Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy.

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Abstrakt

Tytuł:: Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy.
Autorzy:: Zhao Y; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Wu J; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Zhang Q; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Hua Z; Department of Pathology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Qi W; Department of Pathology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Wang N; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Lin T; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Sheng L; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Cui D; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Liu J; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Song Q; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Li X; GE Healthcare (China), Shanghai, China.
Wu T; GE Healthcare (China), Shanghai, China.
Guo Y; GE Healthcare (China), Shanghai, China.
Cui J; Huiying Medical Technology Inc, Beijing, China.
Liu A; Department of Radiology, The First Affiliated Hospital, Dalian Medical University, Dalian, China.
Źródło:: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2021 Apr; Vol. 53 (4), pp. 1066-1079. Date of Electronic Publication: 2020 Nov 20.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Publication: <2005-> : Hoboken , N.J. : Wiley-Liss
Original Publication: Chicago, IL : Society for Magnetic Resonance Imaging, c1991-
MeSH Terms:: Carcinoma, Hepatocellular*/diagnostic imaging
Carcinoma, Hepatocellular*/surgery
Liver Neoplasms*/diagnostic imaging
Liver Neoplasms*/surgery
Multiparametric Magnetic Resonance Imaging*
Hepatectomy ; Humans ; Magnetic Resonance Imaging ; Retrospective Studies
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Contributed Indexing:: Keywords: hepatectomy; hepatocellular carcinoma; magnetic resonance imaging; radiomics; recurrence
Entry Date(s):: Date Created: 20201120 Date Completed: 20210514 Latest Revision: 20210514
Update Code:: 20240105
DOI:: 10.1002/jmri.27424
PMID:: 33217114
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Background: Preoperative prediction of early recurrence (ER) of hepatocellular carcinoma (HCC) plays a critical role in individualized risk stratification and further treatment guidance.
Purpose: To investigate the role of radiomics analysis based on multiparametric MRI (mpMRI) for predicting ER in HCC after partial hepatectomy.
Study Type: Retrospective.
Population: In all, 113 HCC patients (ER, n = 58 vs. non-ER, n = 55), divided into training (n = 78) and validation (n = 35) cohorts.
Field Strength/sequence: 1.5T or 3.0T, gradient-recalled-echo in-phase T 1 -weighted imaging (I-T 1 WI) and opposed-phase T 1 WI (O-T 1 WI), fast spin-echo T 2 -weighted imaging (T 2 WI), spin-echo planar diffusion-weighted imaging (DWI), and gradient-recalled-echo contrast-enhanced MRI (CE-MRI).
Assessment: In all, 1146 radiomics features were extracted from each image sequence, and radiomics models based on each sequence and their combination were established via multivariate logistic regression analysis. The clinicopathologic-radiologic (CPR) model and the combined model integrating the radiomics score with the CPR risk factors were constructed. A nomogram based on the combined model was established.
Statistical Tests: Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of each model. The potential clinical usefulness was evaluated by decision curve analysis (DCA).
Results: The radiomics model based on I-T 1 WI, O-T 1 WI, T 2 WI, and CE-MRI sequences presented the best performance among all radiomics models with an area under the ROC curve (AUC) of 0.771 (95% confidence interval (CI): 0.598-0.894) in the validation cohort. The combined nomogram (AUC: 0.873; 95% CI: 0.756-0.989) outperformed the radiomics model and the CPR model (AUC: 0.742; 95% CI: 0.577-0.907). DCA demonstrated that the combined nomogram was clinically useful.
Data Conclusion: The mpMRI-based radiomics analysis has potential to predict ER of HCC patients after hepatectomy, which could enhance risk stratification and provide support for individualized treatment planning.
Evidence Level: 4.
Technical Efficacy: Stage 4.
(© 2020 International Society for Magnetic Resonance in Medicine.)

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