Radiomics-based AI for predicting and prognosticating VETC in hepatocellular carcinoma: a systematic review and meta-analysis (Preprint)

BACKGROUND Vessels encapsulating tumor clusters (VETC) are a distinct vascular pattern associated with aggressive behavior and poor prognosis in hepatocellular carcinoma (HCC). Preoperative identification of VETC is crucial for treatment planning but currently relies on invasive pathological examination. Radiomics-based artificial intelligence (AI) offers a potential noninvasive solution, yet evidence regarding its diagnostic and prognostic accuracy remains synthesized. OBJECTIVE We aimed to systematically evaluate the diagnostic performance and prognostic value of radiomics-based AI models for noninvasively predicting VETC status in patients with HCC. METHODS We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library for studies published up to July 11, 2025. Studies developing or validating AI models using medical imaging (contrast-enhanced MRI [CEMRI], contrast-enhanced CT [CECT], contrast-enhanced ultrasound [CEUS], or [18F]FDG PET/CT) to predict pathologically confirmed VETC status in HCC patients were included. Study quality was assessed using the PROBAST+AI tool. Diagnostic accuracy (sensitivity, specificity, AUC) and prognostic value for early recurrence (hazard ratio [HR]) were pooled using random-effects models. RESULTS Fourteen studies involving 729 patients in internal and 581 in external validation cohorts were analyzed. AI models based on CEMRI demonstrated the highest diagnostic accuracy, with a pooled AUC of 0.87 (95% CI 0.84-0.90), sensitivity of 0.82 (95% CI 0.75-0.88), and specificity of 0.77 (95% CI 0.71-0.82). Models using other modalities (CECT, PET/CT, CEUS) showed moderate to good performance. Prognostically, HCC patients classified as VETC-positive by AI had a significantly higher risk of early recurrence (pooled HR 2.34, 95% CI 1.93-2.84). CONCLUSIONS Radiomics-based AI models, particularly those using CEMRI, are promising for the noninvasive prediction of VETC and offer valuable prognostic stratification for early recurrence risk in HCC. However, significant heterogeneity and the retrospective nature of current studies limit the strength of evidence. Prospective, multicenter validation is required to confirm clinical utility. CLINICALTRIAL PROSPERO CRD420251167155