue, and loss of appetite. Clinical examination revealed hepatomegaly, prompting advanced imaging and laboratory investigations. Imaging studies identified a large hepatic mass with portal vein thrombosis and metastatic lesions, while histopathological analysis confirmed the diagnosis of MTM-HCC. The patient initiated treatment with a combination of immune checkpoint inhibitors and anti-angiogenic agents, which represent the current standard for advanced HCC. Despite initial adherence, disease progression was observed after four cycles of therapy. The patient passed away less than two months after his last consultation. This clinical course highlights the aggressive nature of MTM-HCC and its limited responsiveness to existing therapeutic protocols. MTM-HCC is characterized by distinctive histological and molecular features that differentiate it from other HCC subtypes. These include specific genetic mutations and protein expression patterns that contribute to its aggressive behavior and poor prognosis. Advanced imaging modalities combined with histopathological analysis remain crucial for accurate diagnosis and classification. This case emphasizes the critical need for heightened clinical vigilance, particularly in younger patients with atypical presentations of liver disease. It also underscores the importance of developing more effective, tailored therapeutic strategies for MTM-HCC. Further research into its molecular characteristics and inclusion in clinical trials is essential to improving outcomes for patients with this challenging and understudied subtype of liver cancer.
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Affiliation(s)
- Raphaël Eftimie Spitz
- Department of Clinical Immunology and Allergology, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU
| | - Simona Manole
- Department of Radiology and Imaging, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU
| | - Teodora Surdea-Blaga
- Department of Internal Medicine, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU
| | - Cosmin Caraiani
- Department of Medical Imaging and Nuclear Medicine, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU
| | - Claudia Burz
- Department of Clinical Immunology and Allergology, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU
- Department of Medical Oncology, Oncology Institute "Prof. Dr. Ion Chiricuţă" Cluj-Napoca, Cluj-Napoca, ROU
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16
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Pan J, Zhang C, Huang H, Zhu Y, Zhang Y, Wu S, Zhao YC, Chen F. Deciphering the Prognostic and Therapeutic Value of a Gene Model Associated with Two Aggressive Hepatocellular Carcinoma Phenotypes Using Machine Learning. J Hepatocell Carcinoma 2024; 11:2373-2390. [PMID: 39634327 PMCID: PMC11614714 DOI: 10.2147/jhc.s480358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Accepted: 11/19/2024] [Indexed: 12/07/2024] Open
Abstract
Background Macrotrabecular-massive (MTM) and vessels encapsulating tumor clusters (VETC)-hepatocellular carcinoma (HCC) are aggressive histopathological phenotypes with significant prognostic implications. However, the molecular markers associated with MTM-HCC and VETC-HCC and their implications for clinical outcomes and therapeutic strategies remain unclear. Methods Utilizing the TCGA-LIHC cohort, we employed machine learning techniques to develop a prognostic risk score based on MTM and VETC-related genes. The performance of the risk score was assessed by investigating various aspects including clinical outcomes, biological pathways, treatment responses, drug sensitivities, tumor microenvironment, and molecular subclasses. To validate the risk score, additional data from the ICGC-JP, GSE14520, GSE104580, GSE109211, and an in-house cohort were collected and analyzed. Results The machine learning algorithm established a 4-gene-based risk score. High-risk patients had significantly worse prognosis compared to low-risk patients, with the risk score being associated with malignant progression of HCC. Functionally, the high-risk group exhibited enrichment in tumor proliferation pathways. Additionally, patients in the low-risk group exhibited improved response to TACE and sorafenib treatments compared to the high-risk group. In contrast, the high-risk group exhibited reduced sensitivity to immunotherapy and increased sensitivity to paclitaxel. In the in-house cohort, high-risk patients displayed higher rates of early recurrence, along with an increased frequency of elevated alpha-fetoprotein, microvascular invasion, and aggressive MRI features associated with HCC. Conclusion This study has successfully developed a risk score based on MTM and VETC-related genes, providing a promising tool for prognosis prediction and personalized treatment strategies in HCC patients.
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Affiliation(s)
- Junhan Pan
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Cong Zhang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
- Hepatobiliary and Pancreatic Interventional Treatment Center, Division of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Huizhen Huang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Yuhao Zhang
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Shuzhen Wu
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Yan-Ci Zhao
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Feng Chen
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
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Gu K, Min JH, Lee JH, Shin J, Jeong WK, Kim YK, Kim H, Baek SY, Kim JM, Choi GS, Rhu J, Ha SY. Prognostic significance of MRI features in patients with solitary large hepatocellular carcinoma following surgical resection. Eur Radiol 2024; 34:7002-7012. [PMID: 38767659 DOI: 10.1007/s00330-024-10780-x] [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: 11/03/2023] [Revised: 02/22/2024] [Accepted: 03/17/2024] [Indexed: 05/22/2024]
Abstract
OBJECTIVE To assess the prognostic impact of preoperative MRI features on outcomes for single large hepatocellular carcinoma (HCC) (≥ 8 cm) after surgical resection. MATERIAL AND METHODS This retrospective study included 151 patients (mean age: 59.2 years; 126 men) with a single large HCC who underwent gadoxetic acid-enhanced MRI and surgical resection between 2008 and 2020. Clinical variables, including tumor markers and MRI features (tumor size, tumor margin, and the proportion of hypovascular component on hepatic arterial phase (AP) (≥ 50% vs. < 50% tumor volume) were evaluated. Cox proportional hazards model analyzed overall survival (OS), recurrence-free survival (RFS), and associated factors. RESULTS Among 151 HCCs, 37.8% and 62.2% HCCs were classified as ≥ 50% and < 50% AP hypovascular groups, respectively. The 5- and 10-year OS and RFS rates in all patients were 62.0%, 52.6% and 41.4%, 38.5%, respectively. Multivariable analysis revealed that ≥ 50% AP hypovascular group (hazard ratio [HR] 1.7, p = 0.048), tumor size (HR 1.1, p = 0.006), and alpha-fetoprotein ≥ 400 ng/mL (HR 2.6, p = 0.001) correlated with poorer OS. ≥ 50% AP hypovascular group (HR 1.9, p = 0.003), tumor size (HR 1.1, p = 0.023), and non-smooth tumor margin (HR 2.1, p = 0.009) were linked to poorer RFS. One-year RFS rates were lower in the ≥ 50% AP hypovascular group than in the < 50% AP hypovascular group (47.4% vs 66.9%, p = 0.019). CONCLUSION MRI with ≥ 50% AP hypovascular component and larger tumor size were significant factors associated with poorer OS and RFS after resection of single large HCC (≥ 8 cm). These patients require careful multidisciplinary management to determine optimal treatment strategies. CLINICAL RELEVANCE STATEMENT Preoperative MRI showing a ≥ 50% arterial phase hypovascular component and larger tumor size can predict worse outcomes after resection of single large hepatocellular carcinomas (≥ 8 cm), underscoring the need for tailored, multidisciplinary treatment strategies. KEY POINTS MRI features offer insights into the postoperative prognosis for large hepatocellular carcinoma. Hypovascular component on arterial phase ≥ 50% and tumor size predicted poorer overall survival and recurrence-free survival. These findings can assist in prioritizing aggressive and multidisciplinary approaches for patients at risk for poor outcomes.
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Affiliation(s)
- Kyowon Gu
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji Hye Min
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
| | - Jeong Hyun Lee
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jaeseung Shin
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Young Kon Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Honsoul Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sun-Young Baek
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jong Man Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Gyu Seong Choi
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jinsoo Rhu
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sang Yun Ha
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Liu Z, Mao Y, Liu L, Li J, Li Q, Zhou Y. Preoperative CT features for characterization of vessels that encapsulate tumor clusters in hepatocellular carcinoma. Eur J Radiol 2024; 179:111681. [PMID: 39142009 DOI: 10.1016/j.ejrad.2024.111681] [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: 02/21/2024] [Revised: 08/03/2024] [Accepted: 08/08/2024] [Indexed: 08/16/2024]
Abstract
PURPOSE To explore the capability of preoperative CT imaging features, in combination with clinical indicators, for predicting vessels that encapsulate tumor clusters (VETC) pattern and prognosis in hepatocellular carcinoma (HCC). MATERIALS AND METHODS From January 2015 to May 2022, patients with HCC who underwent curative resection and preoperative enhanced CT were retrospectively included. Clinical indicators and imaging featuresassociated with the VETC pattern were determined by logistic regression analyses. The early recurrence (ER) rate was determined using the Kaplan-Meier survival curve. Factors associated with ER after surgical resection were identified by Cox regression analyses. RESULT A total of 243 patients with HCCwere evaluated. The total bilirubin > 17.1 μmol/L (odds ratio [OR] 3.43, 95 % Confidence Interval [CI] 1.70, 6.91, p = 0.001), serum α-fetoprotein > 100 ng/mL (OR 2.41, 95 % CI 1.25, 4.67, p = 0.009), intratumor artery (IA) (OR 2.00, 95 % CI 1.04, 3.86,p = 0.039) and arterial peritumoral enhancement (OR 2.60, 95 % CI 1.13, 5.96, p = 0.025) were independent risk factors for VETC+-HCC. The VETC+status andCT feature ofIA were associated with an increased risk of recurrence, with a shorter median RFS, compared to those without these factors (p < 0.001 and p = 0.019, respectively). In multivariable Cox regression analysis, the VETC+(hazard ratio [HR] 2.60, 95 % CI 1.66, 4.09, p < 0.001), morphological patterns of confluent multinodular growth (HR 1.79, 95 % CI 1.10, 2.91,p = 0.019), the number of the tumors (≥2) (HR 2.69, 95 % CI 1.56, 4.65, p < 0.001), and the IA (HR 1.73, 95 % CI 1.12, 2.66, p = 0.013) were independent predictors of ER in patients with HCC after surgical resection. CONCLUSION Preoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early postoperative recurrence in patients with HCC. CLINICAL RELEVANCE STATEMENT Preoperative CT features combined with clinical indicators could predict VETC pattern, and the CT features, along with VETC status, were of prognostic significance for early recurrence in patients with HCC after surgical resection.
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Affiliation(s)
- Ziyu Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing 400016, PR China.
| | - Yun Mao
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing 400016, PR China.
| | - Liu Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing 400016, PR China.
| | - Junjie Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Chongqing Medical University, PR China.
| | - Qingshu Li
- Department of Pathology, School of Basic Medicine, Chongqing Medical University/ Molecular Medicine Diagnostic and Testing Center, Chongqing Medical University/ Department of Clinical Pathology Laboratory of Pathology Diagnostic Center, Chongqing Medical University, No.1 Medical College Road, Yuzhong District, Chongqing 400016, PR China.
| | - Yin Zhou
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1, Youyi Road, Yuzhong District, Chongqing 400016, PR China.
