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Yang Q, Zhou J, Luo B, Zheng R, Liao J, Tang L, Cheng W, Jing X, Cai W, Cheng Z, Liu F, Han Z, Yu X, Yu J, Liang P. Non-radiomics imaging (US-CEUS) features and clinical text features: correlation with microvascular invasion and tumor grading in hepatocellular carcinoma. Abdom Radiol (NY) 2025; 50:2476-2493. [PMID: 39607454 DOI: 10.1007/s00261-024-04659-0] [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: 07/09/2024] [Revised: 10/25/2024] [Accepted: 10/26/2024] [Indexed: 11/29/2024]
Abstract
OBJECTIVES To predict microvascular invasion (MVI) status and tumor grading of hepatocellular carcinoma (HCC) by evaluating preoperative non-radiomics ultrasound and contrast-enhanced ultrasound (US-CEUS) features and determine the influences of MVI/tumor grading on the category of CEUS LI-RADS for HCC. METHODS A total of 506 HCC patients who underwent preoperative US-CEUS examinations from 8 hospitals between July 2020 and June 2023 were enrolled. According to the MVI status, all the patients were classified, and HCC differentiation was assessed by using Edmondson-Steiner (ES) grading: MVI-negative (M0) and low-grade ES (GI/II) (MN-L, n = 297) and MVI-positive (M1/M2) and/or high-grade ES (GIII/IV) (MP-H, n = 209). Stratified analysis was performed based on fibrosis stage and tumor size. RESULTS The results proved that MN-L HCC was more frequently classified into the LR-5 category (p = 0.034), while MP-H HCC was more frequently classified into the LR-TIV (p = 0.010). The heterogeneously arterial phase hyperenhancement (APHE) is significantly correlated with MVI(+)/high grade-ES (p = 0.003). Compared with MN-L HCC, the onset of washout was earlier, washout rate was higher, and tumor-invasion border was larger (all p < 0.01) in MP-H HCC. In addition, fibrosis stage and tumor size significantly influenced the onset of washout and washout rate of HCC (all p < 0.01). The tumor-invasion border was only positively correlated with tumor size (p < 0.001) rather than fibrosis stage (p > 0.05). CONCLUSIONS MVI status and tumor grading influence the classification of LR-5 and LR-TIV. Heterogeneous APHE, higher washout rate, earlier onset of washout (≤65 s), larger tumor-invasion border (≥3 mm) and higher alpha fetoprotein level indicate the presence of MVI and/or high-grade ES.
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Affiliation(s)
- Qi Yang
- Chinese PLA General Hospital, Beijing, China
- Peking University Shenzhen Hospital, Shenzhen, China
| | - Jianhua Zhou
- Sun Yat-sen University Cancer Center, Guangzhou, China
- Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Baoming Luo
- Sun Yat-sen Memorial Hospital, Guangzhou, China
| | - Rongqin Zheng
- Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | | | - Lina Tang
- Fujian Provincial Cancer Hospital, Fuzhou, China
| | - Wen Cheng
- Harbin Medical University Cancer Hospital, Harbin, China
| | - Xiang Jing
- Tianjin Third Central Hospital, Tianjin, China
| | - Wenjia Cai
- Chinese PLA General Hospital, Beijing, China
| | | | - Fangyi Liu
- Chinese PLA General Hospital, Beijing, China
| | - Zhiyu Han
- Chinese PLA General Hospital, Beijing, China
| | - Xiaoling Yu
- Chinese PLA General Hospital, Beijing, China
| | - Jie Yu
- Chinese PLA General Hospital, Beijing, China
| | - Ping Liang
- Chinese PLA General Hospital, Beijing, China.
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Liu Q, Li X, Yang K, Sun S, Xu X, Qu K, Xiao J, Liu C, Yu H, Lu Y, Qu J, Zhang Y, Zhang Y. Liver tumor imaging staging: a multi-institutional study of a preoperative staging tool for hepatocellular carcinoma. Abdom Radiol (NY) 2024:10.1007/s00261-024-04661-6. [PMID: 39939542 DOI: 10.1007/s00261-024-04661-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2024] [Revised: 10/25/2024] [Accepted: 10/26/2024] [Indexed: 02/14/2025]
Abstract
BACKGROUND & AIMS The current staging system has limitations in preoperatively assessing hepatocellular carcinoma (HCC) and in precise detailed treatment allocation. This study aims to propose a new Liver Tumor Imaging Staging (LTIS) method for HCC. METHODS 1295 patients who underwent CT or MRI and curative liver resection during January 2012 and October 2020 were retrospectively recruited from three independent institutions. All images were interpreted by two abdominal and a board-certified radiologist. LTIS was designed to discriminate low-grade (absence of microvascular invasion [MVI] and Edmondson-Steiner grade III/IV), intermediate (MVI + or Edmondson-Steiner grade III/IV but not both) and high-grade HCC (MVI + and Edmondson-Steiner grade III/IV) upon CT and MRI. Model was constructed in 578 derivation cohort (center 1) and validated in internal center 1 test cohort (n = 291), and external center 2 (n = 226) and center 3 (n = 200), respectively. Cronbach's alpha statistics were determined to assess interobserver agreement. Net clinical benefit of LTIS on recurrence-free survival (RFS) and overall survival (OS) was analyzed with a Cox proportional hazards model. RESULTS LTIS shows good inter-reader agreements in both CT and MRI datasets, with a Cronbach's alpha coefficient of 0.86 and 0.85, respectively. In independent test, LTIS achieved agreement of 73.2% (281/384), 18.9% (100/528), and 69.2% (265/383) for determining low, intermediate, and high-grade HCCs with "ground truth" results. In the Cox analysis, LTIS was comparable to "ground truth" grade for predicting RFS (hazards ratio (HR), 1.30 vs. ground truth grade, 1.36 and 1.56) and OS (HR, 1.76 vs. ground truth grade, 2.00 and 3.03) of patients after surgery. In patients conventionally classified as having low-grade tumors (serum α-fetoprotein < 400 ng/mL, stage T1), 47.4% and 35.6% were reclassified as high-grade tumors upon LTIS restaging. The resulting LTIS subgroups showed a significant difference in RFS and OS at Kaplan-Meier analysis (Log-rank test, p < 0.001). CONCLUSION LTIS provides a potential noninvasive way to precisely stage HCC using CT and MRI.
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Affiliation(s)
- Qiupng Liu
- Department of Radiology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, China
| | - Xiang Li
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - KaiLan Yang
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - ShuWen Sun
- Department of Radiology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, China
| | - Xun Xu
- Department of Radiology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, China
| | - Kai Qu
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jiaqi Xiao
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chenyue Liu
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - HangQi Yu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China
| | - YinYing Lu
- PLA General Hospital, Beijing, China
- Guangdong Key Laboratory of Epigenetics, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - JinRong Qu
- Department of Radiology, Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, China.
| | - YuDong Zhang
- Department of Radiology, Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital, Nanjing, China.
| | - Yuelang Zhang
- Department of Radiology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Kim NR, Bae H, Hwang HS, Han DH, Kim KS, Choi JS, Park MS, Choi GH. Preoperative Prediction of Microvascular Invasion with Gadoxetic Acid-Enhanced Magnetic Resonance Imaging in Patients with Single Hepatocellular Carcinoma: The Implication of Surgical Decision on the Extent of Liver Resection. Liver Cancer 2024; 13:181-192. [PMID: 38751555 PMCID: PMC11095589 DOI: 10.1159/000531786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 06/26/2023] [Indexed: 05/18/2024] Open
Abstract
Introduction Microvascular invasion (MVI) is one of the most important prognostic factors for hepatocellular carcinoma (HCC) recurrence, but its application in preoperative clinical decisions is limited. This study aimed to identify preoperative predictive factors for MVI in HCC and further evaluate oncologic outcomes of different types and extents of hepatectomy according to stratified risk of MVI. Methods Patients with surgically resected single HCC (≤5 cm) who underwent preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI) were included in a single-center retrospective study. Two radiologists reviewed the images with no clinical, pathological, or prognostic information. Significant predictive factors for MVI were identified using logistic regression analysis against pathologic MVI and used to stratify patients. In the subgroup analysis, long-term outcomes of the stratified patients were analyzed using the Kaplan-Meier method with log-rank test and compared between anatomical and nonanatomical or major and minor resection. Results A total of 408 patients, 318 men and 90 women, with a mean age of 56.7 years were included. Elevated levels of tumor markers (alpha-fetoprotein [α-FP] ≥25 ng/mL and PIVKA-II ≥40 mAU/mL) and three MRI features (tumor size ≥3 cm, non-smooth tumor margin, and arterial peritumoral enhancement) were independent predictive factors for MVI. As the MVI risk increased from low (no predictive factor) and intermediate (1-2 factors) to high-risk (3-4 factors), recurrence-free and overall survival of each group significantly decreased (p = 0.001). In the high MVI risk group, 5-year cumulative recurrence rate was significantly lower in patients who underwent major compared to minor hepatectomy (26.6 vs. 59.8%, p = 0.027). Conclusion Tumor markers and MRI features can predict the risk of MVI and prognosis after hepatectomy. Patients with high MVI risk had the worst prognosis among the three groups, and major hepatectomy improved long-term outcomes in these high-risk patients.
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Affiliation(s)
- Na Reum Kim
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Severance Hospital, Seoul, Republic of Korea
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Heejin Bae
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Seoul, Republic of Korea
| | - Hyeo Seong Hwang
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dai Hoon Han
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Severance Hospital, Seoul, Republic of Korea
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kyung Sik Kim
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Severance Hospital, Seoul, Republic of Korea
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin Sub Choi
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Severance Hospital, Seoul, Republic of Korea
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Mi-Suk Park
- Department of Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Seoul, Republic of Korea
| | - Gi Hong Choi
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Severance Hospital, Seoul, Republic of Korea
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Seoul, Republic of Korea
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Li J, Ma Y, Yang C, Qiu G, Chen J, Tan X, Zhao Y. Radiomics analysis of R2* maps to predict early recurrence of single hepatocellular carcinoma after hepatectomy. Front Oncol 2024; 14:1277698. [PMID: 38463221 PMCID: PMC10920317 DOI: 10.3389/fonc.2024.1277698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 02/09/2024] [Indexed: 03/12/2024] Open
Abstract
OBJECTIVES This study aimed to evaluate the effectiveness of radiomics analysis with R2* maps in predicting early recurrence (ER) in single hepatocellular carcinoma (HCC) following partial hepatectomy. METHODS We conducted a retrospective analysis involving 202 patients with surgically confirmed single HCC having undergone preoperative magnetic resonance imaging between 2018 and 2021 at two different institutions. 126 patients from Institution 1 were assigned to the training set, and 76 patients from Institution 2 were assigned to the validation set. A least absolute shrinkage and selection operator (LASSO) regularization was conducted to operate a logistic regression, then features were identified to construct a radiomic score (Rad-score). Uni- and multi-variable tests were used to assess the correlations of clinicopathological features and Rad-score with ER. We then established a combined model encompassing the optimal Rad-score and clinical-pathological risk factors. Additionally, we formulated and validated a predictive nomogram for predicting ER in HCC. The nomogram's discrimination, calibration, and clinical utility were thoroughly evaluated. RESULTS Multivariable logistic regression revealed the Rad-score, microvascular invasion (MVI), and α fetoprotein (AFP) level > 400 ng/mL as significant independent predictors of ER in HCC. We constructed a nomogram based on these significant factors. The areas under the receiver operator characteristic curve of the nomogram and precision-recall curve were 0.901 and 0.753, respectively, with an F1 score of 0.831 in the training set. These values in the validation set were 0.827, 0.659, and 0.808. CONCLUSION The nomogram that integrates the radiomic score, MVI, and AFP demonstrates high predictive efficacy for estimating the risk of ER in HCC. It facilitates personalized risk classification and therapeutic decision-making for HCC patients.
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Affiliation(s)
- Jia Li
- Department of Oncology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Yunhui Ma
- Department of Oncology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Chunyu Yang
- Department of Radiology, The First School of Clinical Medicine, Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Ganbin Qiu
- Imaging Department of Zhaoqing Medical College, Zhaoqing, China
| | - Jingmu Chen
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Xiaoliang Tan
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Yue Zhao
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
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Li J, Su X, Xu X, Zhao C, Liu A, Yang L, Song B, Song H, Li Z, Hao X. Preoperative prediction and risk assessment of microvascular invasion in hepatocellular carcinoma. Crit Rev Oncol Hematol 2023; 190:104107. [PMID: 37633349 DOI: 10.1016/j.critrevonc.2023.104107] [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: 05/24/2023] [Accepted: 08/22/2023] [Indexed: 08/28/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.
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Affiliation(s)
- Jian Li
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China
| | - Xin Su
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China
| | - Xiao Xu
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China
| | - Changchun Zhao
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China
| | - Ang Liu
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China; Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China
| | - Liwen Yang
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China
| | - Baoling Song
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China
| | - Hao Song
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China
| | - Zihan Li
- The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China
| | - Xiangyong Hao
- Department of General Surgery, Gansu Provincial Hospital, Lanzhou 730000, China.
