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Kan NN, Yu CY, Cheng YF, Hsu CC, Chen CL, Hsu HW, Weng CC, Tsang LLC, Chuang YH, Huang PH, Lim WX, Chen CP, Liao CC, Ou HY. Combined Hounsfield units of hepatocellular carcinoma on computed tomography and PET as a noninvasive predictor of early recurrence after living donor liver transplantation: Time-to-recurrence survival analysis. Eur J Radiol 2024; 177:111551. [PMID: 38875747 DOI: 10.1016/j.ejrad.2024.111551] [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: 10/06/2023] [Revised: 04/26/2024] [Accepted: 06/02/2024] [Indexed: 06/16/2024]
Abstract
BACKGROUND Liver transplantation is an effective treatment for preventing hepatocellular carcinoma (HCC) recurrence. This retrospective study aimed to quantitatively evaluate the attenuation in Hounsfield units (HU) on contrast-enhanced computed tomography (CECT) as a prognostic factor for hepatocellular carcinoma (HCC) following liver transplantation as a treatment. Our goal is to optimize its predictive ability for early tumor recurrence and compare it with the other imaging modality-positron emission tomography (PET). METHODS In 618 cases of LDLT for HCC, only 131 patients with measurable viable HCC on preoperative CECT and preoperative positron emission tomography (PET) evaluations were included, with a minimum follow-up period of 6 years. Cox regression models were developed to identify predictors of postoperative recurrence. Performance metrics for both CT and PET were assessed. The correlation between these two imaging modalities was also evaluated. Survival analyses were conducted using time-dependent receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) to assess accuracy and determine optimized cut-off points. RESULTS Univariate and multivariate analyses revealed that both arterial-phase preoperative tumor attenuation (HU) and PET were independent prognostic factors for recurrence-free survival. Both lower arterial tumor enhancement (Cut-off value = 59.2, AUC 0.88) on CT and PET positive (AUC 0.89) increased risk of early tumor recurrence 0.5-year time-dependent ROC. Composites with HU < 59.2 and a positive PET result exhibited significantly higher diagnostic accuracy in detecting early tumor recurrence (AUC = 0.96). CONCLUSION Relatively low arterial tumor enhancement values on CECT effectively predict early HCC recurrence after LDLT. The integration of CT and PET imaging may serve as imaging markers of early tumor recurrence in HCC patients after LDLT.
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Affiliation(s)
- Na-Ning Kan
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chun-Yen Yu
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yu-Fan Cheng
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chien-Chin Hsu
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chao-Long Chen
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Hsien-Wen Hsu
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Ching-Chun Weng
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Leo Leung-Chit Tsang
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Yi-Hsuan Chuang
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Po-Hsun Huang
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Wei-Xiong Lim
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chen-Pei Chen
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Chien-Chang Liao
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan
| | - Hsin-You Ou
- Liver Transplantation Program and Departments of Diagnostic Radiology and Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
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Elias-Neto A, Gonzaga APFC, Braga FA, Gomes NBN, Torres US, D'Ippolito G. Imaging Prognostic Biomarkers in Hepatocellular Carcinoma: A Comprehensive Review. Semin Ultrasound CT MR 2024:S0887-2171(24)00049-0. [PMID: 39067621 DOI: 10.1053/j.sult.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide with its incidence on the rise globally. This paper provides a comprehensive review of prognostic imaging markers in HCC, emphasizing their role in risk stratification and clinical decision-making. We explore quantitative and qualitative criteria derived from imaging studies, such as computed tomography (CT) and magnetic resonance imaging (MRI), which can offer valuable insights into the biological behavior of the tumor. While many of these markers are not yet widely integrated into current clinical guidelines, they represent a promising future direction for approaching this highly heterogeneous cancer. However, standardization and validation of these markers remain important challenges. We conclude by emphasizing the importance of ongoing research to enhance clinical practices and improve outcomes for patients with HCC.
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Affiliation(s)
- Abrahão Elias-Neto
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Ana Paula F C Gonzaga
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Fernanda A Braga
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Natália B N Gomes
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil
| | - Ulysses S Torres
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil; Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil.
| | - Giuseppe D'Ippolito
- Department of Diagnostic Imaging, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, São Paulo, Brazil; Department of Radiology, Grupo Fleury, São Paulo, São Paulo, Brazil
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Zhang Y, Sheng R, Yang C, Dai Y, Zeng M. Detecting microvascular invasion in hepatocellular carcinoma using the impeded diffusion fraction technique to sense macromolecular coordinated water. Abdom Radiol (NY) 2024; 49:1892-1904. [PMID: 38526597 DOI: 10.1007/s00261-024-04230-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 01/27/2024] [Accepted: 01/29/2024] [Indexed: 03/26/2024]
Abstract
OBJECTIVES Impeded diffusion fraction (IDF) is a novel and promising diffusion-weighted imaging (DWI) technique that allows for the detection of various diffusion compartments, including macromolecular coordinated water, free diffusion, perfusion, and cellular free water. This study aims to investigate the clinical potential of IDF-DWI in detecting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). METHODS 66 patients were prospectively included. Metrics derived from IDF-DWI and the apparent diffusion coefficient (ADC) were calculated. Multivariate logistic regression was employed to identify clinical risk factors. Diagnostic performance was evaluated using the area under the receiver operating characteristics curve (AUC-ROC), the area under the precision-recall curve (AUC-PR), and the calibration error (cal-error). Additionally, a power analysis was conducted to determine the required sample size. RESULTS The results suggested a significantly higher fraction of impeded diffusion (FID) originating from IDF-DWI in MVI-positive HCCs (p < 0.001). Moreover, the ADC was found to be significantly lower in MVI-positive HCCs (p = 0.019). Independent risk factors of MVI included larger tumor size and elevated alpha-fetoprotein (AFP) levels. The nomogram model incorporating ADC, FID, tumor size, and AFP level yielded the highest diagnostic accuracy for MVI (AUC-PR = 0.804, AUC-ROC = 0.783, cal-error = 0.044), followed by FID (AUC-PR = 0.693, AUC-ROC = 0.760, cal-error = 0.060) and ADC (AUC-PR = 0.570, AUC-ROC = 0.651, cal-error = 0.164). CONCLUSION IDF-DWI shows great potential in noninvasively, accurately, and preoperatively detecting MVI in HCC and may offer clinical benefits for prognostic prediction and determination of treatment strategy.
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Affiliation(s)
- Yunfei Zhang
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Ruofan Sheng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Chun Yang
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China
| | - Yongming Dai
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech Univerisity, Shanghai, 200032, China.
| | - Mengsu Zeng
- Shanghai Institute of Medical Imaging, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
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Fujita N, Ushijima Y, Ishimatsu K, Okamoto D, Wada N, Takao S, Murayama R, Itoyama M, Harada N, Maehara J, Oda Y, Ishigami K, Nishie A. Multiparametric assessment of microvascular invasion in hepatocellular carcinoma using gadoxetic acid-enhanced MRI. Abdom Radiol (NY) 2024; 49:1467-1478. [PMID: 38360959 DOI: 10.1007/s00261-023-04179-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/22/2023] [Accepted: 12/27/2023] [Indexed: 02/17/2024]
Abstract
PURPOSE To elucidate how precisely microvascular invasion (MVI) in hepatocellular carcinoma (HCC) can be predicted using multiparametric assessment of gadoxetic acid-enhanced MRI. METHODS In this retrospective single-center study, patients who underwent liver resection or transplantation of HCC were evaluated. Data obtained in patients who underwent liver resection were used as the training set. Nine kinds of MR findings for predicting MVI were compared between HCCs with and without MVI by univariate analysis, followed by multiple logistic regression analysis. Using significant findings, a predictive formula for diagnosing MVI was obtained. The diagnostic performance of the formula was investigated in patients who underwent liver resection (validation set 1) and in patients who underwent liver transplantation (validation set 2) using a receiver operating characteristic curve analysis. The area under the curves (AUCs) of these three groups were compared. RESULTS A total of 345 patients with 356 HCCs were selected for analysis. Tumor diameter (D) (P = 0.021), tumor washout (TW) (P < 0.01), and peritumoral hypointensity in the hepatobiliary phase (PHH) (P < 0.01) were significantly associated with MVI after multivariate analysis. The AUCs for predicting MVI of the predictive formula were as follows: training set, 0.88 (95% confidence interval (CI) 0.82,0.93); validation set 1, 0.81 (95% CI 0.73,0.87); validation set 2, 0.67 (95% CI 0.51,0.80). The AUCs were not significantly different among three groups (training set vs validation set 1; P = 0.15, training set vs validation set 2; P = 0.09, validation set 1 vs validation set 2; P = 0.29, respectively). CONCLUSION Our multiparametric assessment of gadoxetic acid-enhanced MRI performed quite precisely and with good reproducibility for predicting MVI.
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Affiliation(s)
- Nobuhiro Fujita
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
| | - Yasuhiro Ushijima
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Keisuke Ishimatsu
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Daisuke Okamoto
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Noriaki Wada
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Seiichiro Takao
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Ryo Murayama
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Masahiro Itoyama
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Noboru Harada
- Department of Surgery and Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Junki Maehara
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
- Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Yoshinao Oda
- Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Kousei Ishigami
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Akihiro Nishie
- Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa, 903-0125, Japan
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Hwang SH, Rhee H. Radiologic features of hepatocellular carcinoma related to prognosis. JOURNAL OF LIVER CANCER 2023; 23:143-156. [PMID: 37384030 PMCID: PMC10202237 DOI: 10.17998/jlc.2023.02.16] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 01/29/2023] [Accepted: 02/16/2023] [Indexed: 06/30/2023]
Abstract
The cross-sectional imaging findings play a crucial role in the diagnosis of hepatocellular carcinoma (HCC). Recent studies have shown that imaging findings of HCC are not only relevant for the diagnosis of HCC, but also for identifying genetic and pathologic characteristics and determining prognosis. Imaging findings such as rim arterial phase hyperenhancement, arterial phase peritumoral hyperenhancement, hepatobiliary phase peritumoral hypointensity, non-smooth tumor margin, low apparent diffusion coefficient, and the LR-M category of the Liver Imaging-Reporting and Data System have been reported to be associated with poor prognosis. In contrast, imaging findings such as enhancing capsule appearance, hepatobiliary phase hyperintensity, and fat in mass have been reported to be associated with a favorable prognosis. Most of these imaging findings were examined in retrospective, single-center studies that were not adequately validated. However, the imaging findings can be applied for deciding the treatment strategy for HCC, if their significance can be confirmed by a large multicenter study. In this literature, we would like to review imaging findings related to the prognosis of HCC as well as their associated clinicopathological characteristics.