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Kim TH, Woo S, Lee DH, Do RK, Chernyak V. MRI imaging features for predicting macrotrabecular-massive subtype hepatocellular carcinoma: a systematic review and meta-analysis. Eur Radiol 2024; 34:6896-6907. [PMID: 38507054 PMCID: PMC12058086 DOI: 10.1007/s00330-024-10671-1] [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: 11/06/2023] [Revised: 02/06/2024] [Accepted: 02/14/2024] [Indexed: 03/22/2024]
Abstract
PURPOSE To identify significant MRI features associated with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC), and to assess the distribution of Liver Imaging Radiology and Data System (LI-RADS, LR) category assignments. METHODS PubMed and EMBASE were searched up to March 28, 2023. Random-effects model was constructed to calculate pooled diagnostic odds ratios (DORs) and 95% confidence intervals (CIs) for each MRI feature for differentiating MTM-HCC from NMTM-HCC. The pooled proportions of LI-RADS category assignments in MTM-HCC and NMTM-HCC were compared using z-test. RESULTS Ten studies included 1978 patients with 2031 HCCs (426 (20.9%) MTM-HCC and 1605 (79.1%) NMTM-HCC). Six MRI features showed significant association with MTM-HCC: tumor in vein (TIV) (DOR = 2.4 [95% CI, 1.6-3.5]), rim arterial phase hyperenhancement (DOR =2.6 [95% CI, 1.4-5.0]), corona enhancement (DOR = 2.6 [95% CI, 1.4-4.5]), intratumoral arteries (DOR = 2.6 [95% CI, 1.1-6.3]), peritumoral hypointensity on hepatobiliary phase (DOR = 2.2 [95% CI, 1.5-3.3]), and necrosis (DOR = 4.2 [95% CI, 2.0-8.5]). The pooled proportions of LI-RADS categories in MTM-HCC were LR-3, 0% [95% CI, 0-2%]; LR-4, 11% [95% CI, 6-16%]; LR-5, 63% [95% CI, 55-71%]; LR-M, 12% [95% CI, 6-19%]; and LR-TIV, 13% [95% CI, 6-22%]. In NMTM-HCC, the pooled proportions of LI-RADS categories were LR-3, 1% [95% CI, 0-2%]; LR-4, 8% [95% CI, 3-15%]; LR-5, 77% [95% CI, 71-82%]; LR-M, 5% [95% CI, 3-7%]; and LR-TIV, 6% [95% CI, 2-11%]. MTM-HCC had significantly lower proportion of LR-5 and higher proportion of LR-M and LR-TIV categories. CONCLUSIONS Six MRI features showed significant association with MTM-HCC. Additionally, compared to NMTM-HCC, MTM-HCC are more likely to be categorized LR-M and LR-TIV and less likely to be categorized LR-5. CLINICAL RELEVANCE STATEMENT Several MR imaging features can suggest macrotrabecular-massive hepatocellular carcinoma subtype, which can assist in guiding treatment plans and identifying potential candidates for clinical trials of new treatment strategies. KEY POINTS • Macrotrabecular-massive hepatocellular carcinoma is a subtype of HCC characterized by its aggressive nature and unfavorable prognosis. • Tumor in vein, rim arterial phase hyperenhancement, corona enhancement, intratumoral arteries, peritumoral hypointensity on hepatobiliary phase, and necrosis on MRI are indicative of macrotrabecular-massive hepatocellular carcinoma. • Various MRI characteristics can be utilized for the diagnosis of the macrotrabecular-massive hepatocellular carcinoma subtype. This can prove beneficial in guiding treatment decisions and identifying potential candidates for clinical trials involving novel treatment approaches.
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Affiliation(s)
- Tae-Hyung Kim
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sungmin Woo
- Department of Radiology, NYU Langone Health, New York, NY, USA
| | - Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul, South Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea
| | - Richard K Do
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Victoria Chernyak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
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20
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Jiang H, Zuo M, Li W, Zhuo S, Wu P, An C. Multimodal imaging-based prediction of recurrence for unresectable HCC after downstage and resection-cohort study. Int J Surg 2024; 110:5672-5684. [PMID: 38833331 PMCID: PMC11392192 DOI: 10.1097/js9.0000000000001752] [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: 02/23/2024] [Accepted: 05/19/2024] [Indexed: 06/06/2024]
Abstract
BACKGROUND Surgical resection (SR) following transarterial chemoembolization (TACE)-based downstaging is a promising treatment for unresectable hepatocellular carcinoma (uHCC), and identification of patients at high-risk of postoperative recurrence may assist individualized treatment. PURPOSE To develop and externally validate preoperative and postoperative prognostic models integrating multimodal CT and digital subtraction angiography features as well as clinico-therapeutic-pathological features for predicting disease-free survival (DFS) after TACE-based downstaging therapy. MATERIALS AND METHODS From March 2008 to August 2022, 488 consecutive patients with Barcelona Clinic Liver Cancer (BCLC) A/B uHCC receiving TACE-based downstaging therapy and subsequent SR were included from four tertiary-care hospitals. All CT and digital subtraction angiography images were independently evaluated by two blinded radiologists. In the derivation cohort ( n =390), the XGBoost algorithm was used for feature selection, and Cox regression analysis for developing nomograms for DFS (time from downstaging to postoperative recurrence or death). In the external testing cohort ( n =98), model performances were compared with five major staging systems. RESULTS The preoperative nomogram included over three tumors [hazard ratio (HR), 1.42; P =0.003], intratumoral artery (HR, 1.38; P =0.006), TACE combined with tyrosine kinase inhibitor (HR, 0.46; P <0.001) and objective response to downstaging therapy (HR, 1.60; P <0.001); while the postoperative nomogram included over three tumors (HR, 1.43; P =0.013), intratumoral artery (HR, 1.38; P =0.020), TACE combined with tyrosine kinase inhibitor (HR, 0.48; P <0.001), objective response to downstaging therapy (HR, 1.69; P <0.001) and microvascular invasion (HR, 2.20; P <0.001). The testing dataset C-indexes of the preoperative (0.651) and postoperative (0.687) nomograms were higher than all five staging systems (0.472-0.542; all P <0.001). Two prognostically distinct risk strata were identified according to these nomograms (all P <0.001). CONCLUSION Based on 488 patients receiving TACE-based downstaging therapy and subsequent SR for BCLC A/B uHCCs, the authors developed and externally validated two nomograms for predicting DFS, with superior performances than five major staging systems and effective survival stratification.
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Affiliation(s)
- Hanyu Jiang
- Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Mengxuan Zuo
- Department of Minimal invasive intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center
| | - Wang Li
- Department of Minimal invasive intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center
| | - Shuiqing Zhuo
- Department of Radiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong
| | - Peihong Wu
- Department of Minimal invasive intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center
| | - Chao An
- Department of Minimal invasive intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center
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21
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Laurent-Bellue A, Sadraoui A, Claude L, Calderaro J, Posseme K, Vibert E, Cherqui D, Rosmorduc O, Lewin M, Pesquet JC, Guettier C. Deep Learning Classification and Quantification of Pejorative and Nonpejorative Architectures in Resected Hepatocellular Carcinoma from Digital Histopathologic Images. THE AMERICAN JOURNAL OF PATHOLOGY 2024; 194:1684-1700. [PMID: 38879083 DOI: 10.1016/j.ajpath.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/17/2024] [Accepted: 05/16/2024] [Indexed: 06/27/2024]
Abstract
Liver resection is one of the best treatments for small hepatocellular carcinoma (HCC), but post-resection recurrence is frequent. Biotherapies have emerged as an efficient adjuvant treatment, making the identification of patients at high risk of recurrence critical. Microvascular invasion (mVI), poor differentiation, pejorative macrotrabecular architectures, and vessels encapsulating tumor clusters architectures are the most accurate histologic predictors of recurrence, but their evaluation is time-consuming and imperfect. Herein, a supervised deep learning-based approach with ResNet34 on 680 whole slide images (WSIs) from 107 liver resection specimens was used to build an algorithm for the identification and quantification of these pejorative architectures. This model achieved an accuracy of 0.864 at patch level and 0.823 at WSI level. To assess its robustness, it was validated on an external cohort of 29 HCCs from another hospital, with an accuracy of 0.787 at WSI level, affirming its generalization capabilities. Moreover, the largest connected areas of the pejorative architectures extracted from the model were positively correlated to the presence of mVI and the number of tumor emboli. These results suggest that the identification of pejorative architectures could be an efficient surrogate of mVI and have a strong predictive value for the risk of recurrence. This study is the first step in the construction of a composite predictive algorithm for early post-resection recurrence of HCC, including artificial intelligence-based features.
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Affiliation(s)
- Astrid Laurent-Bellue
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Aymen Sadraoui
- Centre de Vision Numérique, Paris-Saclay University, Inria, CentraleSupélec, Gif-sur-Yvette, France
| | - Laura Claude
- Department of Pathology, Charles Nicolle Hospital, Rouen, France
| | - Julien Calderaro
- Department of Pathology, Henri-Mondor Hospital, Assistance Publique-Hôpitaux de Paris, Créteil, France
| | - Katia Posseme
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France
| | - Eric Vibert
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Daniel Cherqui
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Olivier Rosmorduc
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Maïté Lewin
- Centre Hépato-Biliaire, Paul-Brousse Hospital, Assistance Publique-Hôpitaux de Paris, Villejuif, France; Faculté de Médecine, Paris-Saclay University, Le Kremlin-Bicêtre, France; Unité Mixte de Recherche 1193, Paris-Saclay University, INSERM, Villejuif, France
| | - Jean-Christophe Pesquet
- Centre de Vision Numérique, Paris-Saclay University, Inria, CentraleSupélec, Gif-sur-Yvette, France
| | - Catherine Guettier
- Department of Pathology, Bicêtre Hospital, Assistance Publique-Hôpitaux de Paris, Le Kremlin-Bicêtre, France.
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22
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Wang Y, Wang M, Cao L, Huang H, Cao S, Tian X, Lei J. A nomogram for preoperative prediction of vessels encapsulating tumor clusters (VETC) pattern and prognosis of hepatocellular carcinoma. Am J Surg 2024; 234:172-178. [PMID: 38755026 DOI: 10.1016/j.amjsurg.2024.05.004] [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: 02/09/2024] [Revised: 04/15/2024] [Accepted: 05/04/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. This study aimed to establish a nomogram model to predict VETC patterns based on preoperative CT imaging features. PATIENTS AND METHODS Patients who underwent surgical resection between January 1, 2016 and August 31, 2022 were retrospectively included. Predictors associated with VETC pattern were determined by using logistic regression analyses, and a nomogram model was constructed. Prognostic factors associated with recurrence-free survival (RFS) after surgical resection were identified by using Cox regression analyses. RESULTS A total of 84 patients were included for CT analysis. All patients underwent radical surgical resection. AST/ALT >1.07(odds ratio [OR], 4.91; 95 % CI: 1.11, 21.68; P < 0.05), intratumoral necrosis (OR, 4.99; 95 % CI: 1.25, 19.99; P < 0.05) and enhancing capsule (OR, 3.32; 95 % CI: 1.27, 8.94; P < 0.05) were independent predictors of VETC pattern. These features were used for the construction of nomogram model, which showed comparable prediction performance, with AUC value of 0.767 (95%CI [0.662, 0.852]). CK19 status (Hazard ratio [HR], 2.02; 95 % CI: 1.06, 3.86; P < 0.05), the number of tumors (HR, 3.31; 95 % CI: 1.47, 7.45; P < 0.05) and VETC pattern (HR, 2.52; 95 % CI: 1.31, 4.86; P < 0.05) were independent predictors of postoperative RFS. CONCLUSION A nomogram model based on preoperative CT imaging features could be used for the characterization of VETC pattern, and has prognostic significance for postoperative RFS in patients with HCC.
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Affiliation(s)
- Yinzhong Wang
- Department of Radiology, The First Hospital of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China
| | - Miaomiao Wang
- The First Clinical Medical College of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China
| | - Liang Cao
- Department of Radiology, The First Hospital of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China
| | - Hongliang Huang
- Department of Radiology, The First Hospital of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China
| | - Shi Cao
- Department of Pathology, The First Hospital of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China
| | - Xiaoxue Tian
- Department of Nuclear Medicine, Second Hospital of LanZhou University, No.82, Cuiyingmen, Chengguan District, Lanzhou City, Gansu Province, China
| | - Junqiang Lei
- Department of Radiology, The First Hospital of Lanzhou University, No.1 Donggang West Road, Lanzhou City, Gansu Province, China.
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Suddle A, Reeves H, Hubner R, Marshall A, Rowe I, Tiniakos D, Hubscher S, Callaway M, Sharma D, See TC, Hawkins M, Ford-Dunn S, Selemani S, Meyer T. British Society of Gastroenterology guidelines for the management of hepatocellular carcinoma in adults. Gut 2024; 73:1235-1268. [PMID: 38627031 PMCID: PMC11287576 DOI: 10.1136/gutjnl-2023-331695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 03/19/2024] [Indexed: 05/01/2024]
Abstract
Deaths from the majority of cancers are falling globally, but the incidence and mortality from hepatocellular carcinoma (HCC) is increasing in the United Kingdom and in other Western countries. HCC is a highly fatal cancer, often diagnosed late, with an incidence to mortality ratio that approaches 1. Despite there being a number of treatment options, including those associated with good medium to long-term survival, 5-year survival from HCC in the UK remains below 20%. Sex, ethnicity and deprivation are important demographics for the incidence of, and/or survival from, HCC. These clinical practice guidelines will provide evidence-based advice for the assessment and management of patients with HCC. The clinical and scientific data underpinning the recommendations we make are summarised in detail. Much of the content will have broad relevance, but the treatment algorithms are based on therapies that are available in the UK and have regulatory approval for use in the National Health Service.
