Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics

Background Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. Methods Patients with a single HCC of 2–5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop ( n = 230) and test ( n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR ( n = 118) and NAR ( n = 85) via propensity score matching using patient data from another 2 centers for external validation. Results The CRR model showed higher area under the curve values (0.835–0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796–0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group ( P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group ( P = 0.31). Conclusions The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.