Literature DB >> 31675174

MRI-Based Radiomics: Associations With the Recurrence-Free Survival of Patients With Hepatocellular Carcinoma Treated With Conventional Transcatheter Arterial Chemoembolization.

Wenlong Song1, Xiangling Yu1, Dajing Guo1, Huan Liu2, Zhuoyue Tang3, Xinjie Liu1, Jun Zhou1, Haiping Zhang1, Yangyang Liu1, Xi Liu1.   

Abstract

BACKGROUND: Preoperative estimation of hepatocellular carcinoma (HCC) recurrence after conventional transcatheter arterial chemoembolization (c-TACE) is crucial for subsequent follow-up and therapy decisions.
PURPOSE: To evaluate the associations of radiomics models based on pretreatment contrast-enhanced MRI, a clinical-radiological model and a combined model with the recurrence-free survival (RFS) of patients with HCC after c-TACE, and to develop a radiomics nomogram for individual RFS estimations and risk stratification. STUDY TYPE: Retrospective. POPULATION: In all, 184 consecutive HCC patients. FIELD STRENGTH/SEQUENCE: 1.5T or 3.0T, including T2 WI, T1 WI, and contrast-enhanced T1 WI. ASSESSMENT: All HCC patients were randomly divided into the training (n = 110) and validation datasets (n = 74). Radiomics signatures capturing intratumoral and peritumoral expansion (1, 3, and 5 mm) were constructed, and the radiomics models were set up using least absolute shrinkage and selection operator (LASSO) Cox regression. Clinical-radiological features were identified by univariate and multivariate Cox regression. The clinical-radiological model and the combined model fusing the radiomics signature with the clinical-radiological risk factors were developed by a multivariate Cox proportional hazard model. A radiomics nomogram derived from the combined model was established. STATISTICAL TESTS: LASSO Cox regression, univariate and multivariate Cox regression, Kaplan-Meier analysis were performed. The discrimination performance of each model was quantified by the C-index.
RESULTS: Among the different peritumoral expansion models, only the 3-mm peritumoral expansion model (C-index, 0.714) showed a comparable performance (P = 0.4087) to that of the portal venous phase intratumoral model (C-index, 0.727). The combined model showed the best performance and the C-index was 0.802. Kaplan-Meier analysis showed that the cutoff values of the combined model relative to a median value (1.7426) perfectly stratified these patients into high-risk and low-risk subgroups. DATA
CONCLUSION: The combined model is more valuable than the clinical-radiological model or radiomics model alone for evaluating the RFS of HCC patients after c-TACE, and the radiomics nomogram can be used to preoperatively and individually estimate RFS. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;52:461-473.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  hepatocellular carcinoma; radiomics nomogram; recurrence-free survival; transcatheter arterial chemoembolization

Mesh:

Year:  2019        PMID: 31675174     DOI: 10.1002/jmri.26977

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  16 in total

Review 1.  Radiomics of hepatocellular carcinoma: promising roles in patient selection, prediction, and assessment of treatment response.

Authors:  Amir A Borhani; Roberta Catania; Yuri S Velichko; Stefanie Hectors; Bachir Taouli; Sara Lewis
Journal:  Abdom Radiol (NY)       Date:  2021-04-23

2.  Contrast-enhanced ultrasound-based ultrasomics score: a potential biomarker for predicting early recurrence of hepatocellular carcinoma after resection or ablation.

Authors:  Hui Huang; Si-Min Ruan; Meng-Fei Xian; Ming-de Li; Mei-Qing Cheng; Wei Li; Yang Huang; Xiao-Yan Xie; Ming-de Lu; Ming Kuang; Wei Wang; Hang-Tong Hu; Li-Da Chen
Journal:  Br J Radiol       Date:  2021-11-29       Impact factor: 3.039

3.  Preoperative estimation of the survival of patients with unresectable hepatocellular carcinoma achieving complete response after conventional transcatheter arterial chemoembolization: assessments of clinical and LI-RADS MR features.

Authors:  Wenlong Song; Qianyu Chen; Dajing Guo; Caiming Jiang
Journal:  Radiol Med       Date:  2022-08-26       Impact factor: 6.313

4.  Multi-Sequence MR-Based Radiomics Signature for Predicting Early Recurrence in Solitary Hepatocellular Carcinoma ≤5 cm.

Authors:  Leyao Wang; Xiaohong Ma; Bing Feng; Shuang Wang; Meng Liang; Dengfeng Li; Sicong Wang; Xinming Zhao
Journal:  Front Oncol       Date:  2022-06-08       Impact factor: 5.738

5.  Radiomics Analysis Based on Contrast-Enhanced MRI for Prediction of Therapeutic Response to Transarterial Chemoembolization in Hepatocellular Carcinoma.

Authors:  Ying Zhao; Nan Wang; Jingjun Wu; Qinhe Zhang; Tao Lin; Yu Yao; Zhebin Chen; Man Wang; Liuji Sheng; Jinghong Liu; Qingwei Song; Feng Wang; Xiangbo An; Yan Guo; Xin Li; Tingfan Wu; Ai Lian Liu
Journal:  Front Oncol       Date:  2021-03-31       Impact factor: 6.244

Review 6.  Progress of MRI Radiomics in Hepatocellular Carcinoma.

Authors:  Xue-Qin Gong; Yun-Yun Tao; Yao-Kun Wu; Ning Liu; Xi Yu; Ran Wang; Jing Zheng; Nian Liu; Xiao-Hua Huang; Jing-Dong Li; Gang Yang; Xiao-Qin Wei; Lin Yang; Xiao-Ming Zhang
Journal:  Front Oncol       Date:  2021-09-20       Impact factor: 6.244

7.  Prediction of Hepatocellular Carcinoma Response to Transcatheter Arterial Chemoembolization: A Real-World Study Based on Non-Contrast Computed Tomography Radiomics and General Image Features.

Authors:  Zheng Guo; Nanying Zhong; Xueming Xu; Yu Zhang; Xiaoning Luo; Huabin Zhu; Xiufang Zhang; Di Wu; Yingwei Qiu; Fuping Tu
Journal:  J Hepatocell Carcinoma       Date:  2021-07-09

8.  Peritumoral Dilation Radiomics of Gadoxetate Disodium-Enhanced MRI Excellently Predicts Early Recurrence of Hepatocellular Carcinoma without Macrovascular Invasion After Hepatectomy.

Authors:  Huanhuan Chong; Yuda Gong; Xianpan Pan; Aie Liu; Lei Chen; Chun Yang; Mengsu Zeng
Journal:  J Hepatocell Carcinoma       Date:  2021-06-09

9.  Hepatocellular Carcinoma Drug-Eluting Bead Transarterial Chemoembolization (DEB-TACE): Outcome Analysis Using a Model Based On Pre-Treatment CT Texture Features.

Authors:  Marcello Andrea Tipaldi; Edoardo Ronconi; Elena Lucertini; Miltiadis Krokidis; Marta Zerunian; Tiziano Polidori; Paola Begini; Massimo Marignani; Federica Mazzuca; Damiano Caruso; Michele Rossi; Andrea Laghi
Journal:  Diagnostics (Basel)       Date:  2021-05-26

Review 10.  The application of texture quantification in hepatocellular carcinoma using CT and MRI: a review of perspectives and challenges.

Authors:  Ismail Bilal Masokano; Wenguang Liu; Simin Xie; Dama Faniriantsoa Henrio Marcellin; Yigang Pei; Wenzheng Li
Journal:  Cancer Imaging       Date:  2020-09-22       Impact factor: 3.909

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