列线图
无线电技术
医学
放射科
肝细胞癌
队列
临床试验
肿瘤科
核医学
内科学
作者
Yutao Wang,Shuying Luo,Gehui Jin,Randi Fu,Zhongfei Yu,Jian Zhang
标识
DOI:10.1186/s12880-022-00796-4
摘要
To develop a clinical-radiomics nomogram by incorporating radiomics score and clinical predictors for preoperative prediction of microvascular invasion in hepatocellular carcinoma.A total of 97 HCC patients were retrospectively enrolled from Shanghai Universal Medical Imaging Diagnostic Center and Changhai Hospital Affiliated to the Second Military Medical University. 909 CT and 909 PET slicers from 97 HCC patients were divided into a training cohort (N = 637) and a validation cohort (N = 272). Radiomics features were extracted from each CT or PET slicer, and features selection was performed with least absolute shrinkage and selection operator regression and radiomics score was also generated. The clinical-radiomics nomogram was established by integrating radiomics score and clinical predictors, and the performance of the models were evaluated from its discrimination ability, calibration ability, and clinical usefulness.The radiomics score consisted of 45 selected features, and age, the ratio of maximum to minimum tumor diameter, and [Formula: see text]F-FDG uptake status were independent predictors of microvascular invasion. The clinical-radiomics nomogram showed better performance for MVI detection (0.890 [0.854, 0.927]) than the clinical nomogram (0.849 [0.804, 0.893]) ([Formula: see text]). Both nomograms showed good calibration and the clinical-radiomics nomogram's clinical practicability outperformed the clinical nomogram.With the combination of radiomics score and clinical predictors, the clinical-radiomics nomogram can significantly improve the predictive efficacy of microvascular invasion in hepatocellular carcinoma ([Formula: see text]) compared with clinical nomogram.
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