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Wu F, Sun H, Shi Z, Zhou C, Huang P, Xiao Y, Yang C, Zeng M. Estimating Microvascular Invasion in Patients with Resectable Multinodular Hepatocellular Carcinoma by Using Preoperative Contrast-Enhanced MRI: Establishment and Validation of a Risk Score. J Hepatocell Carcinoma 2023; 10:1143-1156. [PMID: 37492267 PMCID: PMC10364817 DOI: 10.2147/jhc.s410237] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/07/2023] [Indexed: 07/27/2023] Open
Abstract
Objective To determine the preoperative clinicoradiological factors to predict microvascular invasion (MVI) in patients with resectable multinodular hepatocellular carcinoma (mHCC), and further to establish and validate a stratified risk scoring system. Methods Two hundred and seventy-three patients with pathologically confirmed mHCC (≥2 lesions) without major vascular invasion and biliary tract tumor thrombosis, who underwent preoperative contrast-enhanced MRI and hepatectomy, were consecutively enrolled (training/validation cohort=193/80). Preoperative clinicoradiological variables were collected and analyzed. The multivariable logistic regression was performed to determine the independent predictors of MVI and create a risk score system. The C-index, calibration curve and decision curve were used to evaluate the performance of the risk score. A risk score-based prognostic stratification system was performed in mHCC patients. The risk score system was further verified in the validation cohort. Results AFP > 400 ng/mL, presence of satellite nodule, mosaic architecture and increased total tumor diameter were independent predictors of MVI while fat in mass was an independent protective factor of MVI. The risk score yielded satisfactory C-index values (training/validation cohort: 0.777/0.758) and fitted well in calibration curves. Decision curve analysis further confirmed its clinical utility. Based on the risk score, mHCC patients were stratified into high-/low-MVI-risk subgroups with significantly different recurrence-free survival (both P < 0.001). Conclusion The presented risk score incorporating clinicoradiological parameters could stratify mHCC patients into high-risk and low-risk subgroups and predict prognosis in patients with resectable mHCC.
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Affiliation(s)
- Fei Wu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Haitao Sun
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Zhang Shi
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Changwu Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Shanghai Institute of Medical Imaging, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Peng Huang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Yuyao Xiao
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
- Shanghai Institute of Medical Imaging, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China
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Jiang T, He S, Yang H, Dong Y, Yu T, Luo Y, Jiang X. Multiparametric MRI-based radiomics for the prediction of microvascular invasion in hepatocellular carcinoma. Acta Radiol 2023; 64:456-466. [PMID: 35354318 DOI: 10.1177/02841851221080830] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is essential in obtaining a successful surgical treatment, in decreasing recurrence, and in improving survival. PURPOSE To investigate the value of multiparametric magnetic resonance imaging (MRI)-based radiomics in the prediction of peritumoral MVI in HCC. MATERIAL AND METHODS A total of 102 patient with pathologically proven HCC after surgical resection from June 2014 to March 2018 were enrolled in this retrospective study. Histological analysis of resected specimens confirmed positive MVI in 48 patients and negative MVI in 54 patients. Radiomics features were extracted from four MRI sequences and selected with the least absolute shrinkage and selection operator (LASSO) regression and used to analyze the tumoral and peritumoral regions for MVI. Univariate logistic regression was employed to identify the most important clinical factors, which were integrated with the radiomics signature to develop a nomogram. RESULTS In total, 11 radiomics features were selected and used to build the radiomics signature. The serum level of alpha-fetoprotein was identified as the clinical factor with the highest predictive value. The developed nomogram achieved the highest AUC in predicting MVI status. The decision curve analysis confirmed the potential clinical utility of the proposed nomogram. CONCLUSION The multiparametric MRI-based radiomics nomogram is a promising tool for the preoperative diagnosis of peritumoral MVI in HCCs and helps determine the appropriate medical or surgical therapy.
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Affiliation(s)
- Tao Jiang
- Department of Biomedical Engineering, 159407China Medical University, Shenyang, PR China
| | - Shuai He
- Department of Radiology, 74665Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, PR China
| | - Huazhe Yang
- Department of Biophysics, School of Fundamental Sciences, 159407China Medical University, Shenyang, PR China
| | - Yue Dong
- Department of Radiology, 74665Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, PR China
| | - Tao Yu
- Department of Radiology, 74665Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, PR China
| | - Yahong Luo
- Department of Radiology, 74665Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, PR China
| | - Xiran Jiang
- Department of Biomedical Engineering, 159407China Medical University, Shenyang, PR China
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Combining Preoperative Clinical and Imaging Characteristics to Predict MVI in Hepatitis B Virus-Related Combined Hepatocellular Carcinoma and Cholangiocarcinoma. J Pers Med 2023; 13:jpm13020246. [PMID: 36836479 PMCID: PMC9968216 DOI: 10.3390/jpm13020246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/23/2023] [Accepted: 01/28/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Combined hepatocellular carcinoma and cholangiocarcinoma (cHCC-CCA) is a rare form of primary liver malignancy. Microvascular invasion (MVI) indicates poor postsurgical prognosis in cHCC-CCA. The objective of this study was to investigate preoperative predictors of MVI in hepatitis B virus (HBV) -related cHCC-CCA patients. METHODS A total of 69 HBV-infected patients with pathologically confirmed cHCC-CCA who underwent hepatectomy were included. Univariate and multivariate analyses were conducted to determine independent risk factors that were then incorporated into the predictive model associated with MVI. Receiver operating characteristic analysis was used to assess the predictive performance of the new model. RESULTS For the multivariate analysis, γ-glutamyl transpeptidase (OR, 3.69; p = 0.034), multiple nodules (OR, 4.41; p = 0.042) and peritumoral enhancement (OR, 6.16; p = 0.004) were independently associated with MVI. Active replication of HBV indicated by positive HBeAg showed no differences between MVI-positive and MVI-negative patients. The prediction score using the independent predictors achieved an area under the curve of 0.813 (95% CI 0.717-0.908). A significantly lower recurrence-free survival was observed in the high-risk group with a score of ≥1 (p < 0.001). CONCLUSION γ-glutamyl transpeptidase, peritumoral enhancement and multiple nodules were independent preoperative predictors of MVI in HBV-related cHCC-CCA patients. The established prediction score demonstrated satisfactory performance in predicting MVI pre-operatively and may facilitate prognostic stratification.
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Sim JZT, Hui TCH, Chuah TK, Low HM, Tan CH, Shelat VG. Efficacy of texture analysis of pre-operative magnetic resonance imaging in predicting microvascular invasion in hepatocellular carcinoma. World J Clin Oncol 2022; 13:918-928. [PMID: 36483976 PMCID: PMC9724184 DOI: 10.5306/wjco.v13.i11.918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 10/13/2022] [Accepted: 11/04/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Presence of microvascular invasion (MVI) indicates poorer prognosis post-curative resection of hepatocellular carcinoma (HCC), with an increased chance of tumour recurrence. By present standards, MVI can only be diagnosed post-operatively on histopathology. Texture analysis potentially allows identification of patients who are considered 'high risk' through analysis of pre-operative magnetic resonance imaging (MRI) studies. This will allow for better patient selection, improved individualised therapy (such as extended surgical margins or adjuvant therapy) and pre-operative prognostication. AIM This study aims to evaluate the accuracy of texture analysis on pre-operative MRI in predicting MVI in HCC. METHODS Retrospective review of patients with new cases of HCC who underwent hepatectomy between 2007 and 2015 was performed. Exclusion criteria: No pre-operative MRI, significant movement artefacts, loss-to-follow-up, ruptured HCCs, previous hepatectomy and adjuvant therapy. Fifty patients were divided into MVI (n = 15) and non-MVI (n = 35) groups based on tumour histology. Selected images of the tumour on post-contrast-enhanced T1-weighted MRI were analysed. Both qualitative (performed by radiologists) and quantitative data (performed by software) were obtained. Radiomics texture parameters were extracted based on the largest cross-sectional area of each tumor and analysed using MaZda software. Five separate methods were performed. Methods 1, 2 and 3 exclusively made use of features derived from arterial, portovenous and equilibrium phases respectively. Methods 4 and 5 made use of the comparatively significant features to attain optimal performance. RESULTS Method 5 achieved the highest accuracy of 87.8% with sensitivity of 73% and specificity of 94%. CONCLUSION Texture analysis of tumours on pre-operative MRI can predict presence of MVI in HCC with accuracies of up to 87.8% and can potentially impact clinical management.
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Affiliation(s)
- Jordan Zheng Ting Sim
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Terrence Chi Hong Hui
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Tong Kuan Chuah
- School of Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore
| | - Hsien Min Low
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Cher Heng Tan
- Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
| | - Vishal G Shelat
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore
- Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
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Yang WL, Zhu F, Chen WX. Texture analysis of contrast-enhanced magnetic resonance imaging predicts microvascular invasion in hepatocellular carcinoma. Eur J Radiol 2022; 156:110528. [PMID: 36162156 DOI: 10.1016/j.ejrad.2022.110528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 04/03/2022] [Accepted: 09/15/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Microvascular invasion is one of the important risk factors of postoperative recurrence of hepatocellular carcinoma. Texture analysis uses mathematical methods to analyze the gray's quantitative value and distribution of images, for quantifying the heterogeneity of tissues. PURPOSE To investigate the feasibility of predicting MVI in HCC by analyzing the texture features of hepatic MR-enhanced images. METHODS 110 patients with HCC who underwent MR-enhanced examinations were included in this study, were divided into MVI-positive group (n = 52) and MVI-negative group (n = 58) according to postoperative pathology. Clinical, pathological data and MR imaging features were collected. 11 texture parameters were selected from the gray histogram and gray level co-occurrence matrix (GLCM). Texture parameters of MR-enhanced images were calculated for statistical analysis. RESULTS There were statistically significant differences in tumor size, location, degree of differentiation, AFP level, signal, pseudocapsule, margin, peritumoral enhancement and intratumoral artery between MVI-positive group and MVI-negative group (P < 0.05). The AUC value of combining MR image features in prediction of MVI was 0.693(sensitivity and specificity: 53.8 %, 82.8 %, respectively). There were statistically significant differences in the texture parameters of GLCM between two groups (P < 0.05). The AUC value of combining texture parameters in prediction of MVI was 0.797 (sensitivity and specificity: 88.2 %, 62.7 %, respectively). CONCLUSION MR image features and texture analysis have certain predictive effect on MVI, which are mutually verified and complementary. The texture parameters of GLCM could reflect tumor heterogeneity, which have great potential to help with preoperative decision. The combination of MR image features and texture analysis may improve the efficiency in prediction of MVI.
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Affiliation(s)
- Wei-Lin Yang
- Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China
| | - Fei Zhu
- Department of Radiology, West China Hospital, Sichuan University, 37# Guo Xue Xiang, Chengdu, Sichuan 610041, PR China
| | - Wei-Xia Chen
- Department of Radiology, West China Hospital, Sichuan University, 37# Guo Xue Xiang, Chengdu, Sichuan 610041, PR China.
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11
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TED: Two-stage expert-guided interpretable diagnosis framework for microvascular invasion in hepatocellular carcinoma. Med Image Anal 2022; 82:102575. [DOI: 10.1016/j.media.2022.102575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 07/08/2022] [Accepted: 08/11/2022] [Indexed: 12/16/2022]
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Liao CC, Cheng YF, Yu CY, Tsang LCL, Chen CL, Hsu HW, Chang WC, Lim WX, Chuang YH, Huang PH, Ou HY. A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI. J Clin Med 2022; 11:3789. [PMID: 35807074 PMCID: PMC9267530 DOI: 10.3390/jcm11133789] [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: 06/07/2022] [Revised: 06/23/2022] [Accepted: 06/28/2022] [Indexed: 11/17/2022] Open
Abstract
Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a histopathological marker and risk factor for HCC recurrence. We integrated diffusion-weighted imaging (DWI) and magnetic resonance (MR) image findings of tumors into a scoring system for predicting MVI. In total, 228 HCC patients with pathologically confirmed MVI who underwent surgical resection or liver transplant between November 2012 and March 2021 were enrolled retrospectively. Patients were divided into a right liver lobe group (n = 173, 75.9%) as the model dataset and a left liver lobe group (n = 55, 24.1%) as the model validation dataset. Multivariate logistic regression identified two-segment involved tumor (Score: 1; OR: 3.14; 95% CI: 1.22 to 8.06; p = 0.017); ADCmin ≤ 0.95 × 10-3 mm2/s (Score: 2; OR: 10.88; 95% CI: 4.61 to 25.68; p = 0.000); and largest single tumor diameter ≥ 3 cm (Score: 1; OR: 5.05; 95% CI: 2.25 to 11.30; p = 0.000), as predictive factors for the scoring model. Among all patients, sensitivity was 89.66%, specificity 58.04%, positive predictive value 68.87%, and negative predictive value 84.41%. For validation of left lobe group, sensitivity was 80.64%, specificity 70.83%, positive predictive value 78.12%, and negative predictive value 73.91%. The scoring model using ADCmin, largest tumor diameter, and two-segment involved tumor provides high sensitivity and negative predictive value in MVI prediction for use in routine functional MR.
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Affiliation(s)
- Chien-Chang Liao
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Yu-Fan Cheng
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Chun-Yen Yu
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Leung-Chit Leo Tsang
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Chao-Long Chen
- Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan;
| | - Hsien-Wen Hsu
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Wan-Ching Chang
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Wei-Xiong Lim
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Yi-Hsuan Chuang
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Po-Hsun Huang
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
| | - Hsin-You Ou
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Ta-Pei Road, Niao-Sung District, Kaohsiung 833, Taiwan; (C.-C.L.); (Y.-F.C.); (C.-Y.Y.); (L.-C.L.T.); (H.-W.H.); (W.-C.C.); (W.-X.L.); (Y.-H.C.); (P.-H.H.)