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Affiliation(s)
- Shin Hye Hwang
- Department of Radiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea
| | - Hyungjin Rhee
- Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
- Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
- Center for Clinical Imaging Data Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
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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: 2.0] [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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Liang G, Yu W, Liu S, Zhang M, Xie M, Liu M, Liu W. The diagnostic performance of radiomics-based MRI in predicting microvascular invasion in hepatocellular carcinoma: A meta-analysis. Front Oncol 2023; 12:960944. [PMID: 36798691 PMCID: PMC9928182 DOI: 10.3389/fonc.2022.960944] [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: 06/03/2022] [Accepted: 12/23/2022] [Indexed: 02/01/2023] Open
Abstract
Objective The aim of this study was to assess the diagnostic performance of radiomics-based MRI in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Method The databases of PubMed, Cochrane library, Embase, Web of Science, Ovid MEDLINE, Springer, and Science Direct were searched for original studies from their inception to 20 August 2022. The quality of each study included was assessed according to the Quality Assessment of Diagnostic Accuracy Studies 2 and the radiomics quality score. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated. The summary receiver operating characteristic (SROC) curve was plotted and the area under the curve (AUC) was calculated to evaluate the diagnostic accuracy. Sensitivity analysis and subgroup analysis were performed to explore the source of the heterogeneity. Deeks' test was used to assess publication bias. Results A total of 15 studies involving 981 patients were included. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.79 (95%CI: 0.72-0.85), 0.81 (95%CI: 0.73-0.87), 4.1 (95%CI:2.9-5.9), 0.26 (95%CI: 0.19-0.35), 16 (95%CI: 9-28), and 0.87 (95%CI: 0.84-0.89), respectively. The results showed great heterogeneity among the included studies. Sensitivity analysis indicated that the results of this study were statistically reliable. The results of subgroup analysis showed that hepatocyte-specific contrast media (HSCM) had equivalent sensitivity and equivalent specificity compared to the other set. The least absolute shrinkage and selection operator method had high sensitivity and specificity than other methods, respectively. The investigated area of the region of interest had high specificity compared to the volume of interest. The imaging-to-surgery interval of 15 days had higher sensitivity and slightly low specificity than the others. Deeks' test indicates that there was no publication bias (P=0.71). Conclusion Radiomics-based MRI has high accuracy in predicting MVI in HCC, and it can be considered as a non-invasive method for assessing MVI in HCC.
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Affiliation(s)
- Gao Liang
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Wei Yu
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Shuqin Liu
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Mingxing Zhang
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Mingguo Xie
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China,*Correspondence: Mingguo Xie,
| | - Min Liu
- Toxicology Department, West China-Frontier PharmaTech Co., Ltd. (WCFP), Chengdu, Sichuan, China
| | - Wenbin Liu
- Department of Radiology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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Preoperative assessment of microvascular invasion of hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging with a fractional order calculus model: A pilot study. Magn Reson Imaging 2023; 95:110-117. [PMID: 34506910 DOI: 10.1016/j.mri.2021.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 09/05/2021] [Accepted: 09/05/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE To assess the clinical potential of a set of new diffusion parameters (D, β, and μ) derived from fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS Between January 2019 to November 2020, a total of 63 patients with HCC were enrolled in this study. Diffusion-weighted images were acquired by using ten b-values (0-2000 s/mm2). The FROC model parameters including diffusion coefficient (D), fractional order parameter (β), a microstructural quantity (μ) together with a conventional apparent diffusion coefficient (ADC) were calculated. Intraclass coefficients were calculated for assessing the agreement of parameters quantified by two radiologists. The differences of these values between the MVI-positive and MVI-negative HCC groups were compared by using independent sample t-test or the Mann-Whitney U test. Then the parameters showing significant differences between subgroups, including the β and D, were integrated to develop a comprehensive predictive model via binary logistic regression. The diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS Among all the studied diffusion parameters, significant differences were found in D, β, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher β values (0.65 ± 0.17 vs. 0.51 ± 0.13, P = 0.001), along with lower D values (0.84 ± 0.11 μm2/ms vs. 1.03 ± 0.13 μm2/ms, P < 0.001) and lower ADC values (1.38 ± 0.46 μm2/ms vs. 2.09 ± 0.70 μm2/ms, P < 0.001) than those of MVI-negative HCCs. According to the ROC analysis, the combination of D and β demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; β: 0.733; and ADC: 0.831) for differentiating MVI-positive from MVI-negative HCCs. CONCLUSIONS The FROC parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the MVI status of HCCs.
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Wang S, Zheng W, Zhang Z, Zhang GH, Huang DJ. Microvascular invasion risk scores affect the estimation of early recurrence after resection in patients with hepatocellular carcinoma: a retrospective study. BMC Med Imaging 2022; 22:204. [PMID: 36419016 PMCID: PMC9682687 DOI: 10.1186/s12880-022-00940-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Accepted: 11/15/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a histological factor that is closely related to the early recurrence of hepatocellular carcinoma (HCC) after resection. To investigate whether a noninvasive risk score system based on MVI status can be established to estimate early recurrence of HCC after resection. METHODS Between January 2018 to March 2021, a total of 108 patients with surgically treated single HCC was retrospectively included in our study. Fifty-one patients were pathologically confirmed with MVI and 57 patients were absent of MVI. Univariate and multivariate logistic regression analysis of preoperative laboratory and magnetic resonance imaging (MRI) features were used to screen noninvasive risk factors in association with MVI in HCC. Risk scores based on the odds ratio (OR) values of MVI-related risk factors were calculated to estimate the early recurrence after resection of HCC. RESULTS In multivariate logistic regression analysis, tumor size > 2 cm (P = 0.024, OR 3.05, 95% CI 1.19-11.13), Prothrombin induced by vitamin K absence-II > 32 mAU/ml (P = 0.001, OR 4.13, 95% CI 1.23-11.38), irregular tumor margin (P = 0.018, OR 3.10, 95% CI 1.16-8.31) and apparent diffusion coefficient value < 1007 × 10- 3mm2/s (P = 0.035, OR 2.27, 95% CI 1.14-7.71) were independent risk factors correlated to MVI in HCC. Risk scores of patients were calculated and were then categorized into high or low-risk levels. In multivariate cox survival analysis, only high-risk score of MVI was the independent risk factor of early recurrence (P = 0.009, OR 2.11, 95% CI 1.20-3.69), with a sensitivity and specificity of 0.52, 0.88, respectively. CONCLUSION A risk score system based on MVI status can help stratify patients in high-risk of early recurrence after resection of HCC.
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Affiliation(s)
- Sheng Wang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
| | - Weizhi Zheng
- grid.469601.cDepartment of Pathology, Taizhou First People’s Hospital, Taizhou City, 318020 Zhejiang Province China
| | - Zhencheng Zhang
- grid.469601.cDepartment of Laboratory, Taizhou First People’s Hospital, Taizhou City, 318020 Zhejiang Province China
| | - Guo-hua Zhang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
| | - Dan-jiang Huang
- grid.469601.cDepartment of Radiology, Taizhou First People’s Hospital, 218 Hengjie Rd., Dongcheng Street, Huangyan District, Taizhou City, 318020 Zhejiang Province China
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Qin YL, Wang S, Chen F, Liu HX, Yue KT, Wang XZ, Ning HF, Dong P, Yu XR, Wang GZ. Prediction of outcomes by diffusion kurtosis imaging in patients with large (≥5 cm) hepatocellular carcinoma after liver resection: A retrospective study. Front Oncol 2022; 12:939358. [DOI: 10.3389/fonc.2022.939358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/18/2022] [Indexed: 11/18/2022] Open
Abstract
PurposeTo evaluate preoperative diffusion kurtosis imaging (DKI) in predicting the outcomes of large hepatocellular carcinoma (HCC) after liver resection (LR).Materials and methodsFrom January 2015 to December 2017, patients with a large (≥5cm) HCC who underwent preoperative DKI were retrospectively reviewed. The correlations of the mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) with microvascular invasion (MVI) or histological grade were analyzed. Cox regression analyses were performed to identify the predictors of recurrence-free survival (RFS) and overall survival (OS). A nomogram to predict RFS was established. P<0.05 was considered as statistically significant.ResultsA total of 97 patients (59 males and 38 females, 56.0 ± 10.9 years) were included in this study. The MK, MD, and ADC values were correlated with MVI or histological grade (P<0.01). With a median follow-up time of 41.2 months (range 12-69 months), 67 patients (69.1%) experienced recurrence and 41 patients (42.3%) were still alive. The median RFS and OS periods after LR were 29 and 45 months, respectively. The 1-, 3-, and 5-year RFS and OS rates were 88.7%, 41.2%, and 21.7% and 99.0%, 68.3%, and 25.6%, respectively. MK (P<0.001), PVT (P<0.001), and ADC (P=0.033) were identified as independent predictor factors for RFS. A nomogram including the MK value for RFS showed the best performance, and the C-index was 0.895.ConclusionThe MK value obtained from DKI is a potential predictive factor for recurrence and poor survival, which could provide valuable information for guiding the efficacy of LR in patients with large HCC.
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Deng Y, Li J, Xu H, Ren A, Wang Z, Yang D, Yang Z. Diagnostic Accuracy of the Apparent Diffusion Coefficient for Microvascular Invasion in Hepatocellular Carcinoma: A Meta-analysis. J Clin Transl Hepatol 2022; 10:642-650. [PMID: 36062283 PMCID: PMC9396311 DOI: 10.14218/jcth.2021.00254] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 10/13/2021] [Accepted: 10/27/2021] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND AND AIMS Microvascular invasion (MVI) is a major risk factor for the early recurrence of hepatocellular carcinoma (HCC) and it seriously worsens the prognosis. Accurate preoperative evaluation of the presence of MVI could greatly benefit the treatment management and prognosis prediction of HCC patients. The study aim was to evaluate the diagnostic performance of the apparent diffusion coefficient (ADC), a quantitative parameter for the preoperative diagnosis MVI in HCC patients. METHODS Original articles about diffusion-weighted imaging (DWI) and/or intravoxel incoherent motion (IVIM) conducted on a 3.0 or 1.5 Tesla magnetic resonance imaging (MRI) system indexed through January 17, 2021were collected from MEDLINE/PubMed, Web of Science, EMBASE, and the Cochrane Library. Methodological quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUROC) were calculated, and meta-regression analysis was performed using a bivariate random effects model through a meta-analysis. RESULTS Nine original articles with a total of 988 HCCs were included. Most studies had low bias risk and minimal applicability concerns. The pooled sensitivity, specificity and AUROC of the ADC value were 73%, 70%, and 0.78, respectively. The time interval between the index test and the reference standard was identified as a possible source of heterogeneity by subgroup meta-regression analysis. CONCLUSIONS Meta-analysis showed that the ADC value had moderate accuracy for predicting MVI in HCC. The time interval accounted for the heterogeneity.
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Affiliation(s)
- Yuhui Deng
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Medical Imaging Division, Heilongjiang Provincial Hospital, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Jisheng Li
- Department of Interventional Radiology, Yantai Penglai Traditional Chinese Medicine Hospital, Yantai, Shandong, China
| | - Hui Xu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Ahong Ren
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Dawei Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Correspondence to: Dawei Yang and Zhenghan Yang, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing 100050, China. ORCID: https://orcid.org/0000-0002-1868-2746 (DY) and https://orcid.org/0000-0003-3986-1732 (ZY). Tel: +86-13488676354 (DY) and +86-13910831365 (ZY), Fax: +86-10-63138490, E-mail: (DY) and (ZY)
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Correspondence to: Dawei Yang and Zhenghan Yang, Beijing Friendship Hospital, Capital Medical University, Yongan Road 95, West District, Beijing 100050, China. ORCID: https://orcid.org/0000-0002-1868-2746 (DY) and https://orcid.org/0000-0003-3986-1732 (ZY). Tel: +86-13488676354 (DY) and +86-13910831365 (ZY), Fax: +86-10-63138490, E-mail: (DY) and (ZY)
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12
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Chen YD, Zhang L, Zhou ZP, Lin B, Jiang ZJ, Tang C, Dang YW, Xia YW, Song B, Long LL. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. World J Gastroenterol 2022; 28:4399-4416. [PMID: 36159011 PMCID: PMC9453772 DOI: 10.3748/wjg.v28.i31.4399] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 02/05/2022] [Accepted: 07/25/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Microvascular invasion (MVI) of small hepatocellular carcinoma (sHCC) (≤ 3.0 cm) is an independent prognostic factor for poor progression-free and overall survival. Radiomics can help extract imaging information associated with tumor pathophysiology.