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Affiliation(s)
- Abid Suddle
- King's College Hospital NHS Foundation Trust, London, UK
| | - Helen Reeves
- Newcastle University Translational and Clinical Research Institute, Newcastle upon Tyne, UK
| | - Richard Hubner
- Department of Oncology, The Christie NHS Foundation Trust, Manchester, UK
| | | | - Ian Rowe
- University of Leeds, Leeds, UK
- St James's University Hospital, Leeds, UK
| | - Dina Tiniakos
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Stefan Hubscher
- Department of Pathology, University of Birmingham, Birmingham, UK
| | - Mark Callaway
- Division of Diagnostics and Therapies, University Hospitals Bristol NHS Trust, Bristol, UK
| | | | - Teik Choon See
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Maria Hawkins
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | | | - Sarah Selemani
- King's College Hospital NHS Foundation Trust, London, UK
| | - Tim Meyer
- Department of Oncology, University College, London, UK
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24
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Balli HT, Piskin FC, Sozutok S, Erdoğan KE, Aikimbaev K. Outcomes in Patients with Macrotrabecular-Massive Subtype Hepatocellular Carcinoma Treated with Yttrium-90 Transarterial Radioembolization. J Vasc Interv Radiol 2024; 35:998-1003. [PMID: 38548131 DOI: 10.1016/j.jvir.2024.03.025] [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: 06/28/2023] [Revised: 03/03/2024] [Accepted: 03/13/2024] [Indexed: 05/26/2024] Open
Abstract
PURPOSE To compare the outcomes of yttrium-90 transarterial radioembolization (TARE) in patients with hepatocellular carcinoma (HCC) with and without macrotrabecular-massive (MTM) subtypes. MATERIALS AND METHODS Forty-one consecutive patients with HCC (male, 90.3%; mean age, 65.3 years [SD ± 10.7]) who underwent yttrium-90 TARE between September 2014 and January 2022 were grouped into the MTM-HCC (n = 17, 41.5%) and non-MTM-HCC (n = 24, 58.5%) groups based on their histopathological subtypes. Demographic, clinical, and radiological characteristics were compared. Survival, univariate, and multivariate analyses were performed, and prognostic factors were evaluated. RESULTS In MTM-HCC group, the rates of moderately to poorly differentiated tumors were significantly higher (13/17 vs 8/16, P = .007), and new intrahepatic/extrahepatic metastases were detected more frequently (12/17 vs 15/24, P = .038). Median overall survival (OS) in the cohort was 29 months (range, 17.1-40.9 months), whereas patients with MTM-HCC had a significantly shorter median OS (20 vs 44 months, P = .014). In univariate analysis, MTM-HCC subtype (hazard ratio [HR], 2.690; P = .021), the presence of satellite nodules (HR, 3.810; P = .004), and macrovascular invasion (HR, 3.321; P = .012) were identified as significant prognostic factors. In multivariate analysis, MTM-HCC subtype and macrovascular invasion were determined as independent poor prognostic factors (P = .038 and P = .012, respectively). CONCLUSIONS In patients with HCC treated with yttrium-90 TARE, both the rates of moderately to poorly differentiated histopathological classes and the development of intrahepatic or extrahepatic metastases were significantly higher in the MTM-HCC subtype. OS was worse in patients with MTM-HCC, and macrovascular invasion and MTM-HCC subtype were identified as independent poor prognostic factors.
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Affiliation(s)
| | | | | | - Kivilcim Eren Erdoğan
- Department of Pathology, Cukurova University Medical School, Balcali Hospital, Adana, Turkey
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25
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Huang XW, Li Y, Jiang LN, Zhao BK, Liu YS, Chen C, Zhao D, Zhang XL, Li ML, Jiang YY, Liu SH, Zhu L, Zhao JM. Nomogram for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma. Transl Oncol 2024; 45:101986. [PMID: 38723299 PMCID: PMC11101742 DOI: 10.1016/j.tranon.2024.101986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 04/22/2024] [Accepted: 05/05/2024] [Indexed: 05/21/2024] Open
Abstract
Microvascular invasion (MVI) is an adverse prognostic indicator of tumor recurrence after surgery for hepatocellular carcinoma (HCC). Therefore, developing a nomogram for estimating the presence of MVI before liver resection is necessary. We retrospectively included 260 patients with pathologically confirmed HCC at the Fifth Medical Center of Chinese PLA General Hospital between January 2021 and April 2024. The patients were randomly divided into a training cohort (n = 182) for nomogram development, and a validation cohort (n = 78) to confirm the performance of the model (7:3 ratio). Significant clinical variables associated with MVI were then incorporated into the predictive nomogram using both univariate and multivariate logistic analyses. The predictive performance of the nomogram was assessed based on its discrimination, calibration, and clinical utility. Serum carnosine dipeptidase 1 ([CNDP1] OR 2.973; 95 % CI 1.167-7.575; p = 0.022), cirrhosis (OR 8.911; 95 % CI 1.922-41.318; p = 0.005), multiple tumors (OR 4.095; 95 % CI 1.374-12.205; p = 0.011), and tumor diameter ≥3 cm (OR 4.408; 95 % CI 1.780-10.919; p = 0.001) were independent predictors of MVI. Performance of the nomogram based on serum CNDP1, cirrhosis, number of tumors and tumor diameter was achieved with a concordance index of 0.833 (95 % CI 0.771-0.894) and 0.821 (95 % CI 0.720-0.922) in the training and validation cohorts, respectively. It fitted well in the calibration curves, and the decision curve analysis further confirmed its clinical usefulness. The nomogram, incorporating significant clinical variables and imaging features, successfully predicted the personalized risk of MVI in HCC preoperatively.
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Affiliation(s)
- Xiao-Wen Huang
- Medical School of Chinese PLA, Beijing, China; Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yan Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Li-Na Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Bo-Kang Zhao
- Department of Hepatology, Center of Infectious Diseases and Pathogen Biology, The First Hospital of Jilin University, Changchun, China
| | - Yi-Si Liu
- First Department of Liver Disease Center, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Chun Chen
- Senior Department of Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Dan Zhao
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xue-Li Zhang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Mei-Ling Li
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yi-Yun Jiang
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shu-Hong Liu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Li Zhu
- Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jing-Min Zhao
- Medical School of Chinese PLA, Beijing, China; Department of Pathology and Hepatology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
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Cheng J, Li X, Wang L, Chen F, Li Y, Zuo G, Pei M, Zhang H, Yu L, Liu C, Wang J, Han Q, Cai P, Li X. Evaluation and Prognostication of Gd-EOB-DTPA MRI and CT in Patients With Macrotrabecular-Massive Hepatocellular Carcinoma. J Magn Reson Imaging 2024; 59:2071-2081. [PMID: 37840197 DOI: 10.1002/jmri.29052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/17/2023] Open
Abstract
BACKGROUND Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is highly aggressive. Comparing the diagnosis ability of CT and gadoxetate disodium (Gd-EOB-DTPA) MRI for MTM-HCC are lacking. PURPOSE To compare the performance of Gd-EOB-DTPA MRI and CT for differentiating MTM-HCC from non-MTM-HCC, and determine the prognostic indicator. STUDY TYPE Retrospective. SUBJECTS Post-surgery HCC patients, divided into the training (N = 272) and external validation (N = 44) cohorts. FIELD STRENGTH/SEQUENCE 3.0 T, T1-weighted imaging, in-opp phase, and T1-weighted volumetric interpolated breath-hold examination/liver acquisition with volume acceleration; enhanced CT. ASSESSMENT Three radiologists evaluated clinical characteristics (sex, age, liver disease, liver function, blood routine, alpha-fetoprotein [AFP] and prothrombin time international normalization ratio [PT-INR]) and imaging features (tumor length, intratumor fat, hemorrhage, arterial phase peritumoral enhancement, intratumor necrosis or ischemia, capsule, and peritumoral hepatobiliary phase [HBP] hypointensity). Compared the performance of CT and MRI for diagnosing MTM-HCC. Follow-up occurred every 3-6 months, and nomogram demonstrated the probability of MTM-HCC. STATISTICAL TESTS Fisher test, t-test or Wilcoxon rank-sum test, area under the curve (AUC), 95% confidence interval (CI), multivariable logistic regression, Kaplan-Meier curve, and Cox proportional hazards. Significance level: P < 0.05. RESULTS Gd-EOB-DTPA MRI (AUC: 0.793; 95% CI, 0.740-0.839) outperformed CT (AUC: 0.747; 95% CI, 0.691-0.797) in the training cohort. The nomogram, incorporating AFP, PT-INR, and MRI features (non-intratumor fat, incomplete capsule, intratumor necrosis or ischemia, and peritumoral HBP hypointensity) demonstrated powerful performance for diagnosing MTM-HCC with an AUC of 0.826 (95% CI, 0.631-1.000) in the external validation cohort. Median follow-up was 347 days (interquartile range [IQR], 606 days) for the training cohort and 222 days (IQR, 441 days) for external validation cohort. Intratumor necrosis or ischemia was an independent indicator for poor prognosis. DATA CONCLUSION Gd-EOB-DTPA MRI might assist in preoperative diagnosis of MTM-HCC, and intratumor necrosis or ischemia was associated with poor prognosis. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Jie Cheng
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xiaofeng Li
- Department of Radiology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Limei Wang
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Fengxi Chen
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Yiman Li
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Guojiao Zuo
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Mi Pei
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Huarong Zhang
- Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
| | - Linze Yu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, China
| | - Chen Liu
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Qi Han
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ping Cai
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xiaoming Li
- Department of Radiology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China
- 7T Magnetic Resonance Imaging Translational Medical Center, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
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Faure A, Dioguardi Burgio M, Cannella R, Sartoris R, Bouattour M, Hobeika C, Cauchy F, Trapani L, Beaufrère A, Vilgrain V, Ronot M. Imaging and prognostic characterization of fat-containing hepatocellular carcinoma subtypes. LA RADIOLOGIA MEDICA 2024; 129:687-701. [PMID: 38512627 DOI: 10.1007/s11547-024-01807-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/04/2024] [Indexed: 03/23/2024]
Abstract
PURPOSE Steatohepatitic hepatocellular carcinoma (SH-HCC) is characterized by intratumoral fat with > 50% inflammatory changes. However, intratumoral fat (with or without inflammation) can also be found in not-otherwise specified HCC (NOS-HCC). We compared the imaging features and outcome of resected HCC containing fat on pathology including SH-HCC (> 50% steatohepatitic component), NOS-HCC with < 50% steatohepatitic component (SH-NOS-HCC), and fatty NOS-HCC (no steatohepatitic component). MATERIAL AND METHODS From September 2012 to June 2021, 94 patients underwent hepatic resection for fat-containing HCC on pathology. Imaging features and categories were assessed using LIRADS v2018. Fat quantification was performed on chemical-shift MRI. Recurrence-free and overall survival were estimated. RESULTS Twenty-one patients (26%) had nonalcoholic steatohepatitis (NASH). The median intra-tumoral fat fraction was 8%, with differences between SH-HCC and SH-NOS-HCC (9.5% vs. 5% p = 0.03). There was no difference in major LI-RADS features between all groups; most tumors were classified as LR-4/5. A mosaic architecture on MRI was rare (7%) in SH-HCC, a fat in mass on CT was more frequently depicted (48%) in SH-HCC. A combination of NASH with no mosaic architecture on MRI or NASH with fat in mass on CT yielded excellent specificity for diagnosing SH-HCC (97.6% and 97.7%, respectively). The median recurrence-free and overall survival were 58 and 87 months, with no difference between groups (p = 0.18 and p = 0.69). CONCLUSION In patients with NASH, an SH-HCC may be suspected in L4/LR-5 observations with no mosaic architecture at MRI or with fat in mass on CT. Oncological outcomes appear similar between fat-containing HCC subtypes.