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13
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Jiang H, Wei J, Fu F, Wei H, Qin Y, Duan T, Chen W, Xie K, Lee JM, Bashir MR, Wang M, Song B, Tian J. Predicting microvascular invasion in hepatocellular carcinoma: A dual-institution study on gadoxetate disodium-enhanced MRI. Liver Int 2022; 42:1158-1172. [PMID: 35243749 PMCID: PMC9314889 DOI: 10.1111/liv.15231] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 12/06/2021] [Accepted: 12/14/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND & AIMS Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI. METHODS From July 2015 to November 2020, consecutive patients underwent surgery for HCC with preoperative gadoxetate disodium (EOB)-enhanced MRI was retrospectively enrolled. All MR images were reviewed independently by two radiologists who were blinded to the outcomes. In the training centre, a radio-clinical MVI score was developed via logistic regression analysis against pathology. In the testing centre, areas under the receiver operating curve (AUCs) of the MVI score and other previous MVI schemes were compared. Overall survival (OS) and recurrence-free survival (RFS) were analysed by the Kaplan-Meier method with the log-rank test. RESULTS A total of 417 patients were included, 195 (47%) with pathologically-confirmed MVI. The MVI score included: non-smooth tumour margin (odds ratio [OR] = 4.4), marked diffusion restriction (OR = 3.0), internal artery (OR = 3.0), hepatobiliary phase peritumoral hypointensity (OR = 2.5), tumour multifocality (OR = 1.6), and serum alpha-fetoprotein >400 ng/mL (OR = 2.5). AUCs for the MVI score were 0.879 (training) and 0.800 (testing), significantly higher than those for other MVI schemes (testing AUCs: 0.648-0.684). Patients with model-predicted MVI had significantly shorter OS (median 61.0 months vs not reached, P < .001) and RFS (median 13.0 months vs. 42.0 months, P < .001) than those without. CONCLUSIONS A preoperative MVI score integrating five EOB-MRI features and serum alpha-fetoprotein level could accurately predict MVI and postoperative survival in HCC. Therefore, this score may aid in individualized treatment decision making.
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Affiliation(s)
- Hanyu Jiang
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Jingwei Wei
- Key Laboratory of Molecular Imaging, Institute of AutomationChinese Academy of SciencesBeijingChina,Beijing Key Laboratory of Molecular ImagingBeijingChina
| | - Fangfang Fu
- Department of Medical ImagingHenan Provincial People’s HospitalZhengzhouChina,Department of Medical ImagingPeople’s Hospital of Zhengzhou UniversityZhengzhouChina
| | - Hong Wei
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Yun Qin
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Ting Duan
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Weixia Chen
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Kunlin Xie
- Department of Liver Surgery & Liver Transplantation, West China HospitalSichuan UniversityChengduChina
| | - Jeong Min Lee
- Department of RadiologySeoul National University Hospital and Seoul National University College of MedicineSeoulSouth Korea
| | - Mustafa R. Bashir
- Department of RadiologyDuke University Medical CenterDurhamNorth CarolinaUSA,Center for Advanced Magnetic Resonance in MedicineDuke University Medical CenterDurhamNorth CarolinaUSA,Division of Gastroenterology, Department of MedicineDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Meiyun Wang
- Department of Medical ImagingHenan Provincial People’s HospitalZhengzhouChina,Department of Medical ImagingPeople’s Hospital of Zhengzhou UniversityZhengzhouChina
| | - Bin Song
- Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Jie Tian
- Key Laboratory of Molecular Imaging, Institute of AutomationChinese Academy of SciencesBeijingChina,Beijing Key Laboratory of Molecular ImagingBeijingChina,Beijing Advanced Innovation Center for Big Data‐Based Precision Medicine, School of MedicineBeihang UniversityBeijingChina,Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and TechnologyXidian UniversityXi’anChina,Key Laboratory of Big Data‐Based Precision Medicine (Beihang University)Ministry of Industry and Information TechnologyBeijingChina
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14
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Preoperative application of systemic inflammatory biomarkers combined with MR imaging features in predicting microvascular invasion of hepatocellular carcinoma. Abdom Radiol (NY) 2022; 47:1806-1816. [PMID: 35267069 DOI: 10.1007/s00261-022-03473-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 02/21/2022] [Accepted: 02/21/2022] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate whether systemic inflammatory biomarkers compared with the imaging features interpreted by radiologists can offer complementary value for predicting the risk of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). METHODS A total of 156 patients with histologically confirmed HCC between Jan 2018 and Dec 2020 were retrospectively enrolled in the primary cohort. Preoperative clinical-inflammatory biomarkers and MR imaging of the patients were recorded and then evaluated as an inflammatory score (Inflam-score) and imaging feature score (Radio-score). Six Inflam-scores and 12 Radio-scores were determined from each patient by univariate analysis. Logistic regression was performed to select risk factors for MVI and establish a predictive nomogram. Decision curve analysis was applied to estimate the incremental value of the Inflam-score to the Radio-score for predicting MVI. RESULTS Four Radio-scores and 2 Inflam-scores, namely, larger tumor size, non-smooth tumor margin, presence of satellite nodules, presence of peritumoral enhance, higher neutrophil-lymphocyte ratio (NLR), and lower prognostic nutritional index (PNI), were significantly associated with MVI (p < 0.05). An MVI risk prediction nomogram was then constructed with an area under the curve (AUC) of 0.868 (95% CI 0.806-0.931). Adding Inflam-scores to Radio-scores improved the sensitivity of the model from 60.9 to 80.4% in receiver operating characteristic (ROC) curve analysis and led to a net benefit in decision curve analysis. CONCLUSION Systemic inflammatory biomarkers are complementary tools that provide additional benefit to conventional imaging estimation for predicting MVI in HCC patients.
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15
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Renzulli M, Mottola M, Coppola F, Cocozza MA, Malavasi S, Cattabriga A, Vara G, Ravaioli M, Cescon M, Vasuri F, Golfieri R, Bevilacqua A. Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT). Cancers (Basel) 2022; 14:cancers14071816. [PMID: 35406589 PMCID: PMC8997857 DOI: 10.3390/cancers14071816] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 03/18/2022] [Accepted: 03/31/2022] [Indexed: 02/08/2023] Open
Abstract
Background: Microvascular invasion (MVI) is a consolidated predictor of hepatocellular carcinoma (HCC) recurrence after treatments. No reliable radiological imaging findings are available for preoperatively diagnosing MVI, despite some progresses of radiomic analysis. Furthermore, current MVI radiomic studies have not been designed for small HCC nodules, for which a plethora of treatments exists. This study aimed to identify radiomic MVI predictors in nodules ≤3.0 cm by analysing the zone of transition (ZOT), crossing tumour and peritumour, automatically detected to face the uncertainties of radiologist’s tumour segmentation. Methods: The study considered 117 patients imaged by contrast-enhanced computed tomography; 78 patients were finally enrolled in the radiomic analysis. Radiomic features were extracted from the tumour and the ZOT, detected using an adaptive procedure based on local image contrast variations. After data oversampling, a support vector machine classifier was developed and validated. Classifier performance was assessed using receiver operating characteristic (ROC) curve analysis and related metrics. Results: The original 89 HCC nodules (32 MVI+ and 57 MVI−) became 169 (62 MVI+ and 107 MVI−) after oversampling. Of the four features within the signature, three are ZOT heterogeneity measures regarding both arterial and venous phases. On the test set (19MVI+ and 33MVI−), the classifier predicts MVI+ with area under the curve of 0.86 (95%CI (0.70–0.93), p∼10−5), sensitivity = 79% and specificity = 82%. The classifier showed negative and positive predictive values of 87% and 71%, respectively. Conclusions: The classifier showed the highest diagnostic performance in the literature, disclosing the role of ZOT heterogeneity in predicting the MVI+ status.
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Affiliation(s)
- Matteo Renzulli
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Margherita Mottola
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
- Advanced Research Center on Electronic Systems (ARCES), University of Bologna, 40126 Bologna, Italy;
| | - Francesca Coppola
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Maria Adriana Cocozza
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Silvia Malavasi
- Advanced Research Center on Electronic Systems (ARCES), University of Bologna, 40126 Bologna, Italy;
| | - Arrigo Cattabriga
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Giulio Vara
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Matteo Ravaioli
- General Surgery and Transplant Unit, IRCCS, Azienda Ospedaliero-Universitaria di Bologna, Sant’Orsola-Malpighi Hospital, 40138 Bologna, Italy; (M.R.); (M.C.)
| | - Matteo Cescon
- General Surgery and Transplant Unit, IRCCS, Azienda Ospedaliero-Universitaria di Bologna, Sant’Orsola-Malpighi Hospital, 40138 Bologna, Italy; (M.R.); (M.C.)
| | - Francesco Vasuri
- Pathology Unit, IRCCS, Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy;
| | - Rita Golfieri
- Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138 Bologna, Italy; (M.R.); (M.M.); (F.C.); (M.A.C.); (A.C.); (G.V.); (R.G.)
| | - Alessandro Bevilacqua
- Advanced Research Center on Electronic Systems (ARCES), University of Bologna, 40126 Bologna, Italy;
- Department of Computer Science and Engineering (DISI), University of Bologna, 40126 Bologna, Italy
- Correspondence: ; Tel.: +39-05-1209-5409
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Jiang C, Ma G, Liu Q, Song S. The value of preoperative 18F-FDG PET metabolic and volumetric parameters in predicting microvascular invasion and postoperative recurrence of hepatocellular carcinoma. Nucl Med Commun 2022; 43:100-107. [PMID: 34456318 DOI: 10.1097/mnm.0000000000001478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Microvascular invasion (MVI) is very important in the evaluation of hepatocellular carcinoma (HCC), but diagnosis is determined by postoperative pathology; thus, preoperative noninvasive methods will play an active role. The purpose of the study was to assess the performance of metabolic parameters of preoperative 18F-fluorodeoxyglucose PET/computerized tomography (18F-FDG PET/CT) in the prediction of MVI and postoperative recurrence in primary hepatocellular carcinoma. METHODS We retrospectively collected 72 patients with HCC who have performed 18F-FDG PET/CT scan before partial hepatectomy between 2016 and 2019. We used both normal liver tissue and inferior vena cava as the reference background and combined with clinicopathological features, 18F-FDG PET/CT metabolic and volumetric indices to predict MVI and postoperative recurrence of primary HCC before surgery. RESULTS Twenty-one of the 72 patients recurred, in recurrent cases showed higher maximum standard uptake value (SUVmax), TNR (ratio of tumor SUVmax to mean SUV [SUVmean] of the background tissue), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than nonrecurrence cases (P < 0.001). All 18F-FDG PET metabolic and volumetric indices for predicting postoperative HCC recurrence were significant on receiver-operating-characteristic (ROC) curve analyses (P < 0.05). TNRIVC, TNRNL, MTVIVC, MTVNL TLGIVC and TLGNL were significant factors for predicting MVI in HCC (P < 0.05). On multivariate analyses, MVI, SUVmax, TNRIVC, TNRNL, MTVIVC, MTVNL, TLGIVC and TLGNL (P < 0.05) are independent risk factors for predicting postoperative HCC recurrence. TNRIVC is the most relevant PET/CT parameter for predicting MVI in HCC, and MTVIVC is the most valuable for predicting postoperative HCC recurrence. Moreover, the PET/CT parameters are more accurate for prognosis with inferior vena cava as a reference background than with normal liver tissue. CONCLUSION 18F-FDG PET/CT metabolic and volumetric indices are effective predictors, and could noninvasively provide more comprehensive predictive information on MVI and postoperative recurrence of primary HCC before surgery.
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Affiliation(s)
- Chunjuan Jiang
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center
- Center for Biomedical Imaging
- Department of Oncology, Shanghai Medical College, Fudan University
- Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai, China
| | - Guang Ma
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center
- Center for Biomedical Imaging
- Department of Oncology, Shanghai Medical College, Fudan University
- Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai, China
| | - Qiufang Liu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center
- Center for Biomedical Imaging
- Department of Oncology, Shanghai Medical College, Fudan University
- Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai, China
| | - Shaoli Song
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center
- Center for Biomedical Imaging
- Department of Oncology, Shanghai Medical College, Fudan University
- Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai, China
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Kuang Y, Li R, Jia P, Ye W, Zhou R, Zhu R, Wang J, Lin S, Pang P, Ji W. MRI-Based Radiomics: Nomograms predicting the short-term response after transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma patients with diameter less than 5 cm. Abdom Radiol (NY) 2021; 46:3772-3789. [PMID: 33713159 DOI: 10.1007/s00261-021-02992-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 02/05/2021] [Accepted: 02/11/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To construct MRI radiomics nomograms that can predict short-term response after TACE in HCC patients with diameter less than 5 cm. METHODS MRI images and clinical data of 153 cases with tumor diameter less than 5 cm before TACE from 3 hospitals were collected retrospectively and divided into 1 internal training set and 1 external validation set. The T2-weighted imaging (T2WI) and dynamic contrast-enhanced MRI arterial phase (DCE-MR AP) images were studied. Multivariable logistic regression was used to construct Radiomics models, Clinics models, and Nomograms based on T2WI and DCE-MR AP, respectively. The receiver characteristic curve (ROC) was used to evaluate the predictive performance of each model. RESULTS In this study, 113 eligible cases in Hospital 1 were collected as the training set, and 40 eligible cases in other hospitals were used as the verification set. 11 T2WI features and 11 DCE-MRI AP features with the most predictive value were finally screened. 3 models based on T2WI and 3 models based on DCE-MRI AP were established, respectively. The area under curve (AUC) value of Nomogram based on T2WI of training set and validation set was 0.83 and 0.81, respectively. The AUC value of the models based on T2WI and models based on AP was almost equal, and Nomograms were the most effective models among all three types of models. CONCLUSION MRI-based Nomogram has greater predictive efficacy to predict the response after TACE than Radiomics and Clinics models alone, and the efficacy of T2WI-based models and DCE-MRI AP-based models was almost equal.
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Affiliation(s)
- Yani Kuang
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China
| | - Renzhan Li
- Sanmen People's Hospital, Taizhou, China
| | - Peng Jia
- First People's Hospital of Taizhou city, Zhejiang, China
| | - Wenhai Ye
- Sanmen People's Hospital, Taizhou, China
| | - Rongzhen Zhou
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China
| | - Rui Zhu
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China
| | - Jian Wang
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China
| | - Shuangxiang Lin
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China
| | | | - Wenbin Ji
- Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150 Ximen Street, Linhai, Zhejiang, China.