AIM To develop and validate radiomics scores and a nomogram of gadolinium ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for preoperative prediction of MVI in sHCC.
METHODS In total, 415 patients were diagnosed with sHCC by postoperative pathology. A total of 221 patients were retrospectively included from our hospital. In addition, we recruited 94 and 100 participants as independent external validation sets from two other hospitals. Radiomics models of Gd-EOB-DTPA-enhanced MRI and diffusion-weighted imaging (DWI) were constructed and validated using machine learning. As presented in the radiomics nomogram, a prediction model was developed using multivariable logistic regression analysis, which included radiomics scores, radiologic features, and clinical features, such as the alpha-fetoprotein (AFP) level. The calibration, decision-making curve, and clinical usefulness of the radiomics nomogram were analyzed. The radiomic nomogram was validated using independent external cohort data. The areas under the receiver operating curve (AUC) were used to assess the predictive capability.
RESULTS Pathological examination confirmed MVI in 64 (28.9%), 22 (23.4%), and 16 (16.0%) of the 221, 94, and 100 patients, respectively. AFP, tumor size, non-smooth tumor margin, incomplete capsule, and peritumoral hypointensity in hepatobiliary phase (HBP) images had poor diagnostic value for MVI of sHCC. Quantitative radiomic features (1409) of MRI scans) were extracted. The classifier of logistic regression (LR) was the best machine learning method, and the radiomics scores of HBP and DWI had great diagnostic efficiency for the prediction of MVI in both the testing set (hospital A) and validation set (hospital B, C). The AUC of HBP was 0.979, 0.970, and 0.803, respectively, and the AUC of DWI was 0.971, 0.816, and 0.801 (P < 0.05), respectively. Good calibration and discrimination of the radiomics and clinical combined nomogram model were exhibited in the testing and two external validation cohorts (C-index of HBP and DWI were 0.971, 0.912, 0.808, and 0.970, 0.843, 0.869, respectively). The clinical usefulness of the nomogram was further confirmed using decision curve analysis.
CONCLUSION AFP and conventional Gd-EOB-DTPA-enhanced MRI features have poor diagnostic accuracies for MVI in patients with sHCC. Machine learning with an LR classifier yielded the best radiomics score for HBP and DWI. The radiomics nomogram developed as a noninvasive preoperative prediction method showed favorable predictive accuracy for evaluating MVI in sHCC.
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Affiliation(s)
- Yi-Di Chen
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Ling Zhang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Zhi-Peng Zhou
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi Zhuang Autonomous Region, China
| | - Bin Lin
- Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin 541001, Guangxi Zhuang Autonomous Region, China
| | - Zi-Jian Jiang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Cheng Tang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
| | - Yi-Wu Dang
- Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning 5350021, Guangxi Zhuang Autonomous Region, China
| | - Yu-Wei Xia
- Department of Technology, Huiying Medical Technology (Beijing), Beijing 100192, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Li-Ling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
- Guangxi Key Laboratory of Immunology and Metabolism for Liver Diseases, First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
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A Scoring System for Predicting Microvascular Invasion in Hepatocellular Carcinoma Based on Quantitative Functional MRI. J Clin Med 2022; 11:jcm11133789. [PMID: 35807074 PMCID: PMC9267530 DOI: 10.3390/jcm11133789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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Liu B, Zeng Q, Huang J, Zhang J, Zheng Z, Liao Y, Deng K, Zhou W, Xu Y. IVIM using convolutional neural networks predicts microvascular invasion in HCC. Eur Radiol 2022; 32:7185-7195. [PMID: 35713662 DOI: 10.1007/s00330-022-08927-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/13/2022] [Accepted: 05/19/2022] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The study aimed to investigate the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging for prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) using convolutional neural networks (CNNs). METHODS This retrospective study included 114 patients with pathologically confirmed HCC from December 2014 to August 2021. All patients underwent MRI examination including IVIM sequence with 9 b-values preoperatively. First, 9 b-value images were superimposed in the channel dimension, and a b-value volume with a shape of 32 × 32 × 9 dimension was obtained. Secondly, an image resampling method was performed for data augmentation to generate more samples for training. Finally, deep features to predict MVI in HCC were directly derived from a b-value volume based on the CNN. Moreover, a deep learning model based on parameter maps and a fusion model combined with deep features of IVIM, clinical characteristics, and IVIM parameters were also constructed. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance for MVI prediction in HCC. RESULTS Deep features directly extracted from IVIM-DWI (0.810 (range 0.760, 0.829)) using CNN yielded better performance for prediction of MVI than those from IVIM parameter maps (0.590 (range 0.555, 0.643)). Furthermore, the performance of the fusion model combined with deep features of IVIM-DWI, clinical features (α-fetoprotein (AFP) level and tumor size), and apparent diffusion coefficient (ADC) (0.829 (range 0.776, 0.848)) was slightly improved. CONCLUSIONS Deep learning with CNN based on IVIM-DWI can be conducive to preoperative prediction of MVI in patients with HCC. KEY POINTS • Deep learning assessment of IVIM data for prediction of MVI in HCC can overcome the unstable and low performance of IVIM parameters. • Deep learning model based on IVIM performs better than parameter values, clinical features, and deep learning model based on parameter maps. • The fusion model combined with deep features of IVIM, clinical characteristics, and ADC yields better performance for prediction of MVI than the model only based on IVIM.
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Affiliation(s)
- Baoer Liu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, People's Republic of China
| | - Qingyuan Zeng
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, 232 Wide Ring East Road, Panyu District, Guangzhou, 510006, People's Republic of China
| | - Jianbin Huang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, People's Republic of China
| | - Jing Zhang
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, People's Republic of China
| | - Zeyu Zheng
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, People's Republic of China
| | - Yuting Liao
- GE Healthcare, 10/F, GE Tower, No.87 Hua Cheng Avenue, Pearl River New City, Tianhe District, Guangzhou, 510623, People's Republic of China
| | - Kan Deng
- Philips Healthcare, 18F, Block B, China International Center, No.33 Zhongshan 3rd Road, Guangzhou, 510055, People's Republic of China
| | - Wu Zhou
- School of Medical Information Engineering, Guangzhou University of Chinese Medicine, 232 Wide Ring East Road, Panyu District, Guangzhou, 510006, People's Republic of China.
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, People's Republic of China.
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Çelebi F, Görmez A, Serkan Ilgun A, Tokat Y, Cem Balcı N. The role of 18F- FDG PET/MRI in preoperative prediction of MVI in patients with HCC. Eur J Radiol 2022; 149:110196. [DOI: 10.1016/j.ejrad.2022.110196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 12/12/2022]
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Wang G, Jian W, Cen X, Zhang L, Guo H, Liu Z, Liang C, Zhou W. Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning. Acad Radiol 2021; 28 Suppl 1:S118-S127. [PMID: 33303346 DOI: 10.1016/j.acra.2020.11.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 11/03/2020] [Accepted: 11/05/2020] [Indexed: 02/06/2023]
Abstract
RATIONALE AND OBJECTIVES To investigate the value of diffusion-weighted magnetic resonance imaging for the prediction of microvascular invasion (MVI) of Hepatocellular Carcinoma (HCC) using Convolutional Neural Networks (CNN). MATERIAL AND METHODS This study was approved by the local institutional review board and the patients' informed consent was waived. Consecutive 97 subjects with 100 HCCs from July 2012 to October 2018 with surgical resection were retrieved. All subjects with diffusion-weighted imaging (DWI) examinations were performed with single-shot echo-planar imaging in a breath-hold routine. DWI parameters were three b values of 0,100,600 sec/mm2. First, apparent diffusion coefficients (ADC) images were computed by mono-exponentially fitting the three b-value points. Then, multiple 2D axial patches (28 × 28) of HCCs from b0, b100, b600, and ADC images were extracted to increase the dataset for training the CNN model. Finally, the fusion of deep features derived from three b value images and ADC was conducted based on the CNN model for MVI prediction. The data set was split into the training set (60 HCCs) and the independent test set (40 HCCs). The output probability of the deep learning model in the MVI prediction of HCCs was assessed by the independent student's t-test for data following a normal distribution and Mann-Whitney U test for data violating the normal distribution. Receiver operating characteristic curve and area under the curve (AUC) were also used to assess the performance for MVI prediction of HCCs in the fixed test set. RESULTS Deep features in b600 images yielded better performance (AUC = 0.74, p = 0.004) for MVI prediction than b0 (AUC = 0.69, p = 0.023) and b100 (AUC = 0.734, p = 0.011). Comparatively, deep features in the ADC map obtained lower performance (AUC = 0.71, p = 0.012) than that of the higher b value images (b600) for MVI prediction. Furthermore, the fusion of deep features from the b0, b100, b600, and ADC images yielded the best results (AUC = 0.79, p = 0.002) for MVI prediction. CONCLUSION Fusion of deep features derived from DWI images concerning the three b-value images and the ADC image yields better performance for MVI prediction.
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Katabathina VS, Marji H, Khanna L, Ramani N, Yedururi S, Dasyam A, Menias CO, Prasad SR. Decoding Genes: Current Update on Radiogenomics of Select Abdominal Malignancies. Radiographics 2021; 40:1600-1626. [PMID: 33001791 DOI: 10.1148/rg.2020200042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Technologic advances in chromosomal analysis and DNA sequencing have enabled genome-wide analysis of cancer cells, yielding considerable data on the genetic basis of malignancies. Evolving knowledge of tumor genetics and oncologic pathways has led to a better understanding of histopathologic features, tumor classification, tumor biologic characteristics, and imaging findings and discovery of targeted therapeutic agents. Radiogenomics is a rapidly evolving field of imaging research aimed at correlating imaging features with gene mutations and gene expression patterns, and it may provide surrogate imaging biomarkers that may supplant genetic tests and be used to predict treatment response and prognosis and guide personalized treatment options. Multidetector CT, multiparametric MRI, and PET with use of multiple radiotracers are some of the imaging techniques commonly used to assess radiogenomic associations. Select abdominal malignancies demonstrate characteristic imaging features that correspond to gene mutations. Recent advances have enabled us to understand the genetics of steatotic and nonsteatotic hepatocellular adenomas, a plethora of morphologic-molecular subtypes of hepatic malignancies, a variety of clear cell and non-clear cell renal cell carcinomas, a myriad of hereditary and sporadic exocrine and neuroendocrine tumors of the pancreas, and the development of targeted therapeutic agents for gastrointestinal stromal tumors based on characteristic KIT gene mutations. Mutations associated with aggressive phenotypes of these malignancies can sometimes be predicted on the basis of their imaging characteristics. Radiologists should be familiar with the genetics and pathogenesis of common cancers that have associated imaging biomarkers, which can help them be integral members of the cancer management team and guide clinicians and pathologists. Online supplemental material is available for this article. ©RSNA, 2020 See discussion on this article by Luna (pp 1627-1630).