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Affiliation(s)
- Alexandre Faure
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Marco Dioguardi Burgio
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France.
- UMR1149, Centre de Recherche Sur L'inflammation, Université Paris Cité, 75018, Paris, France.
| | - Roberto Cannella
- Section of Radiology, Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo, Italy
| | - Riccardo Sartoris
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Mohamed Bouattour
- Department of Digestive Oncology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Christian Hobeika
- Department of HPB Surgery and Liver Transplantation, Hôpital Beaujon, AP-HP, 92110, Clichy, France
| | - Francois Cauchy
- Department of HPB Surgery and Liver Transplantation, Hôpital Beaujon, AP-HP, 92110, Clichy, France
| | - Loïc Trapani
- Department of Pathology, FHU MOSAIC, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Aurélie Beaufrère
- UMR1149, Centre de Recherche Sur L'inflammation, Université Paris Cité, 75018, Paris, France
- Department of Pathology, FHU MOSAIC, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
| | - Valérie Vilgrain
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
- UMR1149, Centre de Recherche Sur L'inflammation, Université Paris Cité, 75018, Paris, France
| | - Maxime Ronot
- Department of Radiology, Hôpital Beaujon, AP-HP.Nord, 100 Boulevard du Général Leclerc, 92110, Clichy, France
- UMR1149, Centre de Recherche Sur L'inflammation, Université Paris Cité, 75018, Paris, France
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Ding F, Huang M, Ren P, Zhang J, Lin Z, Sun Y, Liang C, Zhao X. Quantitative information from gadobenate dimeglumine-enhanced MRI can predict proliferative subtype of solitary hepatocellular carcinoma: a multicenter retrospective study. Eur Radiol 2024; 34:2445-2456. [PMID: 37691080 DOI: 10.1007/s00330-023-10227-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 06/18/2023] [Accepted: 07/15/2023] [Indexed: 09/12/2023]
Abstract
OBJECTIVES To investigate the value of quantitative parameters derived from gadobenate dimeglumine-enhanced magnetic resonance imaging (MRI) for predicting molecular subtype of hepatocellular carcinoma (HCC) and overall survival. METHODS This multicenter retrospective study included 218 solitary HCC patients who underwent gadobenate dimeglumine-enhanced MRI. All HCC lesions were resected and pathologically confirmed. The lesion-to-liver contrast enhancement ratio (LLCER) and lesion-to-liver contrast (LLC) were measured in the hepatobiliary phase. Potential risk factors for proliferative HCC were assessed by logistic regression. The ability of LLCER and LLC to predict proliferative HCC was assessed by the receiver operating characteristic (ROC) curve. Prognostic factors were evaluated using the Cox proportional hazards regression model for survival outcomes. RESULTS LLCER was an independent predictor of proliferative HCC (odds ratio, 0.015; 95% confidence interval [CI], 0.008-0.022; p < 0.001). The area under the ROC curve was 0.812 (95% CI, 0.748-0.877), higher than that of LLC, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement (all p ≤ 0.001). HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%. During the follow-up period, LLCER was an independent predictor of overall survival (hazard ratio, 0.070; 95% CI, 0.015-0.324; p = 0.001) in HCC patients. CONCLUSIONS Gadobenate dimeglumine-enhanced quantitative parameter in the hepatobiliary phase can predict the proliferative subtype of solitary HCC with a moderately high accuracy. CLINICAL RELEVANCE STATEMENT Quantitative information from gadobenate dimeglumine-enhanced MRI can provide crucial information on hepatocellular carcinoma subtypes. It might be valuable to design novel therapeutic strategies, such as targeted therapies or immunotherapy. KEY POINTS • The lesion-to-liver contrast enhancement ratio (LLCER) is an independent predictor of proliferative hepatocellular carcinoma (HCC). • The ability of LLCER to predict proliferative HCC outperformed lesion-to-liver contrast, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement. • HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%.
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Affiliation(s)
- Feier Ding
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong Province, China
| | - Min Huang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong Province, China
| | - Ping Ren
- Department of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong Province, China
| | - Junlei Zhang
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong Province, China
| | - Zhengyu Lin
- Department of Interventional Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, 350000, Fujian Province, China
| | - Yan Sun
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University, Jinan, 250021, Shandong Province, China
| | - Changhu Liang
- Department of Radiology, Shandong Provincial Hospital, Shandong University, Jinan, 250021, Shandong Province, China.
| | - Xinya Zhao
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, Shandong Province, China.
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Xu W, Huang B, Zhang R, Zhong X, Zhou W, Zhuang S, Xie X, Fang J, Xu M. Diagnostic and Prognostic Ability of Contrast-Enhanced Unltrasound and Biomarkers in Hepatocellular Carcinoma Subtypes. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:617-626. [PMID: 38281888 DOI: 10.1016/j.ultrasmedbio.2024.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/07/2023] [Accepted: 01/06/2024] [Indexed: 01/30/2024]
Abstract
OBJECTIVE To investigate the diagnostic and prognostic value of contrast-enhanced ultrasound (CEUS) and clinical indicators of the vessels encapsulating tumor clusters (VETC) pattern and macrotrabecular-massive subtype in hepatocellular carcinoma (MTM-HCC). METHODS This retrospective study included patients who underwent preoperative CEUS and hepatectomy for HCC between August 2018 and August 2021. Multivariable logistic regression was performed to select independent correlated factors of VETC-HCC and MTM-HCC to develop nomogram models. The association between model outcomes and early postoperative HCC recurrence was assessed using Kaplan-Meier curve and Cox regression analysis. RESULTS The training cohort included 182 patients (54.3 ± 11.3 years, 168 males) and the validation cohort included 91 patients (54.8 ± 10.6 years, 81 males). Multivariate logistic regression analysis revealed that α-fetoprotein (AFP) levels (odds ratio [OR]: 2.26, 95% confidence interval [CI]: 1.49-3.42, p < 0.001), intratumoral nonenhancement (OR: 2.40, 95% CI: 1.02-5.64, p = 0.044), and the perfusion pattern in the CEUS arterial phase (OR: 2.27, 95% CI: 1.05-4.91, p = 0.038) were independent predictors of VETC-HCC. Besides, the former two were also independently associated with MTM-HCC (AFP level: OR: 2.36, 95% CI: 1.36-4.09, p = 0.002; intratumoral nonenhancement: OR: 3.72, 95% CI: 1.02-13.56, p = 0.046). Nomogram models were constructed based on the aforementioned indicators. Kaplan-Meier curve analysis indicated that predicted VETC-HCC or MTM-HCC exhibited higher rates of early recurrence (log-rank p < 0.001 and p = 0.002, respectively). Cox regression analysis showed that a high risk of VETC-HCC was independently correlated with early recurrence (p = 0.011). CONCLUSION CEUS combined with AFP levels can predict VETC-HCC/MTM-HCC and prognosis preoperatively.
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Affiliation(s)
- Wenxin Xu
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China
| | - Biyu Huang
- Key Laboratory of Gene Function and Regulation, School of Life Sciences, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Rui Zhang
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China
| | - Xian Zhong
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China
| | - Wenwen Zhou
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China
| | - Shimei Zhuang
- Key Laboratory of Gene Function and Regulation, School of Life Sciences, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xiaoyan Xie
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China
| | - Jianhong Fang
- Key Laboratory of Gene Function and Regulation, School of Life Sciences, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Ming Xu
- Department of Medical Ultrasonics, The First Affiliated Hospital, Institute of Diagnostic and Interventional Ultrasound, Sun Yat-Sen University, Guangzhou, China.
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Yen YH, Kee KM, Hu TH, Tsai MC, Kuo YH, Li WF, Liu YW, Wang CC, Lin CY. Hepatitis B virus-related hepatocellular carcinoma has superior overall survival compared with other etiologies. PLoS One 2024; 19:e0290523. [PMID: 38489301 PMCID: PMC10942080 DOI: 10.1371/journal.pone.0290523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/17/2023] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Whether the etiology of chronic liver disease (CLD) impacts the overall survival (OS) of patients with hepatocellular carcinoma (HCC) remains unclear. We aim to clarify this issue. MATERIALS AND METHODS Between 2011 and 2020, 3941 patients who were newly diagnosed with HCC at our institution were enrolled in this study. In patients with multiple CLD etiologies, etiology was classified using the following hierarchy: hepatitis C virus (HCV) > hepatitis B virus (HBV) > alcohol-related > all negative. All negative was defined as negative for HCV, HBV, and alcohol use disorder. RESULTS Among 3941 patients, 1407 patients were classified with HCV-related HCC, 1677 patients had HBV-related HCC, 145 patients had alcohol-related HCC, and 712 patients had all-negative HCC. Using the all-negative group as the reference group, multivariate analysis showed that HBV is an independent predictor of mortality (hazard ratio: 0.856; 95% confidence interval: 0.745-0.983; p = 0.027). Patients with HBV-related HCC had superior OS compared with patients with other CLD etiologies (p<0.001). Subgroup analyses were performed, for Barcelona Clinic Liver Cancer (BCLC) stages 0-A (p<0.001); serum alpha-fetoprotein (AFP) levels≧20 ng/ml (p<0.001); AFP levels < 20 ng/ml (p<0.001); age > 65 years (p<0.001); and the use of curative treatments (p = 0.002). No significant difference in OS between HBV and other etiologies was observed among patients aged ≤ 65 years (p = 0.304); with BCLC stages B-D (p = 0.973); or who underwent non-curative treatments (p = 0.1). CONCLUSION Patients with HBV-related HCC had superior OS than patients with other HCC etiologies.
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Affiliation(s)
- Yi-Hao Yen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Kwong-Ming Kee
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Tsung-Hui Hu
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Ming-Chao Tsai
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yuan-Hung Kuo
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Wei-Feng Li
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yueh-Wei Liu
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Chi Wang
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Yun Lin
- Biostatistics Center of Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
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Hou K, Xu X, Ge X, Jiang J, Ouyang F. Blockade of PD-1 and CTLA-4: A potent immunotherapeutic approach for hepatocellular carcinoma. Biofactors 2024; 50:250-265. [PMID: 37921427 DOI: 10.1002/biof.2012] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 09/07/2023] [Indexed: 11/04/2023]
Abstract
Immune checkpoints (ICPs) can promote tumor growth and prevent immunity-induced cancer cell apoptosis. Fortunately, targeting ICPs, such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4), has achieved great success in the past few years and has gradually become an effective treatment for cancers, including hepatocellular carcinoma (HCC). However, many patients do not respond to ICP therapy due to acquired resistance and recurrence. Therefore, clarifying the specific mechanisms of ICP in the development of HCC is very important for enhancing the efficacy of anti-PD-1 and anti-CTLA-4 therapy. In particular, antigen presentation and interferon-γ (IFN-γ) signaling were reported to be involved in the development of resistance. In this review, we have explained the role and regulatory mechanisms of ICP therapy in HCC pathology. Moreover, we have also elaborated on combinations of ICP inhibitors and other treatments to enhance the antitumor effect. Collectively, recent advances in the pharmacological targeting of ICPs provide insights for the development of a novel alternative treatment for HCC.