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18
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Hong SB, Choi SH, Kim SY, Shim JH, Lee SS, Byun JH, Park SH, Kim KW, Kim S, Lee NK. MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Liver Cancer 2021; 10:94-106. [PMID: 33981625 PMCID: PMC8077694 DOI: 10.1159/000513704] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 12/08/2020] [Indexed: 02/04/2023] Open
Abstract
PURPOSE Microvascular invasion (MVI) is an important prognostic factor in patients with hepatocellular carcinoma (HCC). However, the reported results of magnetic resonance imaging (MRI) features for predicting MVI of HCC are variable and conflicting. Therefore, this meta-analysis aimed to identify the significant MRI features for MVI of HCC and to determine their diagnostic value. METHODS Original studies reporting the diagnostic performance of MRI for predicting MVI of HCC were identified in MEDLINE and EMBASE up until January 15, 2020. Study quality was assessed using QUADAS-2. A bivariate random-effects model was used to calculate the meta-analytic pooled diagnostic odds ratio (DOR) and 95% confidence interval (CI) for each MRI feature for diagnosing MVI in HCC. The meta-analytic pooled sensitivity and specificity were calculated for the significant MRI features. RESULTS Among 235 screened articles, we found 36 studies including 4,274 HCCs. Of the 15 available MRI features, 7 were significantly associated with MVI: larger tumor size (>5 cm) (DOR = 5.2, 95% CI [3.0-9.0]), rim arterial enhancement (4.2, 95% CI [1.7-10.6]), arterial peritumoral enhancement (4.4, 95% CI [2.8-6.9]), peritumoral hypointensity on hepatobiliary phase imaging (HBP) (8.2, 95% CI [4.4-15.2]), nonsmooth tumor margin (3.2, 95% CI [2.2-4.4]), multifocality (7.1, 95% CI [2.6-19.5]), and hypointensity on T1-weighted imaging (T1WI) (4.9, 95% CI [2.5-9.6]). Both peritumoral hypointensity on HBP and multifocality showed very high meta-analytic pooled specificities for diagnosing MVI (91.1% [85.4-94.8%] and 93.3% [74.5-98.5%], respectively). CONCLUSIONS Seven MRI features including larger tumor size, rim arterial enhancement, arterial peritumoral enhancement, peritumoral hypointensity on HBP, nonsmooth margin, multifocality, and hypointensity on T1WI were significant predictors for MVI of HCC. These MRI features predictive of MVI can be useful in the management of HCC.
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Affiliation(s)
- Seung Baek Hong
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Sang Hyun Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea,*Sang Hyun Choi, Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympicro 43-gil, Songpa-gu, Seoul 05505 (Republic of Korea),
| | - So Yeon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ju Hyun Shim
- Department of Gastroenterology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seung Soo Lee
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jae Ho Byun
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seong Ho Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Kyung Won Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Suk Kim
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Nam Kyung Lee
- Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
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19
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Hu H, Qi S, Zeng S, Zhang P, He L, Wen S, Zeng N, Yang J, Zhang W, Zhu W, Xiang N, Fang C. Importance of Microvascular Invasion Risk and Tumor Size on Recurrence and Survival of Hepatocellular Carcinoma After Anatomical Resection and Non-anatomical Resection. Front Oncol 2021; 11:621622. [PMID: 33816254 PMCID: PMC8010691 DOI: 10.3389/fonc.2021.621622] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 02/15/2021] [Indexed: 12/12/2022] Open
Abstract
Purpose: To establish a valid prediction model to prognose the occurrence of microvascular invasion (MVI), and to compare the efficacy of anatomic resection (AR) or non-anatomic resection (NAR) for hepatocellular carcinoma (HCC). Methods: Two hundred twenty-eight patients with HCC who underwent surgical treatment were enrolled. Their hematological indicators, MRI imaging features, and outcome data were acquired. Result: In the multivariable analysis, alpha-fetoprotein >15 ng/mL, neutrophil to lymphocyte ratio >3.8, corona enhancement, and peritumoral hypointensity on hepatobiliary phase were associated with MVI. According on these factors, the AUROC of the predictive model in the primary and validation cohorts was 0.884 (95% CI: 0.829, 0.938) and 0.899 (95% CI: 0.821, 0.967), respectively. Patients with high risk of MVI or those with low risk of MVI but tumor size >5 cm in the AR group were associated with a lower rate of recurrence and death than patients in the NAR group; however, when patients are in the state of low-risk MVI with tumor size >5 cm, there is no difference in the rate of recurrence and death between AR and NAR. Conclusion: Our predictive model for HCC with MVI is convenient and accurate. Patients with high-risk of MVI or low-risk of MVI but tumor size >5 cm executing AR is of great necessity.
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Affiliation(s)
- Haoyu Hu
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Shuo Qi
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Silue Zeng
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Peng Zhang
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Linyun He
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Sai Wen
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Ning Zeng
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou, China
| | - Jian Yang
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou, China
| | - Weiqi Zhang
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Wen Zhu
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou, China
| | - Nan Xiang
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou, China
| | - Chihua Fang
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- Guangdong Provincial Clinical and Engineering Center of Digital Medicine, Guangzhou, China
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20
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Zhou W, Jian W, Cen X, Zhang L, Guo H, Liu Z, Liang C, Wang G. Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Contrast-Enhanced MR and 3D Convolutional Neural Networks. Front Oncol 2021; 11:588010. [PMID: 33854959 PMCID: PMC8040801 DOI: 10.3389/fonc.2021.588010] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 01/08/2021] [Indexed: 12/24/2022] Open
Abstract
Background and Purpose It is extremely important to predict the microvascular invasion (MVI) of hepatocellular carcinoma (HCC) before surgery, which is a key predictor of recurrence and helps determine the treatment strategy before liver resection or liver transplantation. In this study, we demonstrate that a deep learning approach based on contrast-enhanced MR and 3D convolutional neural networks (CNN) can be applied to better predict MVI in HCC patients. Materials and Methods This retrospective study included 114 consecutive patients who were surgically resected from October 2012 to October 2018 with 117 histologically confirmed HCC. MR sequences including 3.0T/LAVA (liver acquisition with volume acceleration) and 3.0T/e-THRIVE (enhanced T1 high resolution isotropic volume excitation) were used in image acquisition of each patient. First, numerous 3D patches were separately extracted from the region of each lesion for data augmentation. Then, 3D CNN was utilized to extract the discriminant deep features of HCC from contrast-enhanced MR separately. Furthermore, loss function for deep supervision was designed to integrate deep features from multiple phases of contrast-enhanced MR. The dataset was divided into two parts, in which 77 HCCs were used as the training set, while the remaining 40 HCCs were used for independent testing. Receiver operating characteristic curve (ROC) analysis was adopted to assess the performance of MVI prediction. The output probability of the model was assessed by the independent student's t-test or Mann-Whitney U test. Results The mean AUC values of MVI prediction of HCC were 0.793 (p=0.001) in the pre-contrast phase, 0.855 (p=0.000) in arterial phase, and 0.817 (p=0.000) in the portal vein phase. Simple concatenation of deep features using 3D CNN derived from all the three phases improved the performance with the AUC value of 0.906 (p=0.000). By comparison, the proposed deep learning model with deep supervision loss function produced the best results with the AUC value of 0.926 (p=0.000). Conclusion A deep learning framework based on 3D CNN and deeply supervised net with contrast-enhanced MR could be effective for MVI prediction.
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Affiliation(s)
- Wu Zhou
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wanwei Jian
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xiaoping Cen
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lijuan Zhang
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Hui Guo
- Department of Optometry, Guangzhou Aier Eye Hospital, Jinan University, Guangzhou, China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Changhong Liang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Guangyi Wang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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21
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Pan C, Liu X, Zou B, Chin W, Zhang W, Ye Y, Liu Y, Yu J. A Nomogram Estimation for the Risk of Microvascular Invasion in Hepatocellular Carcinoma Patients Meeting the Milan Criteria. J INVEST SURG 2021; 35:535-541. [PMID: 33655806 DOI: 10.1080/08941939.2021.1893411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE We aimed to develop and validate a nomogram for preoperatively estimating the risk of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) within the Milan criteria. METHODS The clinical data of 312 HCC patients who underwent liver surgery at the xxx from Jan 2017 to Dec 2019 were retrospectively collected. Then, the study population was categorized into the training and validation group based on the date of surgery. To identify risk factors related to MVI, we conducted a series of logistic regression analyses. By combining these risk factors, a nomogram was then established. We further clarified the usability of our model through the area under the ROC curve (AUC), decision curve analysis (DCA), and calibration curve. RESULTS Pathological examination revealed MVI in 108 patients with HCC (34.6%). Three independent predictors were identified: level of alpha-fetoprotein (AFP) exceeds 194 ng/mL (OR = 2.20, 95% CI: 1.13-4.31, p = 0.021), size of tumor (OR = 1.59; 95% CI: 1.18-2.12; P < 0.001) and number of tumors (OR = 3.37, 95% CI: 1.64-7.28, p < 0.001). A nomogram was subsequently built with an AUC of 0.73 and 0.74 respectively in the training cohort and validation cohort. The calibration curve showed a relatively high consistency between predicted probability and observed outcomes. Besides, the DCA revealed that the model was clinically beneficial for preoperatively predicting MVI in HCC. CONCLUSIONS A model for evaluating the risk of MVI HCC patients was developed and validated. The model could provide clinicians with a relatively reliable basis for optimizing treatment decisions.
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Affiliation(s)
- Chenggeng Pan
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xi Liu
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
| | - Bei Zou
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Wenjie Chin
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
| | - Weichen Zhang
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
| | - Yufu Ye
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
| | - Yuanxing Liu
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
| | - Jun Yu
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.,NHC Key Laboratory of Combined Multi-organ Transplantation, Hangzhou, China
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22
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Li Y, Zhang Y, Fang Q, Zhang X, Hou P, Wu H, Wang X. Radiomics analysis of [ 18F]FDG PET/CT for microvascular invasion and prognosis prediction in very-early- and early-stage hepatocellular carcinoma. Eur J Nucl Med Mol Imaging 2021; 48:2599-2614. [PMID: 33416951 DOI: 10.1007/s00259-020-05119-9] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/15/2020] [Indexed: 12/16/2022]
Abstract
As a reliable preoperative predictor for microvascular invasion (MVI) and disease-free survival (DFS) is lacking, we developed a radiomics nomogram of [18F]FDG PET/CT to predict MVI status and DFS in patients with very-early- and early-stage (BCLC 0, BCLC A) hepatocellular carcinoma (HCC). METHODS Patients (N = 80) with BCLC0-A HCC who underwent [18F]FDG PET/CT before surgery were enrolled in this retrospective study and were randomized to a training cohort and a validation cohort. Texture features from patients obtained using Lifex software in the training cohort were subjected to LASSO regression to select the most useful predictive features of MVI and DFS. Then, the radiomics nomogram was constructed using the radiomics signature and clinical features and further validated. RESULTS To predict MVI, the [18F]FDG PET/CT radiomics signature consisted of five texture features from the PET and six texture features from CT. The signature was significantly associated with MVI status in the training cohort (P = 0.001). None of the clinical features was independent predictors for MVI status (P > 0.05). The area under the curve value of the M-PET/CT model was 0.891 (95% CI: 0.799-0.984) in the training cohort and showed good discrimination and calibration. To predict DFS, the [18F]FDG PET/CT radiomics nomogram (D-PET/CT model) and a clinicopathologic nomogram were built in the training cohort. The D-PET/CT model, which integrated the D-PET/CT radiomics signature with INR and TB, provided better predictive performance (C-index: 0.831, 95% CI: 0.761-0.900) and larger net benefits than the simple clinical model, as determined by decision curve analyses. CONCLUSION The newly developed [18F]FDG PET/CT radiomics signature was an independent biomarker for the estimation of MVI and DFS in patients with very-early- and early-stage HCC. Moreover, PET/CT nomogram, which incorporated the radiomics signature of [18F]FDG PET/CT and clinical risk factors in patients with very-early- and early-stage HCC, performed better for individualized DFS estimation, which might enable a step forward in precise medicine.
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Affiliation(s)
- Youcai Li
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Yin Zhang
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, Guangdong Province, China
| | - Qi Fang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Xiaoyao Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Peng Hou
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China
| | - Hubing Wu
- Nanfang PET Center, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, Guangdong Province, China.
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, No. 151, Yanjiang Road, Yuexiu District, Guangzhou, 510000, Guangdong, China.
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23
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Nebbia G, Zhang Q, Arefan D, Zhao X, Wu S. Pre-operative Microvascular Invasion Prediction Using Multi-parametric Liver MRI Radiomics. J Digit Imaging 2020; 33:1376-1386. [PMID: 32495126 PMCID: PMC7728938 DOI: 10.1007/s10278-020-00353-x] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Microvascular invasion (mVI) is the most significant independent predictor of recurrence for hepatocellular carcinoma (HCC), but its pre-operative assessment is challenging. In this study, we investigate the use of multi-parametric MRI radiomics to predict mVI status before surgery. We retrospectively collected pre-operative multi-parametric liver MRI scans for 99 patients who were diagnosed with HCC. These patients received surgery and pathology-confirmed diagnosis of mVI. We extracted radiomics features from manually segmented HCC regions and built machine learning classifiers to predict mVI status. We compared the performance of such classifiers when built on five MRI sequences used both individually and combined. We investigated the effects of using features extracted from the tumor region only, the peritumoral marginal region only, and the combination of the two. We used the area under the receiver operating characteristic curve (AUC) and accuracy as performance metrics. By combining features extracted from multiple MRI sequences, AUCs are 86.69%, 84.62%, and 84.19% when features are extracted from the tumor only, the peritumoral region only, and the combination of the two, respectively. For tumor-extracted features, the T2 sequence (AUC = 80.84%) and portal venous sequence (AUC = 79.22%) outperform other MRI sequences in single-sequence-based models and their combination yields the highest AUC of 86.69% for mVI status prediction. Our results show promise in predicting mVI from pre-operative liver MRI scans and indicate that information from multi-parametric MRI sequences is complementary in identifying mVI.
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Affiliation(s)
- Giacomo Nebbia
- Intelligent Systems Program, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA
| | - Qian Zhang
- Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Dooman Arefan
- Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA
| | - Xinxiang Zhao
- Department of Radiology, The Second Affiliated Hospital of Kunming Medical University, 374 Dianmian Road, Wuhua District, Kunming, 650101, Yunnan, China.
| | - Shandong Wu
- Intelligent Systems Program, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA.