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Affiliation(s)
- Venkata S Katabathina
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Haneen Marji
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Lokesh Khanna
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Nisha Ramani
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Sireesha Yedururi
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Anil Dasyam
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Christine O Menias
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
| | - Srinivasa R Prasad
- From the Department of Radiology, University of Texas Health at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229 (V.S.K., H.M., L.K.); Departments of Radiology (S.Y., S.R.P.) and Pathology (N.R.), University of Texas MD Anderson Cancer Center, Houston, Tex; Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, Pa (A.D.); and Department of Radiology, Mayo Clinic, Scottsdale, Ariz (C.O.M.)
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Zhou H, Sun J, Jiang T, Wu J, Li Q, Zhang C, Zhang Y, Cao J, Sun Y, Jiang Y, Liu Y, Zhou X, Huang P. A Nomogram Based on Combining Clinical Features and Contrast Enhanced Ultrasound LI-RADS Improves Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Front Oncol 2021; 11:699290. [PMID: 34307168 PMCID: PMC8297520 DOI: 10.3389/fonc.2021.699290] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/22/2021] [Indexed: 12/12/2022] Open
Abstract
PURPOSES To establish a predictive model incorporating clinical features and contrast enhanced ultrasound liver imaging and reporting and data system (CEUS LI-RADS) for estimation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. METHODS In the retrospective study, 127 HCC patients from two hospitals were allocated as training cohort (n=98) and test cohorts (n=29) based on cutoff time-point, June 2020. Multivariate regression analysis was performed to identify independent indicators for developing predictive nomogram models. The area under receiver operating characteristic (AUC) curve was also determined to establish the diagnostic performance of different predictive models. Corresponding sensitivities and specificities of different models at the cutoff nomogram value were compared. RESULTS In the training cohort, clinical information (larger tumor size, higher AFP level) and CEUS LR-M were significantly correlated with the presence of MVI (all p<0.05). By incorporating clinical information and CEUS LR-M, the predictive model (LR-M+Clin) achieved a desirable diagnostic performance (AUC=0.80 and 0.84) in both cohorts at nomogram cutoff score value of 89. The sensitivity of LR-M+Clin when predicting MVI in HCC patients was higher than that of the clinical model alone (86.7% vs. 46.7%, p=0.027), while specificities were 78.6% and 85.7% (p=0.06), respectively, in the test cohort. In addition, LR-M+Clin exhibited similar AUC and specificity, but a significantly higher sensitivity (86.7%) than those of LR-M alone and LR-5(No)+Clin (both sensitivities=73.3%, both p=0.048). CONCLUSION The predictive model incorporating CEUS LR-M and clinical features was able to predict the MVI status of HCC and is a potential reliable preoperative tool for informing treatment.
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Affiliation(s)
- Hang Zhou
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiawei Sun
- Department of In-Patient Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tao Jiang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaqi Wu
- Department of In-Patient Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Qunying Li
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Chao Zhang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Zhang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Cao
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yu Sun
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yifan Jiang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yajing Liu
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xianli Zhou
- Department of In-Patient Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Pintong Huang
- Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Gao F, Qiao K, Yan B, Wu M, Wang L, Chen J, Shi D. Hybrid network with difference degree and attention mechanism combined with radiomics (H-DARnet) for MVI prediction in HCC. Magn Reson Imaging 2021; 83:27-40. [PMID: 34147593 DOI: 10.1016/j.mri.2021.06.018] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 02/05/2021] [Accepted: 06/15/2021] [Indexed: 12/12/2022]
Abstract
MVI is a risk assessment factor related to hepatocellular carcinoma (HCC) recurrence after hepatectomy or liver transplantation. The goal of this paper is to study the preoperative diagnosis of microvascular invasion (MVI) by using a deep learning algorithm in non-contrast T2 weighted magnetic resonance imaging (MRI) images instead of pathological images. Herein, an ensemble learning algorithm named H-DARnet-based on the difference degree and attention mechanism, combined with radiomics, for MVI prediction-is proposed. Our hybrid network combines the fine-grained, high-level semantic, and radiomics features and exhibits a rich multilevel-feature architecture composed of global-local-prior knowledge with suitable complementarity. The total loss function comprises two regularization items--the triplet and the cross-entropy loss function--which are selected for the triplet network and SE-DenseNet, respectively. The hard triplet sample selection strategy for a triplet network and data augmentation for small-scale liver image datasets in convolutional neural network (CNN) training is indispensable. For 200 patch level test samples (135 positive samples and 65 negative samples), our method can obtain the best prediction results, the AUC, sensitivity, and specificity were 0.826, 79.5% and 73.8%, respectively. The experiment results show that MVI can be predicted by using MRI images, and the proposed method is better than other deep learning algorithms and hand-crafted feature algorithms. The proposed ensemble learning algorithm is proved to be an effective method for MVI prediction.
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Affiliation(s)
- Fei Gao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, ZhengZhou, China
| | - Kai Qiao
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, ZhengZhou, China
| | - Bin Yan
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, ZhengZhou, China.
| | - Minghui Wu
- Department of Radiology, Henan Provincial People's Hospital, ZhengZhou, China
| | - Linyuan Wang
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, ZhengZhou, China
| | - Jian Chen
- Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, ZhengZhou, China
| | - Dapeng Shi
- Department of Radiology, Henan Provincial People's Hospital, ZhengZhou, China
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Comparison of Conventional Gadoxetate Disodium-Enhanced MRI Features and Radiomics Signatures With Machine Learning for Diagnosing Microvascular Invasion. AJR Am J Roentgenol 2021; 216:1510-1520. [PMID: 33826360 DOI: 10.2214/ajr.20.23255] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVE. This study aimed to determine the best model for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using conventional gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (gadoxetate disodium)-enhanced MRI features and radiomics signatures with machine learning. MATERIALS AND METHODS. This retrospective study included 269 patients with a postoperative pathologic diagnosis of HCC. Gadoxetate disodium-enhanced MRI features were assessed, including T1 relaxation time, tumor margin, tumor size, peritumoral enhancement, peritumoral hypointensity, and ADC. Radiomics models were constructed and validated by machine learning. The least absolute shrinkage and selection operator (LASSO) was used for feature selection, and radiomics-based LASSO models were constructed with six classifiers. Predictive capability was assessed using the ROC AUC. RESULTS. Histologic examination confirmed MVI in 111 (41.3%) of the 269 patients. ADC value, nonsmooth tumor margin, and 20-minute T1 relaxation time showed diagnostic accuracy with AUC values of 0.850, 0.847, and 0.846, respectively (p < .05 for all). A total of 1395 quantitative imaging features were extracted. In the hepatobiliary phase (HBP) model, the support vector machine (SVM), extreme gradient boosting (XGBoost), and logistic regression (LR) classifiers showed greater diagnostic efficiency for predicting MVI, with AUCs of 0.942, 0.938, and 0.936, respectively (p < .05 for all). CONCLUSION. ADC value, nonsmooth tumor margin, and 20-minute T1 relaxation time show high diagnostic accuracy for predicting MVI. Radiomics signatures with machine learning can further improve the ability to predict MVI and are best modeled during HBP. The SVM, XGBoost, and LR classifiers may serve as potential biomarkers to evaluate MVI.
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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: 87] [Impact Index Per Article: 29.0] [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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Wei H, Jiang H, Liu X, Qin Y, Zheng T, Liu S, Zhang X, Song B. Can LI-RADS imaging features at gadoxetic acid-enhanced MRI predict aggressive features on pathology of single hepatocellular carcinoma? Eur J Radiol 2020; 132:109312. [PMID: 33022551 DOI: 10.1016/j.ejrad.2020.109312] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/16/2020] [Accepted: 09/24/2020] [Indexed: 02/05/2023]
Abstract
PURPOSE To investigate whether Liver Imaging Reporting and Data System (LI-RADS) imaging features at preoperative gadoxetic acid-enhanced MRI can predict microvascular invasion (MVI) and histologic grade of hepatocellular carcinoma (HCC) and to evaluate their associations with recurrence after curative resection of single HCC. MATERIALS AND METHODS From July 2015 to September 2018, 111 consecutive patients with pathologically confirmed HCC who underwent gadoxetic acid-enhanced MRI within 1 month before surgery were included in this retrospective study. Significant MRI findings and clinical parameters for predicting MVI, high-grade HCCs and postoperative recurrence were identified by logistic regression model and Cox proportional hazards model. RESULTS Twenty-six of 111 (23.4 %) patients had MVI and 36 of 111 (32.4 %) patients had high-grade HCCs, whereas 44 of 95 (46.3 %) patients experienced recurrence. Tumor size > 5 cm (OR = 9.852; p < 0.001) and absence of nodule-in-nodule architecture (OR = 8.302; p = 0.001) were independent predictors of MVI. Enhancing capsule (OR = 4.396; p = 0.004) and corona enhancement (OR = 3.765; p = 0.021) were independent predictors of high-grade HCCs. Blood products in mass (HR = 2.275; p = 0.009), corona enhancement (HR = 4.332; p < 0.001), and serum AFP level > 400 ng/mL (HR = 2.071; p = 0.023) were independent predictors of recurrence. CONCLUSION LI-RADS imaging features can be used as potential biomarkers for predicting aggressive pathologic features and recurrence of HCC. The identification of prognostic LI-RADS imaging features may facilitate the selection of surgical candidates and optimize the management of HCC patients.
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Affiliation(s)
- Hong Wei
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Hanyu Jiang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Xijiao Liu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Yun Qin
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | - Tianying Zheng
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China
| | | | | | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China.
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Zhou Y, Zhou G, Gao X, Xu C, Wang X, Xu P. Apparent diffusion coefficient value of mass-forming intrahepatic cholangiocarcinoma: a potential imaging biomarker for prediction of lymph node metastasis. Abdom Radiol (NY) 2020; 45:3109-3118. [PMID: 32107582 DOI: 10.1007/s00261-020-02458-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To compare the differences of MR features between mass-forming intrahepatic cholangiocarcinoma (IMCC) with and without lymph node metastasis (LNM) and to search for new imaging biomarkers for predicting LNM. MATERIALS AND METHODS The study included 91 patients with histopathologically confirmed single IMCC (20 patients with LNM and 71 patients without LNM). Findings of preoperative MR imaging including diffusion-weighted imaging (DWI) (b value 0, 500 mm2/s) were analyzed and apparent diffusion coefficient (ADC) values (b = 500 mm2/s) were calculated. Logistic regression analysis was performed to identify independent predictors of LNM. The diagnostic performance of independent predictors was assessed by receiver operating characteristic (ROC) and area under the curve (AUC) was compared. RESULTS Larger tumor size (p = 0.001), diameter of largest lymph node (LN) > 1 cm (p < 0.001), higher ADC value of primary IMCC lesion (ADCIMCC value) (p = 0.001), and positive CA19-9 level (p = 0.018) were correlated with LNM. Multivariate logistic regression analysis demonstrated that ADCIMCC value (odds ratio, 3.347; p = 0.001) and diameter of largest LN > 1 cm (odds ratio, 7.571; p = 0.004) were independent predictors of LNM. The AUCs for ADCIMCC value, diameter of largest LN > 1 cm,and combined method (the combination of ADCIMCC value and diameter of largest LN > 1 cm) were 0.782, 0.701,and 0.857, respectively. The AUC for combined method was significantly higher than that of diameter of largest LN > 1 cm (p = 0.033). CONCLUSION ADCIMCC value can be a potential imaging biomarker for predicting LNM of IMCC, especially in combination with diameter of largest LN > 1 cm.
