Radiomics of Preoperative Multi-Sequence Magnetic Resonance Imaging Can Improve the Predictive Performance of Microvascular Invasion in Hepatocellular Carcinoma

被引:3
作者
Liu, Wan Min [1 ]
Zhao, Xing Yu [1 ]
Gu, Meng Ting [1 ]
Song, Kai Rong [2 ]
Zheng, Wei [2 ]
Yu, Hui [2 ]
Chen, Hui Lin [3 ]
Xu, Xiao Wen [1 ]
Zhou, Xiang [1 ]
Liu, Ai E. [4 ]
Jia, Ning Yang [2 ]
Wang, Pei Jun [1 ]
机构
[1] Tongji Univ, Tongji Hosp, Sch Med, Dept Radiol, Shanghai, Peoples R China
[2] Shanghai Naval Mil Med Univ, Eastern Hepatobiliary Surg Hosp, Affiliated Hosp 3, Dept Radiol, Shanghai, Peoples R China
[3] Univ Shanghai Sci & Technol, Sch Hlth Sci & Engn, Shanghai, Peoples R China
[4] Shanghai United Imaging Intelligence Co Ltd, Dept Res Ctr, Shanghai, Peoples R China
关键词
Radiomics; Magnetic resonance imaging; Microvascular invasion; Hepatocellular carcinoma; Predictive performance; ENHANCED MRI; DIAGNOSIS; RESECTION; NOMOGRAM; IMPACT; RISK;
D O I
10.14740/wjon1731
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: The aim of the study is to demonstrate that radiomics of preoperative multi-sequence magnetic resonance imaging (MRI) can indeed improve the predictive performance of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: A total of 206 patients with pathologically confirmed HCC who underwent preoperative enhanced MRI were retrospectively recruited. Univariate and multivariate logistic regression analysis identified the independent clinicoradiologic predictors of MVI present and constituted the clinicoradiologic model. Recursive feature elimination (RFE) was applied to select radiomics features (extracted from six sequence images) and constructed the radiomics model. Clinicoradiologic model plus radiomics model formed the clinicoradiomics model. Five-fold cross-validation was used to validate the three models. Discrimination, calibration, and clinical utility were used to evaluate the performance. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were used to compare the prediction accuracy between models. Results: The clinicoradiologic model contained alpha-fetoprotein (AFP)_lg10, radiological capsule enhancement, enhancement pattern and arterial peritumoral enhancement, which were independent risk factors of MVI. There were 18 radiomics features related to MVI constructed the radiomics model. The mean area under the receiver operating curve (AUC) of clinicoradiologic, radiomics and clinicoradiomics model were 0.849, 0.925 and 0.950 in the training cohort and 0.846, 0.907 and 0.933 in the validation cohort, respectively. The three models' calibration curves fitted well, and decision curve analysis (DCA) confirmed the clinical usefulness. Compared with the clinicoradiologic model, the NRI of radiomics and clinicoradiomics model increased significantly by 0.575 and 0.825, respectively, and the IDI increased significantly by 0.280 and 0.398, respectively. Conclusions: Radiomics of preoperative multi-sequence MRI can improve the predictive performance of MVI in HCC.
引用
收藏
页码:58 / 71
页数:14
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