- Department of Radiology, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA.
- Department of Bioengineering, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA.
- Department of Biomedical Informatics, University of Pittsburgh, 3362 Fifth Ave, Rm. 130, Pittsburgh, PA, 15213, USA.
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Zhang T, Pandey G, Xu L, Chen W, Gu L, Wu Y, Chen X. The Value of TTPVI in Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Cancer Manag Res 2020; 12:4097-4105. [PMID: 32581583 PMCID: PMC7276193 DOI: 10.2147/cmar.s245475] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 03/11/2020] [Indexed: 12/12/2022] Open
Abstract
Purpose The objective of our study was to evaluate the value of two-trait predictor of venous invasion (TTPVI) in the prediction of pathological microvascular invasion (pMVI) in patients with hepatocellular carcinoma (HCC) from preoperative computed tomography (CT) and magnetic resonance (MR). Methods A total of 128 preoperative patients with findings of HCC were enrolled. Tumor size, tumor margins, tumor capsule, peritumoral enhancement, and TTPVI was assessed on preoperative CT and MRI images. Histopathological features were reviewed: pathological tumor size, tumor differentiation, pMVI along with alpha-fetoprotein level (AFP). Significant imaging findings and histopathological features were determined with univariate and multivariate logistic regression analysis. Results Univariate analysis revealed that tumor size (p<0.01), AFP level (p=0.043), tumor differentiation (p<0.01), peritumoral enhancement (p=0.003), pathological tumor size (p<0.01), tumor margins (p<0.01) on CT and MRI, and TTPVI (p<0.01) showed statistically significant associations with pMVI. In multivariate logistic regression analysis, tumor size (odds ratio [OR] = 1.294; 95% confidence interval [CI]: 1.155, 1.451; p < 0.001), tumor differentiation (odds ratio [OR] =1.384; 95% confidence interval [CI]: 1.224, 1.564; p < 0.001), and TTPVI (odds ratio [OR] = 4.802; 95% confidence interval [CI]: 1.037, 22.233; p=0.045) were significant independent predictors of pMVI. Using 5.8 as the threshold for size, one could obtain an area-under-curve (AUC) of 0.793, 95% confidence interval [CI]: 0.715 to 0.857. Conclusion Tumor size, tumor differentiation, and TTPVI depicted in preoperative CT and MRI had a statistically significant correlation with pMVI. Hence, TTPVI detected on CT and MRI may be predictive of pMVI in HCC cases.
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Affiliation(s)
- Tao Zhang
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Gaurab Pandey
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Lin Xu
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Wen Chen
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Liangrui Gu
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Yijun Wu
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
| | - Xiuwen Chen
- Department of Pathology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, People's Republic of China
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25
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Lo Gullo R, Daimiel I, Morris EA, Pinker K. Combining molecular and imaging metrics in cancer: radiogenomics. Insights Imaging 2020; 11:1. [PMID: 31901171 PMCID: PMC6942081 DOI: 10.1186/s13244-019-0795-6] [Citation(s) in RCA: 122] [Impact Index Per Article: 24.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 09/25/2019] [Indexed: 02/07/2023] Open
Abstract
Background Radiogenomics is the extension of radiomics through the combination of genetic and radiomic data. Because genetic testing remains expensive, invasive, and time-consuming, and thus unavailable for all patients, radiogenomics may play an important role in providing accurate imaging surrogates which are correlated with genetic expression, thereby serving as a substitute for genetic testing. Main body In this article, we define the meaning of radiogenomics and the difference between radiomics and radiogenomics. We provide an up-to-date review of the radiomics and radiogenomics literature in oncology, focusing on breast, brain, gynecological, liver, kidney, prostate and lung malignancies. We also discuss the current challenges to radiogenomics analysis. Conclusion Radiomics and radiogenomics are promising to increase precision in diagnosis, assessment of prognosis, and prediction of treatment response, providing valuable information for patient care throughout the course of the disease, given that this information is easily obtainable with imaging. Larger prospective studies and standardization will be needed to define relevant imaging biomarkers before they can be implemented into the clinical workflow.
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Affiliation(s)
- Roberto Lo Gullo
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA.
| | - Isaac Daimiel
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
| | - Elizabeth A Morris
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA
| | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, New York, NY, 10065, USA.,Department of Biomedical Imaging and Image-guided Therapy, Molecular and Gender Imaging Service, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Wien, Austria
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Lahan-Martins D, Perales SR, Gallani SK, da Costa LBE, Lago EAD, Boin IDFSF, Caserta NMG, de Ataide EC. Microvascular invasion in hepatocellular carcinoma: is it predictable with quantitative computed tomography parameters? Radiol Bras 2019; 52:287-292. [PMID: 31656344 PMCID: PMC6808613 DOI: 10.1590/0100-3984.2018.0123] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Objective To investigate whether quantitative computed tomography (CT) measurements
can predict microvascular invasion (MVI) in hepatocellular carcinoma
(HCC). Materials and Methods This was a retrospective analysis of 200 cases of surgically proven HCCs in
125 consecutive patients evaluated between March 2010 and November 2017. We
quantitatively measured regions of interest in lesions and adjacent areas of
the liver on unenhanced CT scans, as well as in the arterial, portal venous,
and equilibrium phases on contrast-enhanced CT scans. Enhancement profiles
were analyzed and compared with histopathological references of MVI.
Univariate and multivariate logistic regression analyses were used in order
to evaluate CT parameters as potential predictors of MVI. Results Of the 200 HCCs, 77 (38.5%) showed evidence of MVI on histopathological
analysis. There was no statistical difference between HCCs with MVI and
those without, in terms of the percentage attenuation ratio in the portal
venous phase (114.7 vs. 115.8) and equilibrium phase (126.7 vs. 128.2), as
well as in terms of the relative washout ratio, also in the portal venous
and equilibrium phases (15.0 vs. 8.2 and 31.4 vs. 26.3, respectively). Conclusion Quantitative dynamic CT parameters measured in the preoperative period do
not appear to correlate with MVI in HCC.
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Affiliation(s)
- Daniel Lahan-Martins
- Hospital de Clínicas da Universidade Estadual de Campinas (HC-Unicamp), Campinas, SP, Brazil
| | - Simone Reges Perales
- Hospital de Clínicas da Universidade Estadual de Campinas (HC-Unicamp), Campinas, SP, Brazil
| | - Stephanie Kilaris Gallani
- Faculdade de Ciências Médicas da Universidade Estadual de Campinas (FCM-Unicamp), Campinas, SP, Brazil
| | | | | | | | | | - Elaine Cristina de Ataide
- Faculdade de Ciências Médicas da Universidade Estadual de Campinas (FCM-Unicamp), Campinas, SP, Brazil
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Zhu F, Yang F, Li J, Chen W, Yang W. Incomplete tumor capsule on preoperative imaging reveals microvascular invasion in hepatocellular carcinoma: a systematic review and meta-analysis. Abdom Radiol (NY) 2019; 44:3049-3057. [PMID: 31292671 DOI: 10.1007/s00261-019-02126-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE Microvascular invasion (MVI), which is difficult to diagnose before surgery, is a major factor affecting postoperative recurrence in patients with hepatocellular carcinoma (HCC). The relationship between the radiological tumor capsule and MVI is controversial. This study aimed to evaluate the association between the tumor capsule and MVI. METHODS We searched Medline (by PubMed) and Embase (by OvidSP). Two review authors independently screened titles and abstracts, selected studies about MVI prediction with radiologic tumor capsule and studies with enough data for extracted, assessed the methodological quality and collected data. Summary results were presented as the diagnostic odds ratio (DOR), sensitivity, specificity, and 95% confidence interval. RESULTS Fifteen studies with 2038 patients were included; fourteen studies, including 1331 patients, with no significant heterogeneity indicated no relationship between absent tumor capsule and MVI [DOR = 0.90 (0.64, 1.26)]. Six studies, including 541 patients, with no significant heterogeneity showed incomplete capsule could be used to predict MVI of HCC preoperatively [DOR = 1.85 (1.13, 3.04)]. The overall sensitivity and specificity estimate were 0.50 (0.37, 0.64) and 0.64 (0.53, 0.74), respectively. Eight studies, including 1349 patients, with highly significant heterogeneity revealed that complete capsule could be a protective factor for MVI [DOR = 1.97 (1.01, 3.86)]. CONCLUSIONS For MVI of HCC, incomplete tumor capsule is a risk factor, while a complete tumor capsule might be a protective factor. However, absent capsule doesn't show significant relationship with MVI. This might be due to combination of the risk and protective effects of present capsule in MVI.
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Affiliation(s)
- Fei Zhu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Fan Yang
- Department of Radiology, Chengdu First People's Hospital, Chengdu, 610041, Sichuan, China
| | - Jing Li
- Department of Evidence-Based Medicine and Clinical Epidemiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Weixia Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
| | - Weilin Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
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Server S, Sabet S, Yaghouti K, Namal E, Inan N, Tokat Y. Value of Imaging Findings in the Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Transplant Proc 2019; 51:2403-2407. [PMID: 31402256 DOI: 10.1016/j.transproceed.2019.01.178] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Accepted: 01/28/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND The purpose of this study was to determine the utility of some imaging findings in predicting microvascular invasion (MVI) and hepatocellular carcinoma (HCC) recurrence risk after liver transplantation. METHOD This retrospective study included 123 patients with histopathologically proven HCC at explant. All HCCs were classified as MVI positive (group I) or negative (group II) based on histopathological findings. In each group, multifocality, largest tumor size, bulging (tumor causing liver capsule expansion), beak sign (the acute angle between the tumor and liver parenchyma), and diffusion restriction on diffusion weighted images (DWI) were evaluated. These findings were compared between the groups by Student's t test. The relation between the parameters and MVI was analyzed by using the Spearman's correlation test. RESULTS Of the total patients, 30.1% had MVI (group I) and 69.9% (group II) did not have MVI. Presence of beak sign (P ≤ .005), bulging sign (P = .002), and diffusion restriction (P = .045) were significantly more frequent in group I than group II. The beak sign, bulging sign, and diffusion restriction were correlated with presence of MVI. Largest tumor size and multifocality were higher in group I than group II, but the differences were not statistically significant. CONCLUSION Radiologists and transplant surgeons should be aware of some clue imaging findings, especially beak and bulging signs because these findings may predict the presence of MVI in HCC. These patients might benefit from histologic confirmation of the tumor characteristics through biopsy and subsequent bridging treatment options before liver transplantation to reduce the risk of recurrence.
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Affiliation(s)
- Sadik Server
- Department of Radiology, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey.
| | - Soheil Sabet
- Department of Radiology, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey
| | - Kourosh Yaghouti
- Department of Radiology, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey
| | - Esat Namal
- Department of Medical Oncology, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey
| | - Nagihan Inan
- Department of Radiology, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey
| | - Yaman Tokat
- Department of Liver Transplantation, Istanbul Bilim University, Sisli Florence Nightingale Hospital, Istanbul, Turkey
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Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS. Abdom Radiol (NY) 2019; 44:2788-2800. [PMID: 31089780 DOI: 10.1007/s00261-019-02056-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. MATERIALS AND METHODS In this retrospective study, we assessed 62 patients (14 women-48 men; mean age, 63 years; range 38-80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. RESULTS No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. CONCLUSION Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.
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Chou YC, Lao IH, Hsieh PL, Su YY, Mak CW, Sun DP, Sheu MJ, Kuo HT, Chen TJ, Ho CH, Kuo YT. Gadoxetic acid-enhanced magnetic resonance imaging can predict the pathologic stage of solitary hepatocellular carcinoma. World J Gastroenterol 2019; 25:2636-2649. [PMID: 31210715 PMCID: PMC6558433 DOI: 10.3748/wjg.v25.i21.2636] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/30/2019] [Accepted: 05/08/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Although important for determining long-term outcome, pathologic stage of hepatocellular carcinoma (HCC) is difficult to predict before surgery. Current state-of-the-art magnetic resonance imaging (MRI) using gadoxetic acid provides many imaging features that could potentially be used to classify single HCC as pT1 or pT2.
AIM To determine which gadoxetic acid-enhanced MRI (EOB-MRI) findings predict pathologic stage T2 in patients with solitary HCC (cT1).
METHODS Pre-operative EOB-MRI findings were reviewed in a retrospective cohort of patients with solitary HCC. The following imaging features were examined: Hyperintensity in unenhanced T2-weighted images, hypointensity in unenhanced T1-weighted images, arterial enhancement, corona enhancement, washout appearance, capsular appearance, hypointensity in the tumor tissue during the hepatobiliary (HB) phase, peritumoral hypointensity in the HB phase, hypointense rim in the HB phase, intratumoral fat, hyperintensity on diffusion-weighted imaging, hypointensity on apparent diffusion coefficient map, mosaic appearance, nodule-in-nodule appearance, and the margin (smooth or irregular). Surgical pathology was used as the reference method for tumor staging. Univariate and multivariate analyses were performed to identify predictors of microvascular invasion or satellite nodules.
RESULTS There were 39 (34.2%; 39 of 114) and 75 (65.8%; 75 of 114) pathological stage T2 and T1 HCCs, respectively. Large tumor size (≥ 2.3 cm) and two MRI findings, i.e., corona enhancement [odds ratio = 2.67; 95% confidence interval: 1.101-6.480] and peritumoral hypointensity in HB phase images (odds ratio = 2.203; 95% confidence interval: 0.961-5.049) were associated with high risk of pT2 HCC. The positive likelihood ratio was 6.25 (95% confidence interval: 1.788-21.845), and sensitivity of EOB-MRI for detecting pT2 HCC was 86.2% when two or three of these MRI features were present. Small tumor size and hypointense rim in the HB phase were regarded as benign features. Small HCCs with hypointense rim but not associated with aggressive features were mostly pT1 lesions (specificity, 100%).