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Affiliation(s)
- Yang Zhou
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Guofeng Zhou
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Xuan Gao
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Chen Xu
- Department of Pathology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China
| | - Xiaolin Wang
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China
| | - Pengju Xu
- Shanghai Institute of Medical Imaging, Shanghai, 200032, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
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Huang J, Tian W, Zhang L, Huang Q, Lin S, Ding Y, Liang W, Zheng S. Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis. Front Oncol 2020; 10:887. [PMID: 32676450 PMCID: PMC7333535 DOI: 10.3389/fonc.2020.00887] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Accepted: 05/05/2020] [Indexed: 12/12/2022] Open
Abstract
Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis. Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75–0.80; I2 = 70.7%] and 0.78 (95% CI: 0.76–0.81; I2 = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71–0.75; I2 = 83.7%) and 0.82 (95% CI: 0.80–0.83; I2 = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference. Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.
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Affiliation(s)
- Jiacheng Huang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Lab of Combined Multi-Organ Transplantation, Ministry of Public Health, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Wuwei Tian
- College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, China
| | - Lele Zhang
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Lab of Combined Multi-Organ Transplantation, Ministry of Public Health, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Qiang Huang
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Shengzhang Lin
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yong Ding
- College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, China
| | - Wenjie Liang
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Shusen Zheng
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Lab of Combined Multi-Organ Transplantation, Ministry of Public Health, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
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25
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Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology. Eur Radiol 2020; 30:5327-5336. [PMID: 32367417 DOI: 10.1007/s00330-020-06895-6] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 03/04/2020] [Accepted: 04/14/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To assess the accuracy of gadobenate-enhanced MRI for predicting microvascular invasion (MVI) in patients operated for hepatocellular carcinoma (HCC). METHODS The 164 patients who met the inclusion criteria were assigned to one of two groups: the MVI-positive group and the MVI-negative group. Imaging results were compared between the two groups using the Kruskal test, chi-square test, independent sample t test, and logistic regression analysis. RESULTS Differences in the capsule (p = 0.037) and margin (p = 0.004) of the tumor, rim enhancement (p = 0.002), peritumoral enhancement in the arterial phase (p < 0.001), and peritumoral hypointensity in the hepatobiliary phase (HBP) (p < 0.001) were statistically significant. The results of multivariate analysis identified rim enhancement in the arterial phase (odds ratio (OR) = 2.115; 95% confidence interval (CI), 1.002-4.464; p = 0.049) and peritumoral hypointensity in the HBP (OR = 5.836; 95% CI, 2.442-13.948; p < 0.001) as independent risk factors for MVI. Use of the two predictors in combination identified 32.79% (20/61) of HCCs with MVI with a specificity of 95.15% (98/103). CONCLUSIONS Rim enhancement in the arterial phase and peritumoral hypointensity in the HBP were identified as independent risk factors for MVI in patients with HCC. KEY POINTS • Rim enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for microvascular invasion in patients with HCC. • Use of the two predictors in combination had a sensitivity of 32.79% and a specificity of 95.15% for predicting microvascular invasion.
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Rao C, Wang X, Li M, Zhou G, Gu H. Value of T1 mapping on gadoxetic acid-enhanced MRI for microvascular invasion of hepatocellular carcinoma: a retrospective study. BMC Med Imaging 2020; 20:43. [PMID: 32345247 PMCID: PMC7189724 DOI: 10.1186/s12880-020-00433-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 03/17/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND To evaluate the utility of non-invasive parameters derived from T1 mapping and diffusion-weighted imaging (DWI) on gadoxetic acid-enhanced MRI for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS A total of 94 patients with single HCC undergoing partial hepatectomy was analyzed in this retrospective study. Preoperative T1 mapping and DWI on gadoxetic acid-enhanced MRI was performed. The parameters including precontrast, postcontrast and reduction rate of T1 relaxation time and apparent diffusion coefficient (ADC) values were measured for differentiating MVI-positive HCCs (n = 38) from MVI-negative HCCs (n = 56). The receiver operating characteristic curve (ROC) was analyzed to compare the diagnostic performance of the calculated parameters. RESULTS MVI-positive HCCs demonstrated a significantly lower reduction rate of T1 relaxation time than that of MVI-negative HCCs (39.4% vs 49.9, P < 0.001). The areas under receiver operating characteristic curve (AUC) were 0.587, 0.728, 0.824, 0,690 and 0.862 for the precontrast, postcontrast, reduction rate of T1 relaxation time, ADC and the combination of reduction rate and ADC, respectively. The cut-off value of the reduction rate and ADC calculated through maximal Youden index in ROC analyses was 44.9% and 1553.5 s/mm2. To achieve a better diagnostic performance, the criteria of combining the reduction rate lower than 44.9% and the ADC value lower than 1553.5 s/mm2 was proposed with a high specificity of 91.8% and accuracy of 80.9%. CONCLUSIONS The proposed criteria of combining the reduction rate of T1 relaxation time lower than 44.9% and the ADC value lower than 1553.5 s/mm2 on gadoxetic acid-enhanced MRI holds promise for evaluating MVI status of HCC.
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Affiliation(s)
- Chenyi Rao
- Medical College, Nantong University, Nantong, Jiangsu, China
| | - Xinquan Wang
- Medical College, Nantong University, Nantong, Jiangsu, China.,Department of Radiology, Affiliated Hospital of Nantong University, 20 Xisi Rd., Nantong, 226001, Jiangsu, China
| | - Minda Li
- Medical College, Nantong University, Nantong, Jiangsu, China.,Department of Radiology, Affiliated Hospital of Nantong University, 20 Xisi Rd., Nantong, 226001, Jiangsu, China
| | - Guofeng Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hongmei Gu
- Medical College, Nantong University, Nantong, Jiangsu, China. .,Department of Radiology, Affiliated Hospital of Nantong University, 20 Xisi Rd., Nantong, 226001, Jiangsu, China.
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Nomogram to Assist in Surgical Plan for Hepatocellular Carcinoma: a Prediction Model for Microvascular Invasion. J Gastrointest Surg 2019; 23:2372-2382. [PMID: 30820799 DOI: 10.1007/s11605-019-04140-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2018] [Accepted: 01/23/2019] [Indexed: 01/31/2023]
Abstract
BACKGROUND Microvascular invasion (MVI) relates to poor survival in hepatocellular carcinoma (HCC) patients. In this study, we aim at developing a nomogram for MVI prediction and potential assistance in surgical planning. METHODS A total of 357 patients were assigned to training (n = 257) and validation (n = 100) cohort. Univariate and multivariate analyses were used to reveal preoperative predictors for MVI. A nomogram incorporating independent predictors was constructed and validated. Disease-free survival was compared between patients, and the potential of the predicted MVI in making surgical procedure was also explored. RESULTS Pathological examination confirmed MVI in 140 (39.2%) patients. Imaging features including larger tumor, intra-tumoral artery, tumor type, and higher serum AFP independently correlated with MVI. The nomogram showed desirable performance with an AUROC of 0.803 (95% CI, 0.746-0.860) and 0.814 (95% CI, 0.720-0.908) in the training and validation cohorts, respectively. Good calibration were also revealed by calibration curve in both cohorts. The decision curve analysis indicated that the prediction nomogram was of promising usefulness in clinical work. In addition, survival analysis revealed that patients with positive-predicted MVI suffered a higher risk of early recurrence (P < 0.01). There was no difference in disease-free survival between anatomic or non-anatomic resection in large HCC or small HCC without nomogram-predicted MVI. However, anatomic resection improved disease-free survival in small HCC with nomogram-predicted MVI. CONCLUSIONS The nomogram obtained desirable results in predicting MVI. Patients with predicted MVI were associated with early recurrence and anatomic resection was recommended for small HCC patients with predicted MVI.
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Chuang YH, Ou HY, Yu CY, Chen CL, Weng CC, Tsang LLC, Hsu HW, Lim WX, Huang TL, Cheng YF. Diffusion-weighted imaging for identifying patients at high risk of tumor recurrence following liver transplantation. Cancer Imaging 2019; 19:74. [PMID: 31730015 PMCID: PMC6858682 DOI: 10.1186/s40644-019-0264-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 11/07/2019] [Indexed: 12/15/2022] Open
Abstract
Background Tumor recurrence is the major risk factor affecting post-transplant survival. In this retrospective study, we evaluate the prognostic values of magnetic resonance (MR) diffusion-weighted imaging (DWI) in liver transplantation for hepatocellular carcinoma (HCC). Methods From April 2014 to September 2016, 106 HCC patients receiving living donor liver transplantation (LDLT) were enrolled. Nine patients were excluded due to postoperative death within 3 months and incomplete imaging data. The association between tumor recurrence, explant pathologic findings, and DWI parameters was analyzed (tumor-to-liver diffusion weighted imaging ratio, DWIT/L; apparent diffusion coefficients, ADC). The survival probability was calculated using the Kaplan–Meier method. Results Sixteen of 97 patients (16%) developed tumor recurrence during the follow-up period (median of 40.9 months; range 5.2–56.5). In those with no viable tumor (n = 65) on pretransplant imaging, recurrence occurred only in 5 (7.6%) patients. Low minimum ADC values (p = 0.001), unfavorable tumor histopathology (p < 0.001) and the presence of microvascular invasion (p < 0.001) were risk factors for tumor recurrence, while ADCmean (p = 0.111) and DWIT/L (p = 0.093) showed no significant difference between the groups. An ADCmin ≤ 0.88 × 10− 3 mm2/s was an independent factor associated with worse three-year recurrence-free survival (94.4% vs. 23.8%) and overall survival rates (100% vs. 38.6%). Conclusions Quantitative measurement of ADCmin is a promising prognostic indicator for predicting tumor recurrence after liver transplantation.
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Affiliation(s)
- Yi-Hsuan Chuang
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Hsin-You Ou
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Chun-Yen Yu
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Chao-Long Chen
- Liver Transplantation Program, Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Ching-Chun Weng
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Leo Leung-Chit Tsang
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Hsien-Wen Hsu
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Wei-Xiong Lim
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Tung-Liang Huang
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China
| | - Yu-Fan Cheng
- Liver Transplantation Program, Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, 123 Dapi Rd, Niaosong Dist, Kaohsiung, Taiwan, Republic of China.
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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: 1.6] [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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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: 12] [Impact Index Per Article: 2.4] [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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Diffusion-weighted imaging of hepatocellular carcinoma before and after transarterial chemoembolization: role in survival prediction and response evaluation. Abdom Radiol (NY) 2019; 44:2740-2750. [PMID: 31069479 DOI: 10.1007/s00261-019-02030-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Survival outcomes of patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) are heterogeneous. Measuring the apparent diffusion coefficient (ADC) using diffusion-weighted imaging (DWI) may improve overall survival prediction. AIM To assess the value of measuring the ADC before and after TACE in predicting overall survival. METHODS A retrospective analysis was performed in HCC patients treated with TACE at a tertiary referral center between 2008 and 2017. The ADC values and changes in ADC value (ΔADC) of HCC lesions (≥ 1 cm) and liver parenchyma were assessed by DWI ≤ 3 months before and after first TACE. Pre- and post-TACE ADC values were compared with tumor response according to mRECIST and correlated with overall survival (OS) in a univariable and multivariable Cox-regression analysis. RESULTS A total of 89 patients were included, mostly Child-Pugh A (85%) and BCLC stage B (53%) with a median OS of 21.7 months (95% CI 17.6-25.9). Tumor ADC increased from 1081 mm2/s before (IQR 964-1225) to 1328 mm2/s (IQR 1197-1560) after TACE (p < 0.001). Responders according to mRECIST showed a higher ΔADC after first TACE than non-responders (26 vs. 14%, p = 0.048). Pre-TACE ADC and ΔADC were not significantly associated with OS in both univariable and multivariable analysis, whereas response according to mRECIST remained an independent predictor of OS. CONCLUSION mRECIST was confirmed as an independent prognostic factor of OS, but pre- or post-TACE ADC measurements were not. Response according to mRECIST was associated with a higher increase in ADC than non-response.