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Affiliation(s)
- Kai Hou
- Clinical Research Center of the Second Affiliated Hospital, University of South China, Hengyang, Hunan, PR China
| | - Xiaohui Xu
- Department of Medicine of the Second Affiliated Hospital, University of South China, Hengyang, Hunan, PR China
| | - Xin Ge
- Clinical Research Center of the Second Affiliated Hospital, University of South China, Hengyang, Hunan, PR China
| | - Jiacen Jiang
- Department of Medicine of the Second Affiliated Hospital, University of South China, Hengyang, Hunan, PR China
| | - Fan Ouyang
- Department of Cardiology, Zhuzhou Hospital, the Affiliated Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, PR China
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Starmans MPA, Miclea RL, Vilgrain V, Ronot M, Purcell Y, Verbeek J, Niessen WJ, Ijzermans JNM, de Man RA, Doukas M, Klein S, Thomeer MG. Automated Assessment of T2-Weighted MRI to Differentiate Malignant and Benign Primary Solid Liver Lesions in Noncirrhotic Livers Using Radiomics. Acad Radiol 2024; 31:870-879. [PMID: 37648580 DOI: 10.1016/j.acra.2023.07.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 07/06/2023] [Accepted: 07/25/2023] [Indexed: 09/01/2023]
Abstract
RATIONALE AND OBJECTIVES Distinguishing malignant from benign liver lesions based on magnetic resonance imaging (MRI) is an important but often challenging task, especially in noncirrhotic livers. We developed and externally validated a radiomics model to quantitatively assess T2-weighted MRI to distinguish the most common malignant and benign primary solid liver lesions in noncirrhotic livers. MATERIALS AND METHODS Data sets were retrospectively collected from three tertiary referral centers (A, B, and C) between 2002 and 2018. Patients with malignant (hepatocellular carcinoma and intrahepatic cholangiocarcinoma) and benign (hepatocellular adenoma and focal nodular hyperplasia) lesions were included. A radiomics model based on T2-weighted MRI was developed in data set A using a combination of machine learning approaches. The model was internally evaluated on data set A through cross-validation, externally validated on data sets B and C, and compared to visual scoring of two experienced abdominal radiologists on data set C. RESULTS The overall data set included 486 patients (A: 187, B: 98, and C: 201). The radiomics model had a mean area under the curve (AUC) of 0.78 upon internal validation on data set A and a similar AUC in external validation (B: 0.74 and C: 0.76). In data set C, the two radiologists showed moderate agreement (Cohen's κ: 0.61) and achieved AUCs of 0.86 and 0.82. CONCLUSION Our T2-weighted MRI radiomics model shows potential for distinguishing malignant from benign primary solid liver lesions. External validation indicated that the model is generalizable despite substantial MRI acquisition protocol differences. Pending further optimization and generalization, this model may aid radiologists in improving the diagnostic workup of patients with liver lesions.
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Affiliation(s)
- Martijn P A Starmans
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.P.A.S., W.J.N., S.K., M.G.T.).
| | - Razvan L Miclea
- Department of Radiology and Nuclear Medicine, Maastricht UMC+, Maastricht, the Netherlands (R.L.M.)
| | - Valerie Vilgrain
- Université de Paris, INSERM U 1149, CRI, Paris, France (V.V., M.R.); Département de Radiologie, Hôpital Beaujon, APHP.Nord, Clichy, France (V.V., M.R.)
| | - Maxime Ronot
- Université de Paris, INSERM U 1149, CRI, Paris, France (V.V., M.R.); Département de Radiologie, Hôpital Beaujon, APHP.Nord, Clichy, France (V.V., M.R.)
| | - Yvonne Purcell
- Department of Radiology, Hôpital Fondation Rothschild, Paris, France (Y.P.)
| | - Jef Verbeek
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, Belgium (J.V.); Department of Gastroenterology and Hepatology, Maastricht UMC+, Maastricht, the Netherlands (J.V.)
| | - Wiro J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.P.A.S., W.J.N., S.K., M.G.T.); Faculty of Applied Sciences, Delft University of Technology, the Netherlands (W.J.N.)
| | - Jan N M Ijzermans
- Department of Surgery, Erasmus MC, Rotterdam, the Netherlands (J.N.M.I.)
| | - Rob A de Man
- Department of Gastroenterology & Hepatology, Erasmus MC, Rotterdam, the Netherlands (R.A.d.M.)
| | - Michael Doukas
- Department of Pathology, Erasmus MC, Rotterdam, the Netherlands (M.D.)
| | - Stefan Klein
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.P.A.S., W.J.N., S.K., M.G.T.)
| | - Maarten G Thomeer
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.P.A.S., W.J.N., S.K., M.G.T.)
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Chai F, Ma Y, Feng C, Jia X, Cui J, Cheng J, Hong N, Wang Y. Prediction of macrotrabecular-massive hepatocellular carcinoma by using MR-based models and their prognostic implications. Abdom Radiol (NY) 2024; 49:447-457. [PMID: 38042762 DOI: 10.1007/s00261-023-04121-7] [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: 08/09/2023] [Revised: 10/29/2023] [Accepted: 11/03/2023] [Indexed: 12/04/2023]
Abstract
PURPOSE To evaluate the efficacy of MRI-based radiomics and clinical models in predicting MTM-HCC. Additionally, to investigate the ability of the radiomics model designed for MTM-HCC identification in predicting disease-free survival (DFS) in patients with HCC. METHODS A total of 336 patients who underwent oncological resection for HCC between June 2007 and March 2021 were included. 127 patients in Cohort1 were used for MTM-HCC identification, and 209 patients in Cohort2 for prognostic analyses. Radiomics analysis was performed using volumes of interest of HCC delineated on pre-operative MRI images. Radiomics and clinical models were developed using Random Forest algorithm in Cohort1 and a radiomics probability (RP) of MTM-HCC was obtained from the radiomics model. Based on the RP, patients in Cohort2 were divided into a RAD-MTM-HCC (RAD-M) group and a RAD-non-MTM-HCC (RAD-nM) group. Univariate and multivariate Cox regression analyses were employed to identify the independent predictors for DFS of patients in Cohort2. Kaplan-Meier curves were used to compare the DFS between different groups pf patients based on the predictors. RESULTS The radiomics model for identifying MTM-HCC showed AUCs of 0.916 (95% CI: 0.858-0.960) and 0.833 (95% CI: 0.675-0.935), and the clinical model showed AUCs of 0.760 (95% CI: 0.669-0.836) and 0.704 (95% CI: 0.532-0.843) in the respective training and validation sets. Furthermore, the radiomics biomarker RP, portal or hepatic vein tumor thrombus, irregular rim-like arterial phase hyperenhancement (IRE) and AFP were independent predictors of DFS in patients with HCC. The DFS of RAD-nM group was significantly higher than that of the RAD-M group (p < .001). CONCLUSION MR-based clinical and radiomic models have the potential to accurately diagnose MTM-HCC. Moreover, the radiomics signature designed to identify MTM-HCC also can be used to predict prognosis in patients with HCC, realizing the diagnostic and prognostic aims at the same time.
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Affiliation(s)
- Fan Chai
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China
| | - Yingteng Ma
- Department of Pathology, Peking University People's Hospital, Beijing, China
| | - Caizhen Feng
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China
| | - Xiaoxuan Jia
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China
| | - Jingjing Cui
- United Imaging Intelligence (Beijing) Co., Ltd, Beijing, China
| | - Jin Cheng
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China
| | - Nan Hong
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China
| | - Yi Wang
- Department of Radiology, Peking University People's Hospital, 11 Xizhimen South St., Xicheng District, Beijing, 100044, China.
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Ferrell LD, Kakar S, Terracciano LM, Wee A. Tumours and Tumour-Like Lesions. MACSWEEN'S PATHOLOGY OF THE LIVER 2024:842-946. [DOI: 10.1016/b978-0-7020-8228-3.00013-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2025]
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Brusset B, Jacquemin M, Teyssier Y, Roth GS, Sturm N, Roustit M, Bône A, Ghelfi J, Costentin CE, Decaens T. Radiological diagnosis of hepatocellular carcinoma does not preclude biopsy before treatment. JHEP Rep 2024; 6:100957. [PMID: 38234407 PMCID: PMC10792651 DOI: 10.1016/j.jhepr.2023.100957] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 01/19/2024] Open
Abstract
Background & Aims The diagnosis of hepatocellular carcinoma (HCC) in patients with cirrhosis relies on non-invasive criteria based on international guidelines. The advent of systemic therapies warrants reconsideration of the role of biopsy specimens in the diagnosis of HCC. Accordingly, we investigated the diagnostic performance of the LI-RADS 2018 and the AASLD 2011 criteria. Methods Consecutive patients with cirrhosis who underwent a biopsy for suspected HCC between 2015 and 2020 were included. The available imaging studies (computed tomography and/or magnetic resonance imaging) were blindly reviewed by two independent radiologists. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed for LI-RADS, AASLD, and biopsies. Results In total, 167 patients underwent both available biopsy and imaging. Of the 137 relevant biopsies, 114 patients had HCC (83.2%), 12 (9%) had non-HCC malignant lesions, and 11 (8%) had benign nodules. The PPV and NPV of the biopsies were 100% and 62%, respectively; 30 biopsies were non-contributive. The PPV and NPV of the LI-RADS categories were 89% and 32.8% for LR-5 and 85.5% and 54.5% for LR-4 + 5 + TIV, respectively. The PPV and NPV of the 2011 AASLD criteria were 93.2% and 35.6%, respectively. The interobserver kappa (k = 0.380) for the LR-5 categories was reasonable. Of 100 LR-5 nodules, 11 were misclassified, in particular one case was a colorectal metastasis, and two cases were cholangiocarcinomas, of which nine were identified through biopsy, whereas six were correctly classified according to LI-RADS (LR-M or LR-TIV). Fifty percent of macrotrabecular HCC and 48.4% of poorly differentiated HCC (Edmonson 3 and 4) were not classified as LR-5. Conclusions LI-RADS 2018 did not outperform the AASLD 2011 score as a non-invasive diagnosis of HCC. Tumor biopsy allowed restoration of an accurate diagnosis in 11% of LR-5 cases. A combined radiological and histological diagnosis should be considered mandatory for good treatment assessment. Impact and Implications Although biopsy is not required for hepatocellular carcinoma diagnosis when the LI-RADS criteria are met according to current guidelines, our study underscores the limits of radiology and the need for biopsy when hepatocellular carcinoma is suspected. Histological findings could change therapeutics of liver tumors even if only for a small proportion of patients. Histological proof of the type of cancer is a standard in oncology.
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Affiliation(s)
- Bleuenn Brusset
- Univ. Grenoble Alpes, Service d'hépato-gastroentérologie et d'oncologie digestive, CHU Grenoble Alpes, Grenoble, France
| | - Marion Jacquemin
- Univ. Grenoble Alpes, Service d'hépato-gastroentérologie et d'oncologie digestive, CHU Grenoble Alpes, Grenoble, France
| | - Yann Teyssier
- Radiology Department, Université Grenoble Alpes, CHU Grenoble Alpes, Grenoble, France
| | - Gaël S. Roth
- Univ. Grenoble Alpes, Service d'hépato-gastroentérologie et d'oncologie digestive, CHU Grenoble Alpes, Grenoble, France
- Institute for Advanced Biosciences-INSERM U1209/CNRS UMR, Université Grenoble Alpes, Grenoble, France
| | - Nathalie Sturm
- Anatomie et Cytologie Pathologiques, Université Grenoble Alpes, CHU Grenoble Alpes, Grenoble, France
| | - Matthieu Roustit
- Centre d’Investigation Clinique, Université Grenoble Alpes, CHU Grenoble Alpes, Grenoble, France
| | | | - Julien Ghelfi
- Radiology Department, Université Grenoble Alpes, CHU Grenoble Alpes, Grenoble, France
- Institute for Advanced Biosciences-INSERM U1209/CNRS UMR, Université Grenoble Alpes, Grenoble, France
| | - Charlotte E. Costentin
- Univ. Grenoble Alpes, Service d'hépato-gastroentérologie et d'oncologie digestive, CHU Grenoble Alpes, Grenoble, France
- Institute for Advanced Biosciences-INSERM U1209/CNRS UMR, Université Grenoble Alpes, Grenoble, France
| | - Thomas Decaens
- Univ. Grenoble Alpes, Service d'hépato-gastroentérologie et d'oncologie digestive, CHU Grenoble Alpes, Grenoble, France
- Institute for Advanced Biosciences-INSERM U1209/CNRS UMR, Université Grenoble Alpes, Grenoble, France
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He X, Li K, Wei R, Zuo M, Yao W, Zheng Z, He X, Fu Y, Li C, An C, Liu W. A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy. LA RADIOLOGIA MEDICA 2023; 128:1508-1520. [PMID: 37801197 PMCID: PMC10700409 DOI: 10.1007/s11547-023-01719-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/01/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patients' prognosis after hepatic arterial infusion chemotherapy (HAIC). METHODS From June 2018 to March 2020, 158 eligible patients with HCC who underwent surgery were retrospectively enrolled in MTM related cohorts, and 752 HCC patients who underwent HAIC were included in HAIC related cohorts during the same period. DLR features were extracted from dual-phase (arterial phase and venous phase) contrast-enhanced computed tomography (CECT) of the entire liver region. Then, an MDLR model was used for the simultaneous prediction of the MTM subtype and patient prognosis after HAIC. The MDLR model for prognostic risk stratification incorporated DLR signatures, clinical variables and MTM subtype. FINDINGS The predictive performance of the DLR model for the MTM subtype was 0.968 in the training cohort [TC], 0.912 in the internal test cohort [ITC] and 0.773 in the external test cohort [ETC], respectively. Multivariable analysis identified portal vein tumor thrombus (PVTT) (p = 0.012), HAIC response (p < 0.001), HAIC sessions (p < 0.001) and MTM subtype (p < 0.001) as indicators of poor prognosis. After incorporating DLR signatures, the MDLR model yielded the best performance among all models (AUC, 0.855 in the TC, 0.805 in the ITC and 0.792 in the ETC). With these variables, the MDLR model provided two risk strata for overall survival (OS) in the TC: low risk (5-year OS, 44.9%) and high risk (5-year OS, 4.9%). INTERPRETATION A tool based on MDLR was developed to consider that the MTM is an important prognosis factor for HCC patients. MDLR showed outstanding performance for the prognostic risk stratification of HCC patients who underwent HAIC and may help physicians with therapeutic decision making and surveillance strategy selection in clinical practice.