CONCLUSION Imaging features on EOB-MRI could potentially be used to predict the pathologic stage of solitary HCC (cT1) as pT1 or pT2.
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Affiliation(s)
- Yi-Chen Chou
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - I-Ha Lao
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
- Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
- School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
| | - Pei-Ling Hsieh
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ying-Ying Su
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Chee-Wai Mak
- Department of Medical Imaging, Chi Mei Medical Center, Tainan 710, Taiwan
| | - Ding-Ping Sun
- Department of Surgery, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Food Science and Technology, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Ming-Jen Sheu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Medicinal Chemistry, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Hsing-Tao Kuo
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Chi Mei Medical Center, Tainan 710, Taiwan
- Department of Senior Citizen Service Management, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Tzu-Ju Chen
- Department of Pathology, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Optometry, Chung Hwa University of Medical Technology, Tainan 717, Taiwan
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung 804, Taiwan
| | - Chung-Han Ho
- Department of Medical Research, Chi-Mei Medical Center, Tainan 710, Taiwan
- Department of Hospital and Health Care Administration, Chia Nan University of Pharmacy and Science, Tainan 717, Taiwan
| | - Yu-Ting Kuo
- Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan
- Department of Radiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan
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Xu X, Zhang HL, Liu QP, Sun SW, Zhang J, Zhu FP, Yang G, Yan X, Zhang YD, Liu XS. Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma. J Hepatol 2019; 70:1133-1144. [PMID: 30876945 DOI: 10.1016/j.jhep.2019.02.023] [Citation(s) in RCA: 483] [Impact Index Per Article: 80.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 01/30/2019] [Accepted: 02/16/2019] [Indexed: 12/12/2022]
Abstract
BACKGROUND & AIMS Microvascular invasion (MVI) impairs surgical outcomes in patients with hepatocellular carcinoma (HCC). As there is no single highly reliable factor to preoperatively predict MVI, we developed a computational approach integrating large-scale clinical and imaging modalities, especially radiomic features from contrast-enhanced CT, to predict MVI and clinical outcomes in patients with HCC. METHODS In total, 495 surgically resected patients were retrospectively included. MVI-related radiomic scores (R-scores) were built from 7,260 radiomic features in 6 target volumes. Six R-scores, 15 clinical factors, and 12 radiographic scores were integrated into a predictive model, the radiographic-radiomic (RR) model, with multivariate logistic regression. RESULTS Radiomics related to tumor size and intratumoral heterogeneity were the top-ranked MVI predicting features. The related R-scores showed significant differences according to MVI status (p <0.001). Regression analysis identified 8 MVI risk factors, including 5 radiographic features and an R-score. The R-score (odds ratio [OR] 2.34) was less important than tumor capsule (OR 5.12), tumor margin (OR4.20), and peritumoral enhancement (OR 3.03). The RR model using these predictors achieved an area under the curve (AUC) of 0.909 in training/validation and 0.889 in the test set. Progression-free survival (PFS) and overall survival (OS) were significantly different between the RR-predicted MVI-absent and MVI-present groups (median PFS: 49.5 vs. 12.9 months; median OS: 76.3 vs. 47.3 months). RR-computed MVI probability, histologic MVI, tumor size, and Edmondson-Steiner grade were independently associated with disease-specific recurrence and mortality. CONCLUSIONS The computational approach, integrating large-scale clinico-radiologic and radiomic features, demonstrates good performance for predicting MVI and clinical outcomes. However, radiomics with current CT imaging analysis protocols do not provide statistically significant added value to radiographic scores. LAY SUMMARY The most effective treatment for hepatocellular carcinoma (HCC) is surgical removal of the tumor but often recurrence occurs, partly due to the presence of microvascular invasion (MVI). Lacking a single highly reliable factor able to preoperatively predict MVI, we developed a computational approach to predict MVI and the long-term clinical outcome of patients with HCC. In particular, the added value of radiomics, a newly emerging form of radiography, was comprehensively investigated. This computational method can enhance the communication with the patient about the likely success of the treatment and guide clinical management, with the aim of finding drugs that reduce the risk of recurrence.
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Affiliation(s)
- Xun Xu
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Hai-Long Zhang
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Qiu-Ping Liu
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Shu-Wen Sun
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Jing Zhang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Fei-Peng Zhu
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthcare, Shanghai, China
| | - Yu-Dong Zhang
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China.
| | - Xi-Sheng Liu
- Department of Radiology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu Province, China.
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Bodalal Z, Trebeschi S, Nguyen-Kim TDL, Schats W, Beets-Tan R. Radiogenomics: bridging imaging and genomics. Abdom Radiol (NY) 2019; 44:1960-1984. [PMID: 31049614 DOI: 10.1007/s00261-019-02028-w] [Citation(s) in RCA: 188] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic profile, a field commonly referred to as "radiogenomics." In this review, a general outline of radiogenomic literature concerning prominent mutations across different tumor sites will be provided. The field of radiogenomics originates from image processing techniques developed decades ago; however, many technical and clinical challenges still need to be addressed. Nevertheless, increasingly accurate and robust radiogenomic models are being presented and the future appears to be bright.
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33
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Yang DW, Wang XP, Wang ZC, Yang ZH, Bian XF. A scientometric analysis on hepatocellular carcinoma magnetic resonance imaging research from 2008 to 2017. Quant Imaging Med Surg 2019; 9:465-476. [PMID: 31032193 DOI: 10.21037/qims.2019.02.10] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background With the development of new magnetic resonance imaging (MRI) techniques, an increasing number of articles have been published regarding hepatocellular carcinoma magnetic resonance imaging (HCCMRI) in the past decade. However, few studies have statistically analyzed these published articles. In this study, we aim to systematically evaluate the scientific outcomes of HCCMRI research and explore the research hotspots from 2008 to 2017. Methods The included articles regarding HCCMRI research from 2008 to 2017 were downloaded from the Web of Science Core Collection and verified by two experienced radiologists. Excel 2016 was used to analyze the literature data, including the publication years and journals. CiteSpace V was used to perform co-occurrence analyses for authors, countries/regions and institutions and to generate the related collaboration network maps. Reference co-citation analysis (RCA) and burst keyword detection were also performed using CiteSpace V to explore the research hotspots in the past decade. Results A total of 835 HCCMRI articles published from 2008 to 2017 were identified. Journal of Magnetic Resonance Imaging published the most articles (79 publications, 9.46%). Extensive cooperating relationship were observed among countries/regions and among authors. South Korea had the most publications (199 publications, 21.82%), followed by the United States of America (USA) (190 publications, 20.83%), Japan (162 publications, 17.76%), and the People's Republic of China (148 publications, 16.23%). Among the top 10 co-cited authors, Bruix J (398 citations) was ranked first, followed by Llovet JM (235 citations), Kim YK (170 citations) and Forner A (152 citations). According to the RCA, ten major clusters were explored over the last decade; "LI-RADS data system" and "microvascular invasion" (MVI) were the two most recent clusters. Forty-seven burst keywords with the highest citation strength were detected over time. Of these keywords, "microvascular invasion" had the highest strength in the last 3 years. The LI-RADS has been constantly updated with the latest edition released in July 2018. However, the LI-RADS still has limitations in identifying certain categories of lesions by conceptual and non-quantitative probabilistic methods. Plenty of questions still need to be further answered such as the difference of diagnostic efficiency of each major/ancillary imaging features. Preoperative prediction of MVI of HCC is very important to therapeutic decision-making. Some parameters of Gd-EOB-DTPA-enhanced MRI were found to be useful in prediction of MVI, however, with a high specificity but a very low sensitivity. Comprehensive predictive model incorporating both imaging and clinical variables may be the more preferable in prediction of MVI of HCC. Conclusions HCCMRI-related publications displayed a gradually increasing trend from 2008 to 2017. The USA has a central position in collaboration with other countries/regions, while South Korea contributed the most in the number of publications. Of the ten major clusters identified in the RCA, the two most recent clusters were "LI-RADS data system" and "microvascular invasion", indicative of the current HCCMRI research hotspots.
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Affiliation(s)
- Da-Wei Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.,Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, Beijing 100050, China.,Department of Radiology, Hotan District People's Hospital, Hotan 848000, China
| | - Xiao-Pei Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Zhen-Chang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Zheng-Han Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Xue-Feng Bian
- Department of Radiology, Hotan District People's Hospital, Hotan 848000, China
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Yoneda N, Matsui O, Kobayashi S, Kitao A, Kozaka K, Inoue D, Yoshida K, Minami T, Koda W, Gabata T. Current status of imaging biomarkers predicting the biological nature of hepatocellular carcinoma. Jpn J Radiol 2019; 37:191-208. [PMID: 30712167 DOI: 10.1007/s11604-019-00817-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 01/21/2019] [Indexed: 02/07/2023]
Abstract
Hepatocellular carcinoma (HCC) is heterogeneous in terms of its biological nature. Various factors related to its biological nature, including size, multifocality, macroscopic morphology, grade of differentiation, macro/microvascular invasion, bile duct invasion, intra-tumoral fat and molecular factors, and their value as prognostic imaging biomarkers have been reported. And recently, genome-based molecular HCC classification correlated with clinical outcome has been elucidated. The imaging biomarkers suggesting a less aggressive nature of HCC are smaller size, solitary tumor, smooth margin suggesting small nodular type with indistinct margin and simple nodular type with distinct margin, capsule, imaging biomarkers predicting early or well-differentiated grade, intra-tumoral fat detection, and low fluorodeoxyglucose (FDG) accumulation. The imaging biomarkers suggesting an aggressive HCC nature are larger size, multifocality, non-smooth margin suggesting simple nodular type with extranodular growth, confluent multinodular, and infiltrative type, imaging biomarkers predicting poor differentiation, macrovascular tumor thrombus, predicting microvascular invasion imaging biomarkers, bile duct dilatation or tumor thrombus, and high FDG accumulation. In the genome-based molecular classification, CTNNB-1 mutated HCC shows a less aggressive nature, while CK19/EpCAM positive HCC and macrotrabecular massive HCC show an aggressive one. Better understanding of these imaging biomarkers can contribute to devising more appropriate treatment plans for HCC.
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Affiliation(s)
- Norihide Yoneda
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan.
| | - Osamu Matsui
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Satoshi Kobayashi
- Department of Quantum Medical Imaging, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Azusa Kitao
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Kazuto Kozaka
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Dai Inoue
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Kotaro Yoshida
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Tetsuya Minami
- Department of Radiology, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Ishikawa, 920-0293, Japan
| | - Wataru Koda
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
| | - Toshifumi Gabata
- Department of Radiology, Kanazawa University Graduate School of Medical Sciences, 13-1 Takaramachi, Kanazawa, Ishikawa, 920-8640, Japan
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Abstract
We discuss various imaging features that have been reported to be associated with the prognosis of hepatocellular carcinoma (HCC) but not included in the current staging systems: findings related with microvascular invasion, tumor encapsulation, intratumoral fat, presence of satellite nodules, peritumoral hypointensity on hepatobiliary phase images of gadoxetic-acid enhanced MRI, restricted diffusion, and irregular rim-like hyperenhancement. Current evidence suggests that larger (> 2 cm) tumor size, presence of satellite nodules, presence of irregular rim-like hyperenhancement of a tumor, peritumoral parenchymal enhancement in the arterial phase, and peritumoral hypointensity observed on hepatobiliary phase images are independent imaging features to portend a worse prognosis in patients with hepatocellular carcinoma.
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Peng J, Zhang J, Zhang Q, Xu Y, Zhou J, Liu L. A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma. ACTA ACUST UNITED AC 2018; 24:121-127. [PMID: 29770763 DOI: 10.5152/dir.2018.17467] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE We aimed to develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). METHODS A total of 304 eligible patients with HCC were randomly divided into training (n=184) and independent validation (n=120) cohorts. Portal venous and arterial phase computed tomography data of the HCCs were collected to extract radiomic features. Using the least absolute shrinkage and selection operator algorithm, the training set was processed to reduce data dimensions, feature selection, and construction of a radiomics signature. Then, a prediction model including the radiomics signature, radiologic features, and alpha-fetoprotein (AFP) level, as presented in a radiomics nomogram, was developed using multivariable logistic regression analysis. The radiomics nomogram was analyzed based on its discrimination ability, calibration, and clinical usefulness. Internal cohort data were validated using the radiomics nomogram. RESULTS The radiomics signature was significantly associated with MVI status (P < 0.001, both cohorts). Predictors, including the radiomics signature, nonsmooth tumor margin, hypoattenuating halos, internal arteries, and alpha-fetoprotein level were reserved in the individualized prediction nomogram. The model exhibited good calibration and discrimination in the training and validation cohorts (C-index [95% confidence interval]: 0.846 [0.787-0.905] and 0.844 [0.774-0.915], respectively). Its clinical usefulness was confirmed using a decision curve analysis. CONCLUSION The radiomics nomogram, as a noninvasive preoperative prediction method, shows a favorable predictive accuracy for MVI status in patients with HBV-related HCC.
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Affiliation(s)
- Jie Peng
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jing Zhang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Qifan Zhang
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jie Zhou
- Department of Hepatobiliary Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Li Liu
- Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
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Microvascular Invasion in HCC: The Molecular Imaging Perspective. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:9487938. [PMID: 30402046 PMCID: PMC6193341 DOI: 10.1155/2018/9487938] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 09/20/2018] [Indexed: 12/11/2022]
Abstract
Hepatocellular carcinoma represents the most frequent primary liver tumor; curative options are only surgical resection and liver transplantation. From 1996, Milan Criteria are applied in consideration of patients with cirrhosis and hepatocellular for liver transplantation; nonetheless, more recently, Milan Criteria have been criticized because they appear over conservative. Apart from number and size of lesions and biomarker levels, which already have been associated with poorer prognosis, overall survival and recurrence rates after transplantation are affected also by the presence of vascular invasion. Microvascular invasion suggests a poor prognosis but it is often hard to detect before transplant. Diagnostic imaging and tumor markers may play an important role and become the main tools to define microvascular invasion. In particular, a possible role could be found for computed tomography, magnetic resonance imaging, and positron emission tomography. In this paper, we analyze the possible role of positron emission tomography as a preoperative imaging biomarker capable of predicting microvascular invasion in patients with hepatocellular carcinoma and thus selecting optimal candidates for liver transplantation.