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Lim C, Salloum C, Chalaye J, Lahat E, Costentin CE, Osseis M, Itti E, Feray C, Azoulay D. 18F-FDG PET/CT predicts microvascular invasion and early recurrence after liver resection for hepatocellular carcinoma: A prospective observational study. HPB (Oxford) 2019; 21:739-747. [PMID: 30401520 DOI: 10.1016/j.hpb.2018.10.007] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 09/17/2018] [Accepted: 10/10/2018] [Indexed: 12/12/2022]
Abstract
BACKGROUND This study assessed the prognostic value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) in the prediction of MVI and early recurrence following resection. METHOD This prospective study (ClinicalTrials.gov ID: NCT02145013) included 78 consecutive HCC patients who underwent 18F-FDG PET/CT before curative-intent resection from 2014 to 2017. Prognostic factors available before surgery for predicting MVI and early recurrence (≤2 years) were identified by univariate and multivariate analyses. RESULTS The 18F-FDG PET/CT result was positive in 30 (38%) patients. MVI was present in 33% (26/78) of specimens. Early recurrence occurred in 19% (14/74) of surviving patients. PET/CT positivity was the sole independent predictor of MVI (odds ratio [OR] = 3.6, 95% confidence interval [CI] = 1.1-11.2; p = 0.03), with a specificity and sensitivity for predicting MVI of 73% and 62%, respectively. Analysis of variables available before surgery showed that PET/CT positivity (hazard ratio [HR] = 5.8, 95% CI = 1.6-20.4; p = 0.006) and the male sex (HR = 6.6; 95% CI = 1.8-24.2; p = 0.005) were independent predictors of early recurrence. CONCLUSION 18F-FDG PET/CT predicts MVI and early recurrence after surgery for HCC and could be used to select patients for neoadjuvant treatment.
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Affiliation(s)
- Chetana Lim
- Department of Hepatobiliary and Pancreatic Surgery and Liver Transplantation, Henri Mondor Hospital, Créteil APHP, France
| | - Chady Salloum
- Department of Hepatobiliary and Pancreatic Surgery and Liver Transplantation, Henri Mondor Hospital, Créteil APHP, France
| | - Julia Chalaye
- Department of Nuclear Medicine, Henri Mondor Hospital, Créteil APHP, France
| | - Eylon Lahat
- Department of Hepatobiliary and Pancreatic Surgery and Liver Transplantation, Henri Mondor Hospital, Créteil APHP, France
| | | | - Michael Osseis
- Department of Hepatobiliary and Pancreatic Surgery and Liver Transplantation, Henri Mondor Hospital, Créteil APHP, France
| | - Emmanuel Itti
- Department of Nuclear Medicine, Henri Mondor Hospital, Créteil APHP, France
| | - Cyrille Feray
- Department of Nuclear Medicine, Henri Mondor Hospital, Créteil APHP, France
| | - Daniel Azoulay
- Department of Hepatobiliary and Pancreatic Surgery and Liver Transplantation, Henri Mondor Hospital, Créteil APHP, France.
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Segmental Distribution of Hepatocellular Carcinoma Correlates with Microvascular Invasion in Liver Explants Undergoing Transplantation. J Cancer Epidemiol 2019; 2019:8534372. [PMID: 31186641 PMCID: PMC6521314 DOI: 10.1155/2019/8534372] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/12/2019] [Accepted: 04/15/2019] [Indexed: 12/13/2022] Open
Abstract
Introduction Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients is a poor prognostic factor after liver transplantation and/or resection. Any correlation between MVI and segmental location of HCC has yet to be studied. Our aim is to evaluate the segmental location of HCC and any correlation with the presence of MVI, portal vein thrombosis (PVT) in explanted livers, and the recurrence of HCC after transplantation. Another objective of the study is to assess the treatment history (ablation or transarterial chemoembolization (TACE)) and size of the tumor with respect to the risk of MVI. Methods A single center, retrospective chart review, including 98 HCC patients, aged 18 years and older who had liver transplantation in our institute between 2012 and 2017. We reviewed the radiological images of the HCC tumors, the pathological findings of the explanted livers, and the follow-up imaging after transplantation. Results 98 patients with the diagnosis of HCC underwent liver transplantation between 2012 and 2017. The mean age of the cohort was 63 ± 8.2. Males represented 75% and Caucasian race represented 75% of the cohort. The most common etiology of cirrhosis was chronic hepatitis C virus infection followed by alcohol abuse and nonalcoholic steatohepatitis (NASH) with percentages of 50%, 23%, and 10%, respectively. Microvascular invasion was found in 16% of the patients while PVT and the recurrence of HCC were found in 17% and 6 % of the cohort, respectively. MVI was found in 10 single HCC and 6 multifocal HCC. Right lobe HCC had more MVI when compared to the left and multilobar HCC, with percentages of 11%, 2%, and 3%, respectively. Localization of HCC in segment 8 was associated with the highest percentage of MVI when compared to all other segments. The risk of MVI in segment 8 HCC was 3.5 times higher than the risk from the other segments (p=0.002) while no vascular invasion was found in segments 1, 3, and 5. The risk of vascular invasion in untreated HCC is 3 times the risk in treated HCC (P=0.03). Conclusion Our data indicate that the risk of microvascular invasion is highest in tumors localized to segment 8. The size and number of HCC tumors were not associated with an increased risk of microvascular invasion.
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The utility of diffusion-weighted imaging in improving the sensitivity of LI-RADS classification of small hepatic observations suspected of malignancy. Abdom Radiol (NY) 2019; 44:1773-1784. [PMID: 30603882 DOI: 10.1007/s00261-018-01887-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
PURPOSE We investigated the added value of diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) in the categorization of small hepatic observation (≤ 20 mm) detected in patients with chronic liver disease in reference to LI-RADS (liver imaging reporting and data system) classification system. METHODS We prospectively evaluated 165 patients with chronic liver disease with small hepatic observations (≤ 20 mm) which were previously categorized as LI-RADS grade 3-5 on dynamic contrast-enhanced CT (DCE-CT). All patients were submitted to a functional MRI including DCE and DWI. Using LI-RADS v2017, two radiologists independently evaluated the observations and assigned a LI-RADS category to each observation using DCE-MRI alone and combined DCE-MRI and DWI/ADC. In the combined technique, the radiologists assigned a LI-RADS category based on a modified LI-RADS criteria in which restricted diffusion on DWI was considered a major feature of HCC. We evaluated the inter-reader agreement with Kappa statistics and compared the diagnostic performance of the LI-RADS with two imaging techniques by Fisher's exact test using histopathology as the reference standard. RESULTS Combined technique in LI-RADS yielded better sensitivities (reader 1, 97% [65/67]; reader 2, 95.5% [64/67]) for HCC diagnosis than DCE-MRI alone (reader 1, 80.6% [54/67], p = 0.005; reader 2, 83.6% [56/67], p = 0.04). The specificities were insignificantly lower in combined technique (reader 1, 88.4% [107/121]; reader 2, 77.7% [94/121]) than in DCE-MRI alone (reader 1, 90.9% [110/121], p = 0.67; reader 2, 79.3% [96/121], p = 0.88). The inter-reader agreement of the LI-RADS scores between combined technique and DCE-MRI was good (κ = 0.765). CONCLUSION The use of DWI/ADC as an additional major criterion, improved the sensitivity of LI-RADS in the diagnosis of HCC while keeping high specificity.
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Huang K, Dong Z, Cai H, Huang M, Peng Z, Xu L, Jia Y, Song C, Li ZP, Feng ST. Imaging biomarkers for well and moderate hepatocellular carcinoma: preoperative magnetic resonance image and histopathological correlation. BMC Cancer 2019; 19:364. [PMID: 30999947 PMCID: PMC6472074 DOI: 10.1186/s12885-019-5574-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 04/03/2019] [Indexed: 12/20/2022] Open
Abstract
Background Our aim of the study is to investigate the feasibility of preoperative prediction for hepatocellular carcinoma (HCC) histological grading using gadoxetic acid-enhanced magnetic resonance imaging (MRI). Methods This study included one hundred and fifty-six patients with solitary HCC. Preoperative gadoxetic acid-enhanced MRI findings were retrospectively analyzed. MRI qualitative features such as tumor size, margin, capsule status, signal homogeneity, intratumoral vessels, peritumoral enhancement during mid-arterial phase, peritumoral hypointensity during the hepatobiliary phase (HBP) were investigated. Apparent diffusion coefficients (ADCs), T1 reduction ratio of pre- and post-contrast enhanced images of the tumors were calculated. HCC histological grading in surgical specimens were confirmed by Edmonson’s criteria. Correlations between these MRI features and HCC histological grading were analyzed using multivariate logistic regression. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the model. Results Univariate analysis showed that maximum tumor diameter (p = 0.004), tumor margin (p = 0.006), intratumoral vessels (p = 0.001) and peritumoral hypointensity during HBP (p = 0.000), were significantly correlated with HCC histological grading. There was no relationship between capsule, tumor signal, venous thrombosis, peritumoral enhancement during mid-arterial phase, ADC value, T1 reduction ratio, and HCC histological grading. Multivariate logistic regression analysis demonstrated that the maximum tumor diameter (p = 0.012, odds ratio = 1.002, 95% confidence interval: 1.007–1.046)) was an independent risk factor for high grade HCC. Conclusions Greater tumor size, a more irregular margin, presence of intratumoral vessels, and peritumoral hypointensity during HBP were indicators for high grade HCC. The maximum tumor diameter was an independent risk factor for high grade HCC. Electronic supplementary material The online version of this article (10.1186/s12885-019-5574-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Kun Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.,Department of Radiology, Guizhou Provincial People's Hospital, No. 83 East, Zhongshan Road, Guiyang, 550002, Guizhou, China
| | - Zhi Dong
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Huasong Cai
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Mengqi Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Zhenpeng Peng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Ling Xu
- Faculty of Medicine and Dentistry, University of Western Australia, Perth, Australia
| | - Yingmei Jia
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Chenyu Song
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China
| | - Zi-Ping Li
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
| | - Shi-Ting Feng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China.