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Affiliation(s)
- Xuelei He
- School of Information Sciences and Technology, Northwest University, Xi'an, 710127, Shaanxi Province, People's Republic of China
| | - Kai Li
- Department of Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, Province Guangdong, People's Republic of China
| | - Ran Wei
- Department of Interventional Radiology and Vascular Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, Province Guangdong, People's Republic of China
| | - Mengxuan Zuo
- Department of Minimal Invasive Intervention, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651, Dongfeng East Road, Guangzhou, 510060, People's Republic of China
| | - Wang Yao
- Department of Interventional Radiology and Vascular Surgery, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, Province Guangdong, People's Republic of China
| | - Zechen Zheng
- Department of Interventional Therapy, Guangdong Provincial Hospital of Chinese, Medicine and Guangdong Provincial Academy of Chinese Medical Sciences, No. 111 Dade Road, Guangzhou, 510080, Guangdong, People's Republic of China
| | - Xiaowei He
- Department of Interventional Therapy, Guangdong Provincial Hospital of Chinese, Medicine and Guangdong Provincial Academy of Chinese Medical Sciences, No. 111 Dade Road, Guangzhou, 510080, Guangdong, People's Republic of China
| | - Yan Fu
- Department of Interventional Therapy, National Cancer Center/National Clinical, Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical, Sciences and Peking Union Medical College, Beijing, 100021, People's Republic of China
| | - Chengzhi Li
- Department of Interventional Radiology and Vascular Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, 510060, People's Republic of China.
| | - Chao An
- Department of Minimal Invasive Intervention, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, 651, Dongfeng East Road, Guangzhou, 510060, People's Republic of China.
| | - Wendao Liu
- Department of Interventional Therapy, Guangdong Provincial Hospital of Chinese, Medicine and Guangdong Provincial Academy of Chinese Medical Sciences, No. 111 Dade Road, Guangzhou, 510080, Guangdong, People's Republic of China.
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Dioguardi Burgio M, Garzelli L, Cannella R, Ronot M, Vilgrain V. Hepatocellular Carcinoma: Optimal Radiological Evaluation before Liver Transplantation. Life (Basel) 2023; 13:2267. [PMID: 38137868 PMCID: PMC10744421 DOI: 10.3390/life13122267] [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: 09/04/2023] [Revised: 10/27/2023] [Accepted: 11/24/2023] [Indexed: 12/24/2023] Open
Abstract
Liver transplantation (LT) is the recommended curative-intent treatment for patients with early or intermediate-stage hepatocellular carcinoma (HCC) who are ineligible for resection. Imaging plays a central role in staging and for selecting the best LT candidates. This review will discuss recent developments in pre-LT imaging assessment, in particular LT eligibility criteria on imaging, the technical requirements and the diagnostic performance of imaging for the pre-LT diagnosis of HCC including the recent Liver Imaging Reporting and Data System (LI-RADS) criteria, the evaluation of the response to locoregional therapy, as well as the non-invasive prediction of HCC aggressiveness and its impact on the outcome of LT. We will also briefly discuss the role of nuclear medicine in the pre-LT evaluation and the emerging role of artificial intelligence models in patients with HCC.
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Affiliation(s)
- Marco Dioguardi Burgio
- Department of Radiology, Hôpital Beaujon, AP-HP. Nord, 100 Boulevard du Général Leclerc, 92110 Clichy, France (V.V.)
- Centre de Recherche sur l’Inflammation, UMR1149, Université Paris Cité, 75018 Paris, France
| | - Lorenzo Garzelli
- Service d’Imagerie Medicale, Centre Hospitalier de Cayenne, Avenue des Flamboyants, Cayenne 97306, French Guiana
| | - Roberto Cannella
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University Hospital “Paolo Giaccone”, Via del Vespro 129, 90127 Palermo, Italy
| | - Maxime Ronot
- Department of Radiology, Hôpital Beaujon, AP-HP. Nord, 100 Boulevard du Général Leclerc, 92110 Clichy, France (V.V.)
- Centre de Recherche sur l’Inflammation, UMR1149, Université Paris Cité, 75018 Paris, France
| | - Valérie Vilgrain
- Department of Radiology, Hôpital Beaujon, AP-HP. Nord, 100 Boulevard du Général Leclerc, 92110 Clichy, France (V.V.)
- Centre de Recherche sur l’Inflammation, UMR1149, Université Paris Cité, 75018 Paris, France
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Yen YH, Kuo FY, Eng HL, Liu YW, Yong CC, Li WF, Wang CC, Lin CY. Tumor necrosis as a predictor of early tumor recurrence after resection in patients with hepatoma. PLoS One 2023; 18:e0292144. [PMID: 37972101 PMCID: PMC10653529 DOI: 10.1371/journal.pone.0292144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/02/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Tumor necrosis is a significant risk factor affecting patients' prognosis after liver resection (LR) for hepatocellular carcinoma (HCC). We aimed to develop a model with tumor necrosis as a variable to predict early tumor recurrence in HCC patients undergoing LR. MATERIALS AND METHODS Patients who underwent LR between 2010 and 2018 for newly diagnosed HCC but did not receive neoadjuvant therapy were enrolled in this retrospective study. Six predictive factors based on pathological features-tumor size > 5 cm, multiple tumors, high-grade tumor differentiation, tumor necrosis, microvascular invasion, and cirrhosis-were chosen a priori based on clinical relevance to construct a multivariate logistic regression model. The variables were always retained in the model. The impact of each variable on early tumor recurrence within one year of LR was estimated and visualized using a nomogram. The nomogram's performance was evaluated using calibration plots with bootstrapping. RESULTS Early tumor recurrence was observed in 161 (21.3%) patients. The concordance index of the proposed nomogram was 0.722. The calibration plots showed good agreement between nomogram predictions and actual observations of early recurrence. CONCLUSION We developed a nomogram incorporating tumor necrosis to predict early recurrence of HCC after LR. Its predictive accuracy is satisfactory.
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Affiliation(s)
- Yi-Hao Yen
- Division of Hepatogastroenterology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Fang-Ying Kuo
- Department of Pathology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hock-Liew Eng
- Department of Pathology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yueh-Wei Liu
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chee-Chien Yong
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Wei-Feng Li
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Chi Wang
- Liver Transplantation Center and Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chih-Yun Lin
- Biostatistics Center of Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
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Jiang H, Yang C, Chen Y, Wang Y, Wu Y, Chen W, Ronot M, Chernyak V, Fowler KJ, Bashir MR, Song B. Development of a Model including MRI Features for Predicting Advanced-stage Recurrence of Hepatocellular Carcinoma after Liver Resection. Radiology 2023; 309:e230527. [PMID: 37934100 DOI: 10.1148/radiol.230527] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.
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Affiliation(s)
- Hanyu Jiang
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Chongtu Yang
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Yidi Chen
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Yanshu Wang
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Yuanan Wu
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Weixia Chen
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Maxime Ronot
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Victoria Chernyak
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Kathryn J Fowler
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Mustafa R Bashir
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
| | - Bin Song
- From the Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China (H.J., C.Y., Y.C., Y. Wang, W.C., B.S.); JD.com, Beijing, China (Y. Wu); Université Paris Cité, UMR 1149, CRI, Paris, France (M.R.); Department of Radiology, Hôpital Beaujon, APHP.Nord, Clichy, France (M.R.); Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, University of California San Diego, San Diego, Calif (K.J.F.); Department of Radiology, Center for Advanced Magnetic Resonance in Medicine, and Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, NC (M.R.B.); and Department of Radiology, Sanya People's Hospital, Sanya, China (B.S.)
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Auer TA, Halskov S, Fehrenbach U, Nevermann NF, Pelzer U, Mohr R, Hamm B, Schöning W, Horst D, Ihlow J, Geisel D. Gd-EOB MRI for HCC subtype differentiation in a western population according to the 5 th edition of the World Health Organization classification. Eur Radiol 2023; 33:6902-6915. [PMID: 37115216 PMCID: PMC10511376 DOI: 10.1007/s00330-023-09669-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/29/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023]
Abstract
OBJECTIVES To investigate the value of gadoxetic acid (Gd-EOB)-enhanced magnetic resonance imaging (MRI) for noninvasive subtype differentiation of HCCs according to the 5th edition of the WHO Classification of Digestive System Tumors in a western population. METHODS This retrospective study included 262 resected lesions in 240 patients with preoperative Gd-EOB-enhanced MRI. Subtypes were assigned by two pathologists. Gd-EOB-enhanced MRI datasets were assessed by two radiologists for qualitative and quantitative imaging features, including imaging features defined in LI-RADS v2018 and area of hepatobiliary phase (HBP) iso- to hyperintensity. RESULTS The combination of non-rim arterial phase hyperenhancement with non-peripheral portal venous washout was more common in "not otherwise specified" (nos-ST) (88/168, 52%) than other subtypes, in particular macrotrabecular massive (mt-ST) (3/15, 20%), chromophobe (ch-ST) (1/8, 13%), and scirrhous subtypes (sc-ST) (2/9, 22%) (p = 0.035). Macrovascular invasion was associated with mt-ST (5/16, p = 0.033) and intralesional steatosis with steatohepatitic subtype (sh-ST) (28/32, p < 0.001). Predominant iso- to hyperintensity in the HBP was only present in nos-ST (16/174), sh-ST (3/33), and clear cell subtypes (cc-ST) (3/13) (p = 0.031). Associations were found for the following non-imaging parameters: age and sex, as patients with fibrolamellar subtype (fib-ST) were younger (median 44 years (19-66), p < 0.001) and female (4/5, p = 0.023); logarithm of alpha-fetoprotein (AFP) was elevated in the mt-ST (median 397 µg/l (74-5370), p < 0.001); type II diabetes mellitus was more frequent in the sh-ST (20/33, p = 0.027). CONCLUSIONS Gd-EOB-MRI reproduces findings reported in the literature for extracellular contrast-enhanced MRI and CT and may be a valuable tool for noninvasive HCC subtype differentiation. CLINICAL RELEVANCE STATEMENT Better characterization of the heterogeneous phenotypes of HCC according to the revised WHO classification potentially improves both diagnostic accuracy and the precision of therapeutic stratification for HCC. KEY POINTS • Previously reported imaging features of common subtypes in CT and MRI enhanced with extracellular contrast agents are reproducible with Gd-EOB-enhanced MRI. • While uncommon, predominant iso- to hyperintensity in the HBP was observed only in NOS, clear cell, and steatohepatitic subtypes. • Gd-EOB-enhanced MRI offers imaging features that are of value for HCC subtype differentiation according to the 5th edition of the WHO Classification of Digestive System Tumors.
