Multi-parametric radiomics of MRI for preoperative assessment of microvascular invasion and prognosis of hepatocellular carcinoma

To preoperatively predict MVI in HCC patients, this study developed and validated an MVI nomogram prediction model that reveals the features derived from tumor and peritumor tissue of different sequences in Gd-EOB-DTPA dynamic contrast-enhanced MR and combines the clinical and radiological signatures. The nomogram included AFP, capsule appearance, arterial peritumoral enhancement, RVI, and radiomics score, which were independent risk factors for MVI. Finally, this nomogram model achieved satisfactory performance in predicting MVI in both the training and validation cohorts. Moreover, the RFS of the nomogram model was similar to the histopathology outcome.