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Can IVIM help predict HCC recurrence after hepatectomy? Eur Radiol 2019; 29:5791-5803. [PMID: 30972544 DOI: 10.1007/s00330-019-06180-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/30/2019] [Accepted: 02/08/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE To determine the diagnostic performance of intravoxel incoherent motion (IVIM) parameters to predict tumor recurrence after hepatectomy in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). MATERIALS AND METHODS One hundred and fifty-seven patients (mean age 52.54 ± 11.32 years, 87% male) with surgically and pathologically confirmed HCC were included. Regions of interests were drawn including the tumors by two independent radiologists. ADC and IVIM-derived parameters (true diffusion coefficient [D]; pseudodiffusion coefficient [D*]; pseudodiffusion fraction [f]) were obtained preoperatively. The Cox proportional hazards model was used to analyze the predictors associated with tumor recurrence after hepatectomy. RESULTS Forty-seven of 157 (29.9%) patients experienced tumor recurrence. The multivariate Cox proportional hazards model revealed that a D value < 0.985 × 10-3 mm2/s (hazard ratio (HR), 0.190; p = 0.023) was a risk factor for tumor recurrence. Additional risk factors included younger age (HR, 0.328; p = 0.034) and higher serum alpha-fetoprotein (AFP) level (HR, 2.079; p = 0.013). Further, receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of the obtained Cox regression model improved from 0.68 for the combination of AFP and age alone to 0.724 for the combination of D value, AFP, and age. CONCLUSION The D value derived from the IVIM model is a potential biomarker for the preoperative prediction of recurrence after hepatectomy in patients with HCC. When combined with age and AFP levels, D can improve the predictive performance for tumor recurrence. KEY POINTS • The recurrence rate of HCC after hepatectomy was higher in patients with ADC, D, and f values that were lower than the optimal cutoff values. • The optimal cutoff values of ADC, D, D*, and f for predicting recurrence in HBV associated HCC were 0.858 × 10-3 mm2/s, 0.985 × 10-3 mm2/s, 12.5 × 10-3 mm2/s, and 23.4%, respectively. • The D value derived from IVIM diffusion-weighted imaging may be a useful biomarker for preoperative prediction of recurrence after hepatectomy in patients with HCC. When combined with age and AFP levels, D can improve the predictive performance for tumor recurrence.
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Cao L, Chen J, Duan T, Wang M, Jiang H, Wei Y, Xia C, Zhou X, Yan X, Song B. Diffusion kurtosis imaging (DKI) of hepatocellular carcinoma: correlation with microvascular invasion and histologic grade. Quant Imaging Med Surg 2019; 9:590-602. [PMID: 31143650 PMCID: PMC6511714 DOI: 10.21037/qims.2019.02.14] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND The aim of this study was to prospectively evaluate the diagnostic efficacy of diffusion kurtosis imaging (DKI) in predicting microvascular invasion (MVI) and histologic grade of hepatocellular carcinoma (HCC) with comparison to the conventional diffusion-weighted imaging (DWI). METHODS This prospective study was approved by the Institutional Review Board, and written informed consent was obtained from all patients. From September 2015 to January 2017, 74 consecutive HCC patients were enrolled in this study. Preoperative magnetic resonance imaging including DKI protocol was performed, and patients were followed up for at least one year after surgery. Diffusion parameters including the mean corrected apparent diffusion coefficient (MD), mean apparent kurtosis coefficient (MK), and apparent diffusion coefficient (ADC) were calculated. Differences of diffusion parameters among different histopathological groups were compared. For parameters that were significantly different between pathological groups, receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic efficiency for identifying MVI and predicting high-grade HCC. Univariate and multivariate logistic regression analyses were used to evaluate the relative value of clinical and laboratory variables and diffusion parameters as risk factors for early recurrence (≤1 year). RESULTS Among all the studied diffusion parameters, only MK differed significantly between the MVI-positive and MVI-negative group (0.91±0.10 vs. 0.82±0.09, P<0.001), and showed moderate diagnostic efficacy (AUC =0.77) for identifying MVI. High-grade HCCs showed significantly higher MK values (0.93±0.10 vs. 0.82±0.09, P<0.001), along with MD (1.34±0.18 vs. 1.54±0.22, P<0.001) and ADC values (1.17±0.15 vs. 1.30±0.16, P=0.001) than low-grade HCCs. For differentiating high-grade from low-grade HCCs, MK demonstrated a higher area under the ROC curve (AUC) and significantly higher specificity than MD and ADC (AUC =0.81 vs. 0.76 and 0.74; specificity =82.2% vs. 60.0% and 60.0%, P=0.02). In addition, higher MK (OR =5.700, P=0.002) and Barcelona Clinic Liver Cancer (BCLC) stage C (OR =6.329, P=0.005) were independent risk factors for early HCC recurrence. CONCLUSIONS DKI-derived MK values outperformed conventional ADC values for predicting MVI and histologic grade of HCC, and are associated with increased risk of early tumor recurrence.
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Affiliation(s)
- Likun Cao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jie Chen
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ting Duan
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Min Wang
- Department of Radiology, Inner Mongolia People’s Hospital, Hohhot 010017, China
| | - Hanyu Jiang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yi Wei
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Chunchao Xia
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | | | - Xu Yan
- Siemens Healthcare Ltd., Shanghai 201318, China
| | - Bin Song
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
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Filgueira NA. Hepatocellular carcinoma recurrence after liver transplantation: Risk factors, screening and clinical presentation. World J Hepatol 2019; 11:261-272. [PMID: 30967904 PMCID: PMC6447422 DOI: 10.4254/wjh.v11.i3.261] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 03/06/2019] [Accepted: 03/16/2019] [Indexed: 02/06/2023] Open
Abstract
Liver transplantation is the best treatment option for cirrhotic patients with early-stage hepatocellular carcinoma, but it faces the problem of scarcity of donors and the risk of tumor recurrence, which affects between 15% and 20% of the cases, despite the use of restrictive criteria. The risk of recurrence depends on a number of factors, related to the tumor, the patient, and the treatment, which are discussed in this review. Some of these factors are already well established, such as the histopathological characteristics of the tumor, Alpha-fetoprotein (AFP) levels, and waiting time. Other factors related to the biological behavior of the tumor and treatment should be recognized because they can be used in the refinement of the selection criteria of transplant candidates and in an attempt to reduce recurrence. This review also discusses the clinical presentation of recurrence and its prognosis, contributing to the identification of a subgroup of patients who may have better survival, if they are timely identified and treated. Development of recurrence after the first year, with AFP levels ≤ 100 ng/mL, and single site capable of locoregional therapy are associated with better survival after recurrence.
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Affiliation(s)
- Norma Arteiro Filgueira
- Department of Internal Medicine, Universidade Federal de Pernambuco, Recife, Pernambuco 50670-901, Brazil
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Nitta H, Allard MA, Sebagh M, Karam V, Ciacio O, Pittau G, Vibert E, Sa Cunha A, Cherqui D, Castaing D, Bismuth H, Guettier C, Samuel D, Baba H, Adam R. Predictive model for microvascular invasion of hepatocellular carcinoma among candidates for either hepatic resection or liver transplantation. Surgery 2019; 165:1168-1175. [PMID: 30878140 DOI: 10.1016/j.surg.2019.01.012] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 01/05/2019] [Accepted: 01/21/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Microvascular invasion is the strongest prognostic factor of survival in patients with hepatocellular carcinoma. We therefore developed a predictive model for microvascular invasion of hepatocellular carcinoma to help guide treatment strategies in patients scheduled for either hepatic resection or liver transplantation. METHODS Patients with hepatocellular carcinoma who underwent hepatic resection or liver transplantation from 1994 to 2016 were divided into training and validation cohorts. A predictive model for microvascular invasion was developed based on microvascular invasion risk factors in the training cohort and validated in the validation cohort. RESULTS A total of 910 patients (425 having received hepatic resection, 485 having received liver transplantation) were included in the training (n = 637) and validation (n = 273) cohorts. Multivariate analysis identified α-fetoprotein ≥100 ng/mL (relative risk 3.05, P < .0001), tumor size ≥40 mm (relative risk 1.98, P = .0002), nonboundary hepatocellular carcinoma type (relative risk 1.91, P = .001), neutrophil-to-lymphocyte ratio (relative risk 1.86, P = .002), and aspartate aminotransferase (relative risk 1.53, P = .02) as associated with microvascular invasion. The estimated probability of microvascular invasion ranged from 17.0% in patients with none of these factors to 86.9% in the presence of all factors. This model achieved a C-index of 0.732 in the validation cohort. The 5-year overall survival of patients with ≥50% probability of microvascular invasion was poorer than that of patients with <50% probability (hepatic resection; 39.1% vs 61.2%, P < .0001, liver transplantation; 5-year overall survival, 54.8% vs 79.0%, P = .05). CONCLUSION This model developed from preoperative data allows reliable prediction of microvascular invasion in candidates for either hepatic resection or liver transplantation.
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Affiliation(s)
- Hidetoshi Nitta
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France; Departement of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Japan.
| | - Marc-Antoine Allard
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Mylène Sebagh
- Departement of Pathology, Hôpital Paul Brousse, Assistance Publique-Hôpitaux de Paris, Villejuif, France
| | - Vincent Karam
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Oriana Ciacio
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Gabriella Pittau
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Eric Vibert
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Antonio Sa Cunha
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Daniel Cherqui
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Denis Castaing
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Henri Bismuth
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Catherine Guettier
- Departement of Pathology, Bicêtre University Hospital, Université Paris-Sud, Le Kremlin-Bicêtre, Ile-de-France, France
| | - Didier Samuel
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
| | - Hideo Baba
- Departement of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, Japan
| | - René Adam
- Centre Hépato-Biliaire, AP-HP, Hôpital Paul Brousse, Université Paris-Sud, Inserm U 935 and U 1193, Villejuif, France
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Questionable correlation of the apparent diffusion coefficient with the histological grade and microvascular invasion in small hepatocellular carcinoma. Clin Radiol 2019; 74:406.e19-406.e27. [PMID: 30826002 DOI: 10.1016/j.crad.2019.01.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 01/24/2019] [Indexed: 12/13/2022]
Abstract
AIM To evaluate the correlation between the apparent diffusion coefficient (ADC) and various histopathological parameters in small hepatocellular carcinomas (HCCs). MATERIALS AND METHODS In 143 surgically resected small HCCs, the mean and minimum ADC values, tumour-to-liver ADC ratio, and normalised ADC (ADC of the HCC/ADC of the spleen) were correlated to the tumour grade, microvascular invasion (MVI), cellularity, fatty change, degree of fibrosis, and lymphocytic infiltration using linear regression analysis, the Wilcoxon rank sum test, or Spearman's rank correlation. RESULTS No significant correlation was found between the ADC parameters and tumour grade. In the univariate analysis, the ADC ratio of the tumour was significantly correlated with MVI as well as the degree of fibrosis and lymphocyte infiltration of the HCC (p=0.017, 0.042, and 0.002, respectively). The ADC of the tumour was significantly correlated with the degree of lymphocyte infiltration of the HCC (p=0.049). In the multivariate analysis, the ADC ratio of the tumour was an independent parameter for MVI and the degree of lymphocyte infiltration of the HCC (p=0.034 and <0.001, respectively), and the ADC of the tumour was an independent parameter for the degree of lymphocyte infiltration of the HCC (p=0.009). There was no significant correlation between the other ADCs and pathological tumour parameters. CONCLUSION The tumour grade of small HCCs was not correlated with ADC parameters. The tumour-to-liver ADC ratio was a significant independent parameter for the degree of lymphocyte infiltration and MVI of small HCCs.