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Affiliation(s)
- Timo A Auer
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Straße 2, 10178, Berlin, Germany.
| | - Sebastian Halskov
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Uli Fehrenbach
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Nora F Nevermann
- Department of Surgery - CVK/CCM, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Uwe Pelzer
- Department of Hematology, Oncology and Cancer Immunology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Raphael Mohr
- Department of Hepatology and Gastroenterology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Wenzel Schöning
- Department of Surgery - CVK/CCM, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - David Horst
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Jana Ihlow
- Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Dominik Geisel
- Department of Radiology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
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Trapani L, Beaufrère A, Hobeika C, Codjia T, Albuquerque M, Bouattour M, Lesurtel M, Cauchy F, Paradis V. Pathological overview of steatohepatitic hepatocellular carcinoma in a surgical series. Histopathology 2023; 83:526-537. [PMID: 37222200 DOI: 10.1111/his.14941] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/29/2023] [Accepted: 05/01/2023] [Indexed: 05/25/2023]
Abstract
AIMS According to the last WHO classification, steatohepatitic hepatocellular carcinoma (SH-HCC) is recognized as a distinct HCC subtype, even though a consensual definition is still lacking. The objectives of the study were to carefully describe the morphological features of SH-HCC and evaluate its impact on prognosis. METHODS AND RESULTS We conducted a single-centre retrospective study including 297 surgically resected HCC. Pathological features including SH criteria (steatosis, ballooning, Mallory-Denk bodies, fibrosis, and inflammation) were assessed. SH-HCC was defined by the presence of at least four of the five SH criteria and the SH component represented >50% of the tumour area. According to this definition, 39 (13%) HCC cases corresponded to SH-HCC and 30 cases (10%) corresponded to HCC with an SH component (<50%). SH criteria in SH-HCC and non-SH-HCC were distributed as follows: ballooning (100% versus 11%), fibrosis (100% versus 81%), inflammation (100% versus 67%), steatosis (92% versus 8%), and Mallory-Denk bodies (74% versus 3%). Inflammation markers (c-reactive protein [CRP] and serum amyloid A [SAA]) were significantly more expressed in SH-HCC compared to non-SH-HCC (82% versus 14%, P = <0.001). Five-year recurrence-free survival (RFS) and 5-year overall survival (OS) were similar for SH-HCC and non-SH-HCC (P = 0.413 and P = 0.866, respectively). The percentage of SH component does not impact OS and RFS. CONCLUSION We confirm in a large cohort the relatively high prevalence (13%) of SH-HCC. Ballooning is the most specific criteria for this subtype. The percentage of the SH component does not impact prognosis.
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Affiliation(s)
- Loïc Trapani
- Université Paris Cité, Paris, France
- AP-HP.Nord, Department of Pathology, FHU MOSAIC, Beaujon Hospital, Clichy, France
| | - Aurélie Beaufrère
- Université Paris Cité, Paris, France
- AP-HP.Nord, Department of Pathology, FHU MOSAIC, Beaujon Hospital, Clichy, France
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
| | - Christian Hobeika
- AP-HP, Department of HPB and digestive surgery, Pitié-Salpétrière Hospital, Paris, France
| | - Tatiana Codjia
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
- AP-HP.Nord, Department of HPB surgery, Beaujon Hospital, Clichy, France
| | - Miguel Albuquerque
- AP-HP.Nord, Department of Pathology, FHU MOSAIC, Beaujon Hospital, Clichy, France
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
| | - Mohamed Bouattour
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
- AP-HP.Nord, Department of Hepatology, Beaujon Hospital, Clichy, France
| | - Mickael Lesurtel
- Université Paris Cité, Paris, France
- AP-HP.Nord, Department of HPB surgery, Beaujon Hospital, Clichy, France
| | - François Cauchy
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
| | - Valérie Paradis
- Université Paris Cité, Paris, France
- AP-HP.Nord, Department of Pathology, FHU MOSAIC, Beaujon Hospital, Clichy, France
- Centre de Recherche sur l'Inflammation, INSERM UMR 1149, Paris, France
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Fujiwara N, Nakagawa H. Clinico-histological and molecular features of hepatocellular carcinoma from nonalcoholic fatty liver disease. Cancer Sci 2023; 114:3825-3833. [PMID: 37545384 PMCID: PMC10551597 DOI: 10.1111/cas.15925] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 07/07/2023] [Accepted: 07/25/2023] [Indexed: 08/08/2023] Open
Abstract
Patients with nonalcoholic fatty liver disease (NAFLD) continue to increase with the epidemics of obesity, and NAFLD is estimated to become the most prevalent etiology of hepatocellular carcinoma (HCC). Recently, NAFLD-HCC has been recognized to have clinico-histologically and molecularly distinct features from those from other etiologies, including a lower incidence rate of HCC and less therapeutic efficacy to immune checkpoint inhibitors (ICIs). Consistent with the clinical observations that up to 50% of NAFLD-HCC occurs in the absence of cirrhosis, the imbalance of pro- and antitumorigenic hepatic stellate cells termed as myHSC and cyHSC can contribute to the creation of an HCC-prone hepatic environment, independent of the absolute fibrosis abundance. Immune deregulations by accumulated metabolites in NAFLD-affected livers, such as a fatty-acid-induced loss of cytotoxic CD4 T cells serving for immune surveillance and "auto-aggressive" CXCR6+ CD8 T cells, may promote hepatocarcinogenesis and diminish therapeutic response to ICIs. Steatohepatitic HCC (SH-HCC), characterized by the presence of fat accumulation in tumor cells, ballooned tumor cells, Mallory-Denk body, interstitial fibrosis, and intratumor immune cell infiltration, may represent a metabolic reprogramming for adapting to a lipid-rich tumor microenvironment by downregulating CPT2 and leveraging its intermediates as an "oncometabolite." Genome-wide analyses suggested that SH-HCC may be more responsive to ICIs given its mutual exclusiveness with β-catenin mutation/activation that promotes immune evasion. Thus, further understanding of NAFLD-specific hepatocarcinogenesis and HCC would enable us to improve the current daily practice and eventually the prognoses of patients with NAFLD.
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Affiliation(s)
- Naoto Fujiwara
- Department of Gastroenterology and HepatologyGraduate School of Medicine, Mie UniversityTsu cityJapan
| | - Hayato Nakagawa
- Department of Gastroenterology and HepatologyGraduate School of Medicine, Mie UniversityTsu cityJapan
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Choi JH, Thung SN. Advances in Histological and Molecular Classification of Hepatocellular Carcinoma. Biomedicines 2023; 11:2582. [PMID: 37761023 PMCID: PMC10526317 DOI: 10.3390/biomedicines11092582] [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: 07/13/2023] [Revised: 09/06/2023] [Accepted: 09/08/2023] [Indexed: 09/29/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is a primary liver cancer characterized by hepatocellular differentiation. HCC is molecularly heterogeneous with a wide spectrum of histopathology. The prognosis of patients with HCC is generally poor, especially in those with advanced stages. HCC remains a diagnostic challenge for pathologists because of its morphological and phenotypic diversity. However, recent advances have enhanced our understanding of the molecular genetics and histological subtypes of HCC. Accurate diagnosis of HCC is important for patient management and prognosis. This review provides an update on HCC pathology, focusing on molecular genetics, histological subtypes, and diagnostic approaches.
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Affiliation(s)
- Joon Hyuk Choi
- Department of Pathology, Yeungnam University College of Medicine, Daegu 42415, Republic of Korea
| | - Swan N. Thung
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, 1468 Madison Avenue, New York, NY 10029, USA;
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Gerber TS, Witzel HR, Weinmann A, Bartsch F, Schindeldecker M, Galle PR, Lang H, Roth W, Ridder DA, Straub BK. Reduced Lipid Peroxidation Predicts Unfavorable Prognosis in Hepatocellular Carcinoma, but Not Intrahepatic Cholangiocarcinoma. Biomedicines 2023; 11:2471. [PMID: 37760911 PMCID: PMC10525544 DOI: 10.3390/biomedicines11092471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 08/31/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
Primary liver cancer, including hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), remains a significant contributor to cancer-related mortality worldwide. Oxidative stress and lipid peroxidation play a key role in chronic liver diseases and have been shown to be pivotal for tumor initiation and progression. 4-hydroxy-nonenal (4-HNE), one of the major mediators of oxidative stress and a well-established biomarker for lipid peroxidation, can act as a signal transducer, inducing inflammation and exerting carcinogenic effects. However, the role of 4-HNE in primary liver cancer remains poorly explored. In this study, we investigated 4-HNE levels in 797 liver carcinomas, including 561 HCC and 236 iCCA, by immunohistochemistry. We then correlated 4-HNE levels with comprehensive clinical data and survival outcomes. In HCC, lower expression levels of 4-HNE were associated with vascular invasion, a high tumor grade, a macrotrabecular-massive HCC subtype, and poor overall survival. Concerning iCCA, large duct iCCA showed significantly higher 4-HNE levels when compared to small duct iCCA. Yet, in iCCA, 4-HNE levels did not correlate with known prognostic parameters or survival outcomes. To conclude, in HCC but not in iCCA, low amounts of 4-HNE predict unfavorable survival outcomes and are associated with aggressive tumor behavior. These findings provide insights into the role of 4-HNE in liver cancer progression and may enable novel therapeutic strategies.
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Affiliation(s)
- Tiemo Sven Gerber
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
| | - Hagen Roland Witzel
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
| | - Arndt Weinmann
- Department of Internal Medicine, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (A.W.); (P.R.G.)
| | - Fabian Bartsch
- Department of General, Visceral and Transplant Surgery, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (F.B.); (H.L.)
| | - Mario Schindeldecker
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
- Tissue Biobank, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany
| | - Peter R. Galle
- Department of Internal Medicine, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (A.W.); (P.R.G.)
| | - Hauke Lang
- Department of General, Visceral and Transplant Surgery, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (F.B.); (H.L.)
| | - Wilfried Roth
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
| | - Dirk Andreas Ridder
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
| | - Beate Katharina Straub
- Institute of Pathology, University Medical Center of the Johannes Gutenberg University, 55131 Mainz, Germany; (T.S.G.); (H.R.W.); (M.S.); (W.R.); (D.A.R.)
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Kadi D, Yamamoto MF, Lerner EC, Jiang H, Fowler KJ, Bashir MR. Imaging prognostication and tumor biology in hepatocellular carcinoma. JOURNAL OF LIVER CANCER 2023; 23:284-299. [PMID: 37710379 PMCID: PMC10565542 DOI: 10.17998/jlc.2023.08.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/26/2023] [Accepted: 08/29/2023] [Indexed: 09/16/2023]
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.
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Affiliation(s)
- Diana Kadi
- Department of Radiology, Duke University Medical Center, Durham, NC, USA
| | - Marilyn F. Yamamoto
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Emily C. Lerner
- Department of Radiology, Duke University School of Medicine, Durham, NC, USA
| | - Hanyu Jiang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Kathryn J. Fowler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Mustafa R. Bashir
- Department of Radiology, Duke University, Durham, NC, USA
- Division of Hepatology, Department of Medicine, Duke University, Durham, NC, USA
- Center for Advanced Magnetic Resonance Development, Duke University, Durham, NC, USA
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46
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Lominadze Z, Shaik MR, Choi D, Zaffar D, Mishra L, Shetty K. Hepatocellular Carcinoma Genetic Classification. Cancer J 2023; 29:249-258. [PMID: 37796642 PMCID: PMC10686192 DOI: 10.1097/ppo.0000000000000682] [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] [Indexed: 10/07/2023]
Abstract
ABSTRACT Hepatocellular carcinoma (HCC) represents a significant global burden, with management complicated by its heterogeneity, varying presentation, and relative resistance to therapy. Recent advances in the understanding of the genetic, molecular, and immunological underpinnings of HCC have allowed a detailed classification of these tumors, with resultant implications for diagnosis, prognostication, and selection of appropriate treatments. Through the correlation of genomic features with histopathology and clinical outcomes, we are moving toward a comprehensive and unifying framework to guide our diagnostic and therapeutic approach to HCC.
