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Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma

医学 肝细胞癌 放射科 危险系数 队列 无线电技术 神经组阅片室 置信区间 逻辑回归 磁共振成像 比例危险模型 内科学 肿瘤科 神经学 精神科
作者
Yixing Yu,Yanfen Fan,Ximing Wang,Mo Zhu,Mengjie Hu,Cen Shi,Chunhong Hu
出处
期刊:European Radiology [Springer Science+Business Media]
卷期号:32 (2): 959-970 被引量:57
标识
DOI:10.1007/s00330-021-08250-9
摘要

The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for preoperative prediction of VETC and patient prognosis in hepatocellular cancer (HCC).The study included 182 (training cohort: 128; validation cohort: 54) HCC patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Volumes of interest including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase images, from which 1316 radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the useful features. Clinical, intratumoral, peritumoral, combined radiomics, and clinical radiomics models were established using machine learning algorithms. The Kaplan-Meier survival analysis was used to assess early recurrence and progression-free survival (PFS) in the VETC + and VETC- patients.In the validation cohort, the area under the curves (AUCs) of radiomics models were higher than that of the clinical model using random forest (all p < 0.05). The peritumoral radiomics model (AUC = 0.972;95% confidence interval [CI]:0.887-0.998) had significantly higher AUC than intratumoral model (AUC = 0.919; 95% CI: 0.811-0.976) (p = 0.044). There were no significant differences in AUC between intratumoral or peritumoral radiomics model (PR) and combined radiomics model (p > 0.05). Early recurrence and PFS were significantly different between the PR-predicted VETC + and VETC- HCC patients (p < 0.05). PR-predicted VETC was independent predictor of early recurrence (hazard ratio [HR]: 2.08[1.31-3.28]; p = 0.002) and PFS (HR: 1.95[1.20-3.17]; p = 0.007).The intratumoral or peritumoral radiomics model may be useful in predicting VETC and patient prognosis preoperatively. The peritumoral radiomics model may yield an incremental value over intratumoral model.• Radiomics models are useful for predicting vessels encapsulating tumor clusters (VETC) and patient prognosis preoperatively. • Peritumoral radiomics model may yield an incremental value over intratumoral model in prediction of VETC. • Peritumoral radiomics-model-predicted VETC was an independent predictor of early recurrence and progression-free survival.
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