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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: 28] [Impact Index Per Article: 5.6] [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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Ahn SJ, Kim JH, Park SJ, Kim ST, Han JK. Hepatocellular carcinoma: preoperative gadoxetic acid-enhanced MR imaging can predict early recurrence after curative resection using image features and texture analysis. Abdom Radiol (NY) 2019; 44:539-548. [PMID: 30229421 DOI: 10.1007/s00261-018-1768-9] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE To investigate whether pre-operative gadoxetic acid-enhanced MRI can predict early recurrence after curative resection of single HCC using image features and texture analysis. MATERIALS AND METHODS 179 patients with single HCC and who underwent pre-operative MRI were included. Two reviewers analyzed MR findings, including the tumor margin, peritumoral enhancement, peritumoral hypointensity on the hepatobiliary phase (HBP), diffusion restriction, capsule, tumoral fat, washout, portal-vein thrombus, signal intensity on HBP, and satellite nodule. Texture analysis on the HBP was also quantified. A multivariate analysis was used to identify predictive factors for early recurrence, microvascular invasion (MVI), and the tumor grade. RESULTS For early recurrence, satellite nodule, peritumoral hypointensity, absence of capsule, and GLCM ASM were predictors (P < 0.05). For MVI, satellite nodule, peritumoral hypointensity, washout, and sphericity were predictors (P < 0.05). Satellite nodules, peritumoral hypointensity, diffusion restriction, and iso to high signal intensity on HBP were predictor for higher tumor grade (P < 0.05). Satellite nodules and peritumoral hypointensity were important showed common predictors for early recurrence, MVI, and grade (P < 0.05). The sensitivity and specificity for satellite nodule were 47.36% and 96.25%. When added texture variables to MRI findings, the diagnostic performance for predicting early recurrence is improved from 0.7 (SD 0.604-0.790) to 0.83 (SD 0.787-0.894). CONCLUSION MR finding, including satellite nodule and peritumoral hypointensity on the HBP, as well as the texture parameters are useful to predict not only early recurrence, but also MVI and higher grade.
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Affiliation(s)
- Su Joa Ahn
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Chongno-gu, Seoul, 110-744, Korea
| | - Jung Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Chongno-gu, Seoul, 110-744, Korea.
- Institute of Radiation Medicine, Seoul National University College of Medicine, Seoul, Korea.
| | - Sang Joon Park
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Chongno-gu, Seoul, 110-744, Korea
| | - Seung Tack Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Chongno-gu, Seoul, 110-744, Korea
| | - Joon Koo Han
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Chongno-gu, Seoul, 110-744, Korea
- Institute of Radiation Medicine, Seoul National University College of Medicine, Seoul, Korea
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43
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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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44
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Rungsakulkij N, Mingphruedhi S, Suragul W, Tangtawee P, Muangkaew P, Aeesoa S. Platelet-to-Lymphocyte Ratio and Large Tumor Size Predict Microvascular Invasion after Resection for Hepatocellular Carcinoma. Asian Pac J Cancer Prev 2018; 19:3435-3441. [PMID: 30583666 PMCID: PMC6428560 DOI: 10.31557/apjcp.2018.19.12.3435] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Background: Recurrence after curative resection of hepatocellular carcinoma (HCC) is associated with early death and poor prognosis. Microvascular invasion (mVI) is strongly associated with disease recurrence. Although many studies have examined the relationship between various serum inflammatory indices and post-treatment prognosis, little is known about preoperative predictors of microvascular invasion in HCC. Methods: Patients who underwent curative hepatic resection for HCC at our institute from January 2006 to December 2016 were retrospectively reviewed. The associations between mVI and various potential risk factors, including tumor size, hepatitis B and C virus infection, Child–Pugh scores, platelet-to-lymphocyte ratio, and neutrophil-to-lymphocyte ratio, were analyzed. Optimal cut-off values were determined using receiver operating characteristic curves. Results: A total of 330 HCC patients were enrolled in this study, of whom 74 (22.4%) had tumors with mVI. After univariate analysis, two parameters were significantly associated with mVI after hepatic resection: platelet-to-lymphocyte ratio ≥102 (odds ratio [OR] 2.385, p = 0.001) and tumor size ≥5 cm (OR 4.29, p < 0.001). Both variables remained significant risk factors for mVI after multivariate analysis: platelet-to-lymphocyte ratio ≥102 (OR 1.831, p = 0.034) and tumor size ≥5 cm (OR 3.791, p < 0.001). Conclusions: Large tumor size (≥5 cm) and high platelet-to-lymphocyte ratio (≥102) are independent predictive factors for mVI in HCC.
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Affiliation(s)
- Narongsak Rungsakulkij
- Department of Surgery, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
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Jeong WK, Jamshidi N, Felker ER, Raman SS, Lu DS. Radiomics and radiogenomics of primary liver cancers. Clin Mol Hepatol 2018; 25:21-29. [PMID: 30441889 PMCID: PMC6435966 DOI: 10.3350/cmh.2018.1007] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 08/16/2018] [Indexed: 02/07/2023] Open
Abstract
Concurrent advancements in imaging and genomic biomarkers have created opportunities to identify non-invasive imaging surrogates of molecular phenotypes. In order to develop such imaging surrogates radiomics and radiogenomics/imaging genomics will be necessary; there has been consistent progress in these fields for primary liver cancers. In this article we evaluate the current status of the field specifically with regards to hepatocellular carcinoma and intrahepatic cholangiocarcinoma, highlighting some of the up and coming results that were presented at the annual Radiological Society of North America Conference in 2017. There are an increasing number of studies in this area with a bias towards quantitative feature measurement, which is expected to benefit reproducibility of the findings and portends well for the future development of biomarkers for diagnosis, prognosis, and treatment response assessment. We review some of the advancements and look forward to some of the exciting future applications that are anticipated as the field develops.
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Affiliation(s)
- Woo Kyoung Jeong
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.,Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.,Department of Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Neema Jamshidi
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ely Richard Felker
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Steven Satish Raman
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David Shinkuo Lu
- Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
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46
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Zhou Y, Wang X, Xu C, Zhou G, Liu X, Gao S, Xu P. Mass-forming intrahepatic cholangiocarcinoma: Can diffusion-weighted imaging predict microvascular invasion? J Magn Reson Imaging 2018; 50:315-324. [PMID: 30444023 DOI: 10.1002/jmri.26566] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 09/16/2018] [Accepted: 09/16/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Microvascular invasion (MVI) is a risk factor influencing the survival rate of patients with mass-forming intrahepatic cholangiocarcinoma (IMCC). PURPOSE To investigate whether diffusion-weighted imaging (DWI) could be useful in predicting MVI of IMCC. STUDY TYPE Retrospective. SUBJECTS Eighty patients with surgically resected single IMCC (21 MVI-positive lesions and 59 MVI-negative lesions). FIELD STRENGTH/SEQUENCE Preoperative hepatic MRI (1.5T), including T1 - and T2 -weighted images (T1 WI, T2 WI), DWI, and dynamic enhancement imaging. ASSESSMENT Morphologic characteristics including contour of the lesion, biliary dilation and hepatic capsule retraction, signal features on T1 WI, T2 WI, and DWI, and dynamic enhancement patterns were qualitatively evaluated. The quantitative analysis was performed for the size and apparent diffusion coefficient (ADC) values. STATISTICAL TESTS Chi-square test, Fisher's exact test, and the independent t-test were used for univariate analysis to determine the relationships between these radiological parameters and the presence of MVI. Logistic regression analysis was used to identify the independent predictors of MVI among these radiological parameters. Receiver operating characteristic curve analysis was performed to evaluate their diagnostic performance. RESULTS Larger tumor size (P = 0.006) and higher ADC values (P < 0.001) were positively correlated with MVI. Multivariate logistic regression analysis demonstrated that the ADC value (odds ratio, 3.099; P = 0.001) was an independent predictor for MVI of IMCC. The ADC value for MVI of IMCC showed an area under the receiver operating characteristic curve of 0.782 (optimal cutoff value was 1.59 × 10-3 mm2 /s). DATA CONCLUSION Larger tumor size was associated with MVI and higher ADC values can be a useful predictor of MVI during the preoperative evaluation of IMCC. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:315-324.
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Affiliation(s)
- Yang Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.,Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China
| | - Xiaolin Wang
- Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China.,Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Chen Xu
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Guofeng Zhou
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.,Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China
| | - Xiaoyu Liu
- Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China
| | - Shanshan Gao
- Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China.,Department of Interventional Radiology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China
| | - Pengju Xu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, P.R. China.,Shanghai Institute of Medical Imaging, Xuhui District, Shanghai, P.R. China
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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: 3.5] [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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Sparchez Z, Mocan T. Contemporary role of liver biopsy in hepatocellular carcinoma. World J Hepatol 2018; 10:452-461. [PMID: 30079131 PMCID: PMC6068845 DOI: 10.4254/wjh.v10.i7.452] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/29/2018] [Accepted: 06/27/2018] [Indexed: 02/06/2023] Open
Abstract
A correct diagnosis of hepatocellular carcinoma (HCC) in cirrhotic patients with focal liver lesions is one of the most important issues nowadays. Probably one of the oldest debates in the hepatology community is whether to perform liver biopsy (LB) in all cirrhotic patients with focal liver lesions. We now face a time when oncology is moving towards personalized medicine. According to the current European Association for the study of Liver diseases HCC guidelines, LB has only a minor role in the management of HCC. However, the current recommendations were made more than five years ago. As time has passed, the development of high-throughput molecular technologies has helped reveal the main molecular mechanism involved in HCC development and progression. Several subtypes of HCC, with both molecular and histological characterization, have been described. Importantly, some of these subtypes have prognostic impact. In the context of personalized treatment, the role of LB will be carefully reconsidered. Until then, it is mandatory to know the various techniques of LB, their performances, complications and limitations. The balance of risk and benefit defines many of the decisions that we make as providers of medical care. In this review, we discuss not only the risks associated with LB, but also the benefits of biopsy in various clinical scenarios. Not long from now, the role of LB will be reconsidered. It is possible that we will go back in time and once again use biopsy for HCC diagnosis. Then again, we may move back to the future to try to improve the use of liquid biopsy in the follow-up of HCC patients after various treatment modalities.
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Affiliation(s)
- Zeno Sparchez
- 3rd Medical Department, Institute for Gastroenterology and Hepatology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca 400162, Romania
| | - Tudor Mocan
- 3rd Medical Department, Institute for Gastroenterology and Hepatology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca 400162, Romania
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49
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Pre-operative ADC predicts early recurrence of HCC after curative resection. Eur Radiol 2018; 29:1003-1012. [DOI: 10.1007/s00330-018-5642-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 06/25/2018] [Accepted: 06/29/2018] [Indexed: 02/08/2023]
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Granata V, Fusco R, Filice S, Catalano O, Piccirillo M, Palaia R, Izzo F, Petrillo A. The current role and future prospectives of functional parameters by diffusion weighted imaging in the assessment of histologic grade of HCC. Infect Agent Cancer 2018; 13:23. [PMID: 29988667 PMCID: PMC6029348 DOI: 10.1186/s13027-018-0194-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 06/22/2018] [Indexed: 12/17/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most common human solid malignancies worldwide. Although the MRI is the technique that is best adapted to characterize HCC, there is not an agreement regarding the study protocol and even what the role of Diffusion-weighted imaging (DWI). The possibility that imaging study can correlate to histologic grade to selecting the therapeutic strategy would be valuable in helping to direct the proper management of HCC. Apparent Diffusion Coefficient (ADC) and IVIM-derived perfusion fraction (fp) and tissue diffusivity (Dt) values of HCC showed significantly better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.
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Affiliation(s)
- Vincenza Granata
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Roberta Fusco
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy.,2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Salvatore Filice
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Orlando Catalano
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Mauro Piccirillo
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Raffaele Palaia
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Francesco Izzo
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Antonella Petrillo
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
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