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Reginelli A, Vacca G, Segreto T, Picascia R, Clemente A, Urraro F, Serra N, Vanzulli A, Cappabianca S. Can microvascular invasion in hepatocellular carcinoma be predicted by diagnostic imaging? A critical review. Future Oncol 2018; 14:2985-2994. [PMID: 30084651 DOI: 10.2217/fon-2018-0175] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Imaging still has a limited capacity to detect microvascular invasion (mVI). The objective of this critical review is the evaluation of the most significant predictors of mVI in hepatocellular carcinoma (HCC) detectable by computed tomography, PET/computed tomography and MRI using a mathematical model. We systematically reviewed 15 observational studies from 2008 to 2018 to analyze factors with most impact on mVI detection. The most significant predictors of mVI correlating with imaging techniques were considered. From 1902 patients considered, we individuated 30 total predictors of mVI in a multivariate analysis. The most frequent predictors related to the highest presence with mVI in HCC were: α-fetoprotein (p < 0.0001), tumor size (p < 0.0001) and number of HCC nodules (p = 0.0020).
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Affiliation(s)
- Alfonso Reginelli
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Giovanna Vacca
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Teresa Segreto
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Roberto Picascia
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Alfredo Clemente
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Fabrizio Urraro
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | - Nicola Serra
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
| | | | - Salvatore Cappabianca
- Department of Radiology & Radiotherapy, University of Campania 'Luigi Vanvitelli', Piazza Miraglia, Naples 80138, Italy
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Jiang HY, Chen J, Xia CC, Cao LK, Duan T, Song B. Noninvasive imaging of hepatocellular carcinoma: From diagnosis to prognosis. World J Gastroenterol 2018; 24:2348-2362. [PMID: 29904242 PMCID: PMC6000290 DOI: 10.3748/wjg.v24.i22.2348] [Citation(s) in RCA: 113] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 04/18/2018] [Accepted: 04/23/2018] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a major public health problem worldwide. Hepatocarcinogenesis is a complex multistep process at molecular, cellular, and histologic levels with key alterations that can be revealed by noninvasive imaging modalities. Therefore, imaging techniques play pivotal roles in the detection, characterization, staging, surveillance, and prognosis evaluation of HCC. Currently, ultrasound is the first-line imaging modality for screening and surveillance purposes. While based on conclusive enhancement patterns comprising arterial phase hyperenhancement and portal venous and/or delayed phase wash-out, contrast enhanced dynamic computed tomography and magnetic resonance imaging (MRI) are the diagnostic tools for HCC without requirements for histopathologic confirmation. Functional MRI techniques, including diffusion-weighted imaging, MRI with hepatobiliary contrast agents, perfusion imaging, and magnetic resonance elastography, show promise in providing further important information regarding tumor biological behaviors. In addition, evaluation of tumor imaging characteristics, including nodule size, margin, number, vascular invasion, and growth patterns, allows preoperative prediction of tumor microvascular invasion and patient prognosis. Therefore, the aim of this article is to review the current state-of-the-art and recent advances in the comprehensive noninvasive imaging evaluation of HCC. We also provide the basic key concepts of HCC development and an overview of the current practice guidelines.
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Affiliation(s)
- Han-Yu Jiang
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Jie Chen
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Chun-Chao Xia
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Li-Kun Cao
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Ting Duan
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
| | - Bin Song
- Department of Radiology, Sichuan University West China Hospital, Chengdu 610041, Sichuan Province, China
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40
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Kim AY, Sinn DH, Jeong WK, Kim YK, Kang TW, Ha SY, Park CK, Choi GS, Kim JM, Kwon CHD, Joh JW, Kim MJ, Sohn I, Jung SH, Paik SW, Lee WJ. Hepatobiliary MRI as novel selection criteria in liver transplantation for hepatocellular carcinoma. J Hepatol 2018; 68:1144-1152. [PMID: 29410377 DOI: 10.1016/j.jhep.2018.01.024] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 12/18/2017] [Accepted: 01/24/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND & AIMS Hepatobiliary magnetic resonance imaging (MRI) provides additional information beyond the size and number of tumours, and may have prognostic implications. We examined whether pretransplant radiological features on MRI could be used to stratify the risk of tumour recurrence after liver transplantation (LT) for hepatocellular carcinoma (HCC). METHODS A total of 100 patients who had received a liver transplant and who had undergone preoperative gadoxetic acid-enhanced MRI, including the hepatobiliary phase (HBP), were reviewed for tumour size, number, and morphological type (e.g. nodular, nodular with perinodular extension, or confluent multinodular), satellite nodules, non-smooth tumour margins, peritumoural enhancement in arterial phase, peritumoural hypointensity on HBP, and apparent diffusion coefficients. The primary endpoint was time to recurrence. RESULTS In a multivariable adjusted model, the presence of satellite nodules [hazard ratio (HR) 3.07; 95% confidence interval (CI) 1.14-8.24] and peritumoural hypointensity on HBP (HR 4.53; 95% CI 1.52-13.4) were identified as independent factors associated with tumour recurrence. Having either of these radiological findings was associated with a higher tumour recurrence rate (72.5% vs. 15.4% at three years, p <0.001). When patients were stratified according to the Milan criteria, the presence of these two high-risk radiological findings was associated with a higher tumour recurrence rate in both patients transplanted within the Milan criteria (66.7% vs. 11.6% at three years, p <0.001, n = 68) and those who were transplanted outside the Milan criteria (75.5% vs. 28.6% at three years, p <0.001, n = 32). CONCLUSIONS Radiological features on preoperative hepatobiliary MRI can stratify the risk of tumour recurrence in patients who were transplanted either within or outside the Milan criteria. Therefore, hepatobiliary MRI can be a useful way to select potential candidates for LT. LAY SUMMARY High-risk radiological findings on preoperative hepatobiliary magnetic resonance imaging (either one of the following features: satellite nodule and peritumoural hypointensity on hepatobiliary phase) were associated with a higher tumour recurrence rate in patients transplanted either within or outside the Milan criteria.
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Affiliation(s)
- Ah Yeong Kim
- Department of Radiology and Center for Imaging Sciences, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dong Hyun Sinn
- Department of Internal Medicine, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology and Center for Imaging Sciences, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
| | - Young Kon Kim
- Department of Radiology and Center for Imaging Sciences, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Tae Wook Kang
- Department of Radiology and Center for Imaging Sciences, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sang Yun Ha
- Department of Pathology, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Chul Keun Park
- Department of Pathology, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Gyu Seong Choi
- Department of Surgery, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jong Man Kim
- Department of Surgery, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Choon Hyuck David Kwon
- Department of Surgery, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jae-Won Joh
- Department of Surgery, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Min-Ji Kim
- Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Insuk Sohn
- Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sin-Ho Jung
- Department of Biostatics and Bioinformatics, Duke University, USA
| | - Seung Woon Paik
- Department of Internal Medicine, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Won Jae Lee
- Department of Radiology and Center for Imaging Sciences, Research Institute for Future Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Zhao W, Liu W, Liu H, Yi X, Hou J, Pei Y, Liu H, Feng D, Liu L, Li W. Preoperative prediction of microvascular invasion of hepatocellular carcinoma with IVIM diffusion-weighted MR imaging and Gd-EOB-DTPA-enhanced MR imaging. PLoS One 2018; 13:e0197488. [PMID: 29771954 PMCID: PMC5957402 DOI: 10.1371/journal.pone.0197488] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2017] [Accepted: 05/03/2018] [Indexed: 12/21/2022] Open
Abstract
Microvascular invasion (MVI) is regarded as one of the independent risk factors for recurrence and poor prognosis of hepatocellular carcinoma (HCC). The presence of MVI in HCCs was evaluated on the basis of pathological reports of surgical specimens and was defined as tumor within a vascular space lined by endothelium that was visible only on microscopy. The aim of the study was to investigate the usefulness of intravoxel incoherent motion (IVIM) diffusion weighted (DW) magnetic resonance (MR) imaging in predicting MVI of HCC. Preoperative IVIM DW imaging and Gd-EOB-DTPA-enhanced MRI (DCE-MRI) of 51 patients were analyzed. Standard apparent diffusion coefficient (ADC), D (the true diffusion coefficient), D* (the pseudodiffusion coefficient) and f (the perfusion fraction), relative enhancement (RE) and radiological features were evaluated and analyzed. Univariate analysis revealed that HCCs with MVI had a higher portion of an irregular tumor shape than HCCs without MVI (p = 0.009), the Standard ADC, D value were significantly lower in HCCs with MVI (p = 0.022, p = 0.007, respectively). Multivariate analysis revealed that an irregular shape (p = 0.012) and D value ≤ 1.16×10-3mm2/sec (p = 0.048) were independent predictors for MVI. Combining the two factors of an irregular shape and D value, a sensitivity of 94.4% and specificity of 63.6% for predicting MVI was obtained. In conclusion, we found that an irregular shape and D value ≤ 1.16×10-3mm2/sec may suggest the presence of MVI in HCCs.
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Affiliation(s)
- Wei Zhao
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, P.R. China
| | - Wenguang Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Huaping Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Xiaoping Yi
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Jiale Hou
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Yigang Pei
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Hui Liu
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Deyun Feng
- Department of Pathology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
| | - Liyu Liu
- Center for Molecular Medicine, Xiangya Hospital of Centre-South University, Changsha, Hunan, P.R. China
| | - Wenzheng Li
- Department of Radiology, Xiangya Hospital of Centre-south University, Changsha, Hunan, P.R. China
- * E-mail:
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Ye JZ, Chen JZ, Li ZH, Bai T, Chen J, Zhu SL, Li LQ, Wu FX. Efficacy of postoperative adjuvant transcatheter arterial chemoembolization in hepatocellular carcinoma patients with microvascular invasion. World J Gastroenterol 2017; 23:7415-7424. [PMID: 29151695 PMCID: PMC5685847 DOI: 10.3748/wjg.v23.i41.7415] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 09/09/2017] [Accepted: 09/19/2017] [Indexed: 02/06/2023] Open
Abstract
AIM To investigate the efficacy and safety of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in preventing tumor recurrence and improving survival in Barcelona Clinic Liver Cancer (BCLC) early (A) and intermediate (B) stage hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI).
METHODS A total of 519 BCLC A or B HCC patients treated by liver resection alone or followed by PA-TACE between January 2012 and December 2015 were studied retrospectively. Univariate and multivariate analyses were performed to investigate the risk factors for recurrence-free survival (RFS) and overall survival (OS). Multiple logistic regression was used to identify the clinicopathological characteristics associated with MVI. The rates of RFS and OS were compared among patients with or without MVI treated with liver resection alone or followed by PA-TACE.
RESULTS Univariate and multivariate analyses demonstrated that serum AFP level > 400 ng/mL, tumor size > 5 cm, tumor capsule invasion, MVI, and major hepatectomy were risk factors for poor OS. Tumor capsule invasion, MVI, tumor size > 5 cm, HBV-DNA copies > 1 x 104 IU/mL, and multinodularity were risk factors for poor RFS. Multiple logistic regression identified serum AFP level > 400 ng/mL, tumor size > 5 cm, and tumor capsule invasion as independent predictors of MVI. Both OS and DFS were significantly improved in patients with MVI who received PA-TACE as compared to those who underwent liver resection alone. Patients without MVI did not show a significant difference in OS and RFS between those treated by liver resection alone or followed by PA-TACE.
CONCLUSION PA-TACE is a safe adjuvant intervention and can efficiently prevent tumor recurrence and improve the survival of BCLC early- and intermediate-stage HCC patients with MVI.
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MESH Headings
- Antineoplastic Combined Chemotherapy Protocols/administration & dosage
- Carcinoma, Hepatocellular/mortality
- Carcinoma, Hepatocellular/pathology
- Carcinoma, Hepatocellular/therapy
- Chemoembolization, Therapeutic/adverse effects
- Chemoembolization, Therapeutic/methods
- Chemotherapy, Adjuvant/adverse effects
- Chemotherapy, Adjuvant/methods
- Disease-Free Survival
- Female
- Follow-Up Studies
- Hepatectomy
- Humans
- Incidence
- Liver Neoplasms/mortality
- Liver Neoplasms/pathology
- Liver Neoplasms/therapy
- Male
- Microvessels/pathology
- Middle Aged
- Neoplasm Invasiveness/pathology
- Neoplasm Recurrence, Local/epidemiology
- Neoplasm Recurrence, Local/pathology
- Neoplasm Recurrence, Local/prevention & control
- Neoplasm Staging
- Postoperative Complications/epidemiology
- Postoperative Complications/etiology
- Prognosis
- Retrospective Studies
- Treatment Outcome
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Affiliation(s)
- Jia-Zhou Ye
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jun-Ze Chen
- Department of General Surgery, The Ninth Affiliated Hospital of Guangxi Medical University, Beihai 536000, Guangxi Zhuang Autonomous Region, China
| | - Zi-Hui Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Tao Bai
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Jie Chen
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Shao-Liang Zhu
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Le-Qun Li
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Fei-Xiang Wu
- Department of Hepatobiliary Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Liver Cancer Diagnosis and Treatment Engineering and Technology Research Center, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China
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Wang WT, Yang L, Yang ZX, Hu XX, Ding Y, Yan X, Fu CX, Grimm R, Zeng MS, Rao SX. Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging. Radiology 2017; 286:571-580. [PMID: 28937853 DOI: 10.1148/radiol.2017170515] [Citation(s) in RCA: 125] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Purpose To evaluate the potential role of diffusion kurtosis imaging and conventional magnetic resonance (MR) imaging findings including standard monoexponential model of diffusion-weighted imaging and morphologic features for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Materials and Methods Institutional review board approval and written informed consent were obtained. Between September 2015 and November 2016, 84 patients (median age, 54 years; range, 29-79 years) with 92 histopathologically confirmed HCCs (40 MVI-positive lesions and 52 MVI-negative lesions) were analyzed. Preoperative MR imaging examinations including diffusion kurtosis imaging (b values: 0, 200, 500, 1000, 1500, and 2000 sec/mm2) were performed and kurtosis, diffusivity, and apparent diffusion coefficient maps were calculated. Morphologic features of conventional MR images were also evaluated. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of these parameters as potential predictors of MVI. Results Features significantly related to MVI of HCC at univariate analysis were increased mean kurtosis value (P < .001), decreased mean diffusivity value (P = .033) and apparent diffusion coefficient value (P = .011), and presence of infiltrative border with irregular shape (P = .005) and irregular circumferential enhancement (P = .026). At multivariate analysis, mean kurtosis value (odds ratio, 6.25; P = .001), as well as irregular circumferential enhancement (odds ratio, 6.92; P = .046), were independent risk factors for MVI of HCC. The mean kurtosis value for MVI of HCC showed an area under the receiver operating characteristic curve of 0.784 (optimal cutoff value was 0.917). Conclusion Higher mean kurtosis values in combination with irregular circumferential enhancement are potential predictive biomarkers for MVI of HCC. © RSNA, 2017.