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Affiliation(s)
- Zurabi Lominadze
- Division of Gastroenterology and Hepatology, University of Maryland School of Medicine
| | | | - Dabin Choi
- Department of Medicine, University of Maryland Medical Center
| | - Duha Zaffar
- Department of Medicine, University of Maryland Midtown Medical Center
| | - Lopa Mishra
- Feinstein Institutes for Medical Research and Cold Spring Harbor Laboratory; Divisions of Gastroenterology and Hepatology, Northwell Health
| | - Kirti Shetty
- Division of Gastroenterology and Hepatology, University of Maryland School of Medicine
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Ishteyaque S, Yadav KS, Verma S, Washimkar KR, Mugale MN. CYP2E1 triggered GRP78/ATF6/CHOP signaling axis inhibit apoptosis and promotes progression of hepatocellular carcinoma. Arch Biochem Biophys 2023; 745:109701. [PMID: 37499993 DOI: 10.1016/j.abb.2023.109701] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/09/2023] [Accepted: 07/24/2023] [Indexed: 07/29/2023]
Abstract
Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. Cytochrome P450 2E1 (CYP2E1) is an enzyme, primarily involved in the metabolism of xenobiotics and procarcinogens. The present study was designed to investigate the potential role of CYP2E1 triggered endoplasmic reticulum stress in the progression of HCC through inhibition of apoptosis. In vitro CYP2E1 promotes HepG2 cell migration, reduced chromatin condensation, enhanced intracellular ROS accumulation and induce cell cycle progression. Conversely this effect was averted by CYP2E1 siRNA, selective inhibitor Diallyl sulphide (DAS) and antioxidants (vitamin C and E). In vivo Diethylnitrosamine (DEN) induced HCC rats showed decreased body weight and increased relative liver weight. Moreover, macro trabecular-massive HCC (MTM-HCC) histological subtyping showed pathological features like well-differentiated tumors, micro-trabecular and pseudo glandular patterns, megakaryocytes and cholestasis. Masson's trichrome staining revealed an intensive accumulation of collagen fibers in the extracellular matrix (ECM). Increased CYP2E1, VEGF and PCNA enhance the carcinogenicity as revealed in immunohistochemistry results. Immunoblot analysis showed reduced expression of copper-zinc superoxide dismutase (CuZnSOD) and manganese superoxide dismutase (MnSOD) in cytosolic as well as mitochondrial fraction of rat liver tissue respectively. Also, increased level of CYP2E1 stimulated the upregulation of unfolded proteins response (UPR) and ER stress-related proteins such as Glucose regulatory protein 78 (GRP78), activating transcription factor 6 (ATF6) and CCAAT enhancer-binding protein (C/EBP) homologous protein (CHOP). Meanwhile, CYP2E1 stimulated ER-stress reduces BCL2 and downregulates the cleaved caspase 3 thus suppresses apoptosis. in. Furthermore, immunofluorescence revealed increased expression level of α-SMA in the HCC rat liver tissue. The level of CYP2E1 mRNA was significantly increased. Altogether, these findings indicate that CYP2E1 has a dynamic role in the pathogenesis of HCC and might be a budding agent in liver carcinogenesis therapy.
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Affiliation(s)
- Sharmeen Ishteyaque
- Division of Cancer Biology CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow, 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Karan Singh Yadav
- Division of Cancer Biology CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow, 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Smriti Verma
- Division of Cancer Biology CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow, 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Kaveri R Washimkar
- Division of Cancer Biology CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow, 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Madhav Nilakanth Mugale
- Division of Cancer Biology CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow, 226031, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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Spârchez Z, Crăciun R, Nenu I, Mocan LP, Spârchez M, Mocan T. Refining Liver Biopsy in Hepatocellular Carcinoma: An In-Depth Exploration of Shifting Diagnostic and Therapeutic Applications. Biomedicines 2023; 11:2324. [PMID: 37626820 PMCID: PMC10452389 DOI: 10.3390/biomedicines11082324] [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: 07/26/2023] [Revised: 08/17/2023] [Accepted: 08/19/2023] [Indexed: 08/27/2023] Open
Abstract
The field of hepatocellular carcinoma (HCC) has faced significant change on multiple levels in the past few years. The increasing emphasis on the various HCC phenotypes and the emergence of novel, specific therapies have slowly paved the way for a personalized approach to primary liver cancer. In this light, the role of percutaneous liver biopsy of focal lesions has shifted from a purely confirmatory method to a technique capable of providing an in-depth characterization of any nodule. Cancer subtype, gene expression, the mutational profile, and tissue biomarkers might soon become widely available through biopsy. However, indications, expectations, and techniques might suffer changes as the aim of the biopsy evolves from providing minimal proof of the disease to high-quality specimens for extensive analysis. Consequently, a revamped position of tissue biopsy is expected in HCC, following the reign of non-invasive imaging-only diagnosis. Moreover, given the advances in techniques that have recently reached the spotlight, such as liquid biopsy, concomitant use of all the available methods might gather just enough data to improve therapy selection and, ultimately, outcomes. The current review aims to discuss the changing role of liver biopsy and provide an evidence-based rationale for its use in the era of precision medicine in HCC.
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Affiliation(s)
- Zeno Spârchez
- Department of Gastroenterology, “Prof. Dr. O. Fodor” Regional Institute of Gastroenterology and Hepatology, 400162 Cluj-Napoca, Romania; (Z.S.); (I.N.); (T.M.)
- Department of Internal Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400162 Cluj-Napoca, Romania
| | - Rareș Crăciun
- Department of Gastroenterology, “Prof. Dr. O. Fodor” Regional Institute of Gastroenterology and Hepatology, 400162 Cluj-Napoca, Romania; (Z.S.); (I.N.); (T.M.)
- Department of Internal Medicine, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400162 Cluj-Napoca, Romania
| | - Iuliana Nenu
- Department of Gastroenterology, “Prof. Dr. O. Fodor” Regional Institute of Gastroenterology and Hepatology, 400162 Cluj-Napoca, Romania; (Z.S.); (I.N.); (T.M.)
- Department of Physiology, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania
| | - Lavinia Patricia Mocan
- Department of Histology, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400349 Cluj-Napoca, Romania;
| | - Mihaela Spârchez
- 2nd Pediatric Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, 400124 Cluj-Napoca, Romania;
| | - Tudor Mocan
- Department of Gastroenterology, “Prof. Dr. O. Fodor” Regional Institute of Gastroenterology and Hepatology, 400162 Cluj-Napoca, Romania; (Z.S.); (I.N.); (T.M.)
- UBBMed Department, Babeș-Bolyai University, 400349 Cluj-Napoca, Romania
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Li M, Fan Y, You H, Li C, Luo M, Zhou J, Li A, Zhang L, Yu X, Deng W, Zhou J, Zhang D, Zhang Z, Chen H, Xiao Y, Huang B, Wang J. Dual-Energy CT Deep Learning Radiomics to Predict Macrotrabecular-Massive Hepatocellular Carcinoma. Radiology 2023; 308:e230255. [PMID: 37606573 DOI: 10.1148/radiol.230255] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
Background It is unknown whether the additional information provided by multiparametric dual-energy CT (DECT) could improve the noninvasive diagnosis of the aggressive macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC). Purpose To evaluate the diagnostic performance of dual-phase contrast-enhanced multiparametric DECT for predicting MTM HCC. Materials and Methods Patients with histopathologic examination-confirmed HCC who underwent contrast-enhanced DECT between June 2019 and June 2022 were retrospectively recruited from three independent centers (center 1, training and internal test data set; centers 2 and 3, external test data set). Radiologic features were visually analyzed and combined with clinical information to establish a clinical-radiologic model. Deep learning (DL) radiomics models were based on DL features and handcrafted features extracted from virtual monoenergetic images and material composition images on dual phase using binary least absolute shrinkage and selection operators. A DL radiomics nomogram was developed using multivariable logistic regression analysis. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC), and the log-rank test was used to analyze recurrence-free survival. Results A total of 262 patients were included (mean age, 54 years ± 12 [SD]; 225 men [86%]; training data set, n = 146 [56%]; internal test data set, n = 35 [13%]; external test data set, n = 81 [31%]). The DL radiomics nomogram better predicted MTM than the clinical-radiologic model (AUC = 0.91 vs 0.77, respectively, for the training set [P < .001], 0.87 vs 0.72 for the internal test data set [P = .04], and 0.89 vs 0.79 for the external test data set [P = .02]), with similar sensitivity (80% vs 87%, respectively; P = .63) and higher specificity (90% vs 63%; P < .001) in the external test data set. The predicted positive MTM groups based on the DL radiomics nomogram had shorter recurrence-free survival than predicted negative MTM groups in all three data sets (training data set, P = .04; internal test data set, P = .01; and external test data set, P = .03). Conclusion A DL radiomics nomogram derived from multiparametric DECT accurately predicted the MTM subtype in patients with HCC. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chu and Fishman in this issue.
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Affiliation(s)
- Mengsi Li
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Yaheng Fan
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Huayu You
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Chao Li
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Ma Luo
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Jing Zhou
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Anqi Li
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Lina Zhang
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Xiao Yu
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Weiwei Deng
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Jinhui Zhou
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Dingyue Zhang
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Zhongping Zhang
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Haimei Chen
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Yuanqiang Xiao
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Bingsheng Huang
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
| | - Jin Wang
- From the Departments of Radiology (M. Li, C.L., A.L., L.Z., Jinhui Zhou, D.Z., H.C., Y.X., J.W.) and Pathology (Jing Zhou), The Third Affiliated Hospital, Sun Yat-Sen University, No. 600 Tianhe Rd, Guangzhou, Guangdong, 510630, People's Republic of China; Medical AI Laboratory, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, People's Republic of China (Y.F., B.H.); Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China (H.Y.); Department of Radiology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China (M. Luo); and Department of Clinical Science, Philips Healthcare China, Shanghai, People's Republic of China (X.Y., W.D., Z.Z.)
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Hwang YJ, Bae JS, Lee Y, Hur BY, Lee DH, Kim H. Classification of microvascular invasion of hepatocellular carcinoma: correlation with prognosis and magnetic resonance imaging. Clin Mol Hepatol 2023; 29:733-746. [PMID: 37157775 PMCID: PMC10366800 DOI: 10.3350/cmh.2023.0034] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/17/2023] [Accepted: 05/06/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND/AIMS The microvascular invasion (MVI) of hepatocellular carcinoma (HCC) involves a wide histological spectrum, and it is unclear whether the degree of MVI correlates with patient prognosis or imaging findings. Here, we evaluate the prognostic value of MVI classification and analyze the radiologic features predictive of MVI. METHODS Using a retrospective cohort of 506 patients with resected solitary HCCs, the histological and imaging features of MVI were reviewed and correlated with clinical data. RESULTS MVI-positive HCCs invading ≥5 vessels or those with ≥50 invaded tumor cells were significantly associated with decreased overall survival (OS). The 5-year OS, recurrence-free survival (RFS), and beyond Milan criteria RFS rates were significantly poorer in patients with severe MVI compared with those with mild or no MVI. Severe MVI was a significant independent predictive factor for OS (odds ratio [OR], 2.962; p<0.001), RFS (OR, 1.638; p=0.002), and beyond Milan criteria RFS (OR, 2.797; p<0.001) on multivariable analysis. On MRI, non-smooth tumor margins (OR, 2.224; p=0.023) and satellite nodules (OR, 3.264; p<0.001) were independently associated with the severe-MVI group on multivariable analysis. Both non-smooth tumor margins and satellite nodules were associated with worse 5-year OS, RFS, and beyond Milan criteria RFS. CONCLUSION Histologic risk classification of MVI according to the number of invaded microvessels and invading carcinoma cells was a valuable predictor of prognosis in HCC patients. Non-smooth tumor margin and satellite nodules were significantly associated with severe MVI and poor prognosis.
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Affiliation(s)
- Yoon Jung Hwang
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Jae Seok Bae
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Youngeun Lee
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Bo Yun Hur
- Department of Radiology, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Dong Ho Lee
- Department of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Haeryoung Kim
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
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