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Affiliation(s)
- Wen-Tao Wang
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Li Yang
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Zhao-Xia Yang
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Xin-Xing Hu
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Ying Ding
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Xu Yan
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Cai-Xia Fu
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Robert Grimm
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Meng-Su Zeng
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
| | - Sheng-Xiang Rao
- From the Department of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Medical Imaging Institute, 180 Fenglin Rd, 200032 Shanghai, China (W.T.W., L.Y., Z.X.Y., X.X.H., Y.D., M.S.Z., S.X.R.); MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (X.Y.); Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China (C.X.F.); and MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany (R.G.)
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Zhu W, Qing X, Yan F, Luo Y, Li Y, Zhou X. Can the Contrast-Enhanced Ultrasound Washout Rate Be Used to Predict Microvascular Invasion in Hepatocellular Carcinoma? ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:1571-1580. [PMID: 28502665 DOI: 10.1016/j.ultrasmedbio.2017.04.003] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 03/31/2017] [Accepted: 04/04/2017] [Indexed: 06/07/2023]
Abstract
The objective of this study was to investigate use of the washout rate of hepatocellular carcinoma on contrast-enhanced ultrasound (CEUS) for pre-operative determination of the presence of microvascular invasion. The study included 271 patients who underwent liver resection for hepatocellular carcinoma between April 2008 and December 2012, and were examined with contrast-enhanced ultrasound before surgery. Patients were followed up at 3-mo intervals for 3 y. Four washout patterns were classified according to the start time of washout: rapid, portal, delayed and slow. Rapid washout, presence of two or more tumors and tumor size ≥5 cm were identified as independent pre-operative predictors of microvascular invasion on multivariate analysis. Recurrence rates for patients with none, one, two or three predictors were 22.6%, 34.7%, 57.6% and 75.0%, respectively. In combination with tumor number and tumor size, contrast-enhanced ultrasound washout rate may have a role in identifying hepatocellular carcinoma patients with microvascular invasion.
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Affiliation(s)
- Wei Zhu
- Echo Lab of Cardiology Department/Department of Ultrasound, West China Hospital, Chengdu, Sichuan, China
| | - Xiachuan Qing
- Department of Ultrasound, Nanchong Central Hospital, Nanchong, Sichuan, China
| | - Feng Yan
- Department of Ultrasound, West China Hospital, Chengdu, Sichuan, China
| | - Yan Luo
- Department of Ultrasound, West China Hospital, Chengdu, Sichuan, China
| | - Yongzhong Li
- Department of Ultrasound, West China Hospital, Chengdu, Sichuan, China
| | - Xiang Zhou
- Department of Ultrasound, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Reginelli A, Vanzulli A, Sgrazzutti C, Caschera L, Serra N, Raucci A, Urraro F, Cappabianca S. Vascular microinvasion from hepatocellular carcinoma: CT findings and pathologic correlation for the best therapeutic strategies. Med Oncol 2017; 34:93. [PMID: 28401484 DOI: 10.1007/s12032-017-0949-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2017] [Accepted: 04/04/2017] [Indexed: 12/13/2022]
Abstract
Recurrence of HCC reduces survival rates in patients treated with surgery, and one of the most relevant risk factors for tumour recurrence is microvascular invasion (mVI). The identification of mVI on preoperative examinations could improve surgical planning's and techniques so as to reduce the risk of tumour recurrence. During our study, we have revised 101 CT examinations of the liver performed on patients diagnosed with solitary HCC who had surgical treatment and pathological analysis of the specimens for mVI in order to detect CT signs which could be reliable in mVI prediction. On CT examinations, the tumours were evaluated for margins, capsule, size, contrast enhancement, halo sign and Thad. From our statistical analysis, we found out that irregularity in tumour margins and defects in peritumoural capsule are the most significant characteristics predicting mVI in HCC. Every report on CT examinations performed on surgical candidate patients should include suggestions about mVI probability in order to tailor procedures, reduce tumour recurrence risk and improve survival rates.
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Affiliation(s)
- Alfonso Reginelli
- Department of Internal and Experimental Medicine, Second University of Naples, Naples, Italy.
| | - Angelo Vanzulli
- Niguarda Cancer Center - ASST Grande Ospedale Metropolitano, University of Milano, Niguarda, Milan, Italy
| | - Cristiano Sgrazzutti
- Niguarda Cancer Center - ASST Grande Ospedale Metropolitano, University of Milano, Niguarda, Milan, Italy
| | - Luca Caschera
- Niguarda Cancer Center - ASST Grande Ospedale Metropolitano, University of Milano, Niguarda, Milan, Italy
| | - Nicola Serra
- Department of Internal and Experimental Medicine, Second University of Naples, Naples, Italy
| | - Antonio Raucci
- Department of Internal and Experimental Medicine, Second University of Naples, Naples, Italy
| | - Fabrizio Urraro
- Department of Internal and Experimental Medicine, Second University of Naples, Naples, Italy
| | - Salvatore Cappabianca
- Department of Internal and Experimental Medicine, Second University of Naples, Naples, Italy
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Ünal E, İdilman İS, Akata D, Özmen MN, Karçaaltıncaba M. Microvascular invasion in hepatocellular carcinoma. Diagn Interv Radiol 2017; 22:125-32. [PMID: 26782155 DOI: 10.5152/dir.2015.15125] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Microvascular invasion is a crucial histopathologic prognostic factor for hepatocellular carcinoma. We reviewed the literature and aimed to draw attention to clinicopathologic and imaging findings that may predict the presence of microvascular invasion in hepatocellular carcinoma. Imaging findings suggesting microvascular invasion are disruption of capsule, irregular tumor margin, peritumoral enhancement, multifocal tumor, increased tumor size, and increased glucose metabolism on positron emission tomography-computed tomography. In the presence of typical findings, microvascular invasion may be predicted.
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Affiliation(s)
- Emre Ünal
- Department of Radiology, Hacettepe University School of Medicine Ankara, Turkey; Department of Radiology, Zonguldak Atatürk State Hospital, Zonguldak, Turkey.
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Preoperative Fluorine 18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography for Prediction of Microvascular Invasion in Small Hepatocellular Carcinoma. J Comput Assist Tomogr 2017; 40:524-30. [PMID: 26966955 DOI: 10.1097/rct.0000000000000405] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVES This study aimed to assess the value of preoperative fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET-CT) for predicting microvascular invasion (MVI) in small hepatocellular carcinoma (HCC). METHODS We retrospectively examined 60 patients who received F-FDG PET-CT prior to hepatic resection for small HCC (≤30 mm) with subsequent MVI confirmation by histopathology. The associations between PET-positive status and tumor factors were assessed. Furthermore, independent predictors for MVI and diagnostic utility of each MVI predictor were assessed. RESULTS Multivariate analysis revealed the presence of MVI as an independent predictor of PET-positive status (P = 0.023). Maximum standardized uptake value (SUVmax) of 3.2 or greater (P = 0.017) and lens culinaris agglutinin a-reactive α-fetoprotein (AFP-L3) 19% or greater (P = 0.010) were independent predictors of MVI. Areas under the receiver operating characteristic curves for SUVmax of 3.2 or greater, AFP-L3 19% or greater, and both factors combined for predicting MVI were 0.712 (0.493-0.932), 0.755 (0.563-0.947), and 0.856 (0.721-0.991), respectively. The sensitivity and specificity for predicting MVI were 77.8% and 74.5% for SUVmax of 3.2 or greater, 66.7% and 84.3% for AFP-L3 19% or greater, and 88.9% and 82.4% for the combination. CONCLUSIONS F-FDG PET-CT and AFP-L3 may be useful for predicting MVI in small HCC, and the combination of the 2 factors provided reliable assessment for selection of suitable hepatic resection and liver transplantation candidates.
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Sala E, Mema E, Himoto Y, Veeraraghavan H, Brenton JD, Snyder A, Weigelt B, Vargas HA. Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. Clin Radiol 2017; 72:3-10. [PMID: 27742105 PMCID: PMC5503113 DOI: 10.1016/j.crad.2016.09.013] [Citation(s) in RCA: 239] [Impact Index Per Article: 29.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Revised: 09/06/2016] [Accepted: 09/12/2016] [Indexed: 12/18/2022]
Abstract
Tumour heterogeneity in cancers has been observed at the histological and genetic levels, and increased levels of intra-tumour genetic heterogeneity have been reported to be associated with adverse clinical outcomes. This review provides an overview of radiomics, radiogenomics, and habitat imaging, and examines the use of these newly emergent fields in assessing tumour heterogeneity and its implications. It reviews the potential value of radiomics and radiogenomics in assisting in the diagnosis of cancer disease and determining cancer aggressiveness. This review discusses how radiogenomic analysis can be further used to guide treatment therapy for individual tumours by predicting drug response and potential therapy resistance and examines its role in developing radiomics as biomarkers of oncological outcomes. Lastly, it provides an overview of the obstacles in these emergent fields today including reproducibility, need for validation, imaging analysis standardisation, data sharing and clinical translatability and offers potential solutions to these challenges towards the realisation of precision oncology.
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Affiliation(s)
- E Sala
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA.
| | - E Mema
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Radiology, New York Presbyterian/Columbia University Medical Center, 622 W 168th St., New York, NY 10032, USA
| | - Y Himoto
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - H Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - J D Brenton
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK
| | - A Snyder
- Department of Medicine, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - B Weigelt
- Department of Pathology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - H A Vargas
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
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Jakhete N, Saberi B, Jonassaint NL, Cosar AM, Luu H, Kim A, Anders RA, Philosophe B, Cameron AM, Gurakar A. Microvascular Invasion in Hepatocellular Carcinoma and Liver Transplant. EXP CLIN TRANSPLANT 2016; 14:14-18. [PMID: 27805503 DOI: 10.6002/ect.tondtdtd2016.l17] [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: 06/05/2025]
Abstract
OBJECTIVES Curative therapy for hepatocellular carcinoma is liver transplant. To date, the Milan Criteria remain the best pretransplant clinical surrogate for tumor behavior and overall prognosis. Microvascular invasion portends a poor prognosis; however, it is often undetectable before transplant. Furthermore, its pretransplant indicators are not well established. In this study, we investigated the presurgical and pathologic predictors of microvascular invasion in patients with hepatocellular carcinoma. MATERIALS AND METHODS Between August 2000 and August 2013, 156 liver transplants were performed for hepatocellular carcinoma at the Johns Hopkins Medical Center. Information on clinical characteristics and pathology data, including microvascular invasion, were available for 107 patients on liver explants. Logistic regression was used to assess the effects of Milan Criteria, alpha-fetoprotein, tumor differentiation, and multilobar involvement on the presence of microvascular invasion on explant pathology. RESULTS In 107 patients, 24 (22%) had microvascular invasion on pathology. In patients with microvascular invasion, 41% were outside of Milan Criteria versus 19.3% of patients within but without microvascular invasion. In patients with microvascular invasion, the rate of poor differentiation and alpha-fetoprotein level > 1000 ng/mL were more common than in patients without microvascular invasion; however, on univariate and multivariable analyses, Milan Criteria, alphafetoprotein level, multilobar involvement, and differentiation did not reach statistical significance in predicting microvascular invasion on pathology. CONCLUSIONS In this study, potential predictors of microvascular invasion, including Milan Criteria, alphafetoprotein level, tumor differentiation, and multilobar involvement, were not predictive. Preoperative prediction of microvascular invasion remains a challenge, suggesting the need for future studies.
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Affiliation(s)
- Neha Jakhete
- From the Division of Gastroenterology and Hepatology-Transplant Hepatology, the Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
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Yang C, Wang H, Sheng R, Ji Y, Rao S, Zeng M. Microvascular invasion in hepatocellular carcinoma: is it predictable with a new, preoperative application of diffusion-weighted imaging? Clin Imaging 2016; 41:101-105. [PMID: 27840260 DOI: 10.1016/j.clinimag.2016.10.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Revised: 09/27/2016] [Accepted: 10/14/2016] [Indexed: 12/12/2022]
Abstract
PURPOSE The study aimed to explore the use of MRI in predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS The preoperative MRI and tissues of resected HCC patients were collected. The imaging characteristics that have previously been suggested and the mismatch between diffusion-weighted imaging (DWI) and T2-weighted imaging of regions, which the authors called DWI/T2 mismatch, were analyzed and compared with histopathological references. RESULTS A multivariate logistic regression analysis showed that DWI/T2 mismatch was an independent predictor of MVI. CONCLUSION The DWI/T2 mismatch can be a preoperative predictor of MVI for HCC.
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Affiliation(s)
- Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
| | - Heqing Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
| | - Ruofan Sheng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
| | - Shengxiang Rao
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China.
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