MRI radiomics model differentiates small hepatic metastases and abscesses in periampullary cancer patients

Abstract

Abstract This multi-center, retrospective study focused on periampullary cancer patients undergoing MRI for hepatic metastasis and abscess differentiation. T1-weighted, T2-weighted, and arterial phase images were utilized to create radiomics models. In the training-set, 112 lesions in 54 patients (median age [IQR, interquartile range], 73 [63–80]; 38 men) were analyzed, and 123 lesions in 55 patients (72 [66–78]; 34 men) comprised the validation set. The T1-weighted + T2-weighted radiomics model showed the highest AUC (0.82, 95% CI 0.75–0.89) in the validation set. Notably, < 30% T1-T2 size discrepancy in MRI findings predicted metastasis (Ps ≤ 0.037), albeit with AUCs of 0.64–0.68 for hepatic metastasis. The radiomics model enhanced radiologists’ performance (AUCs, 0.85–0.87 vs. 0.80–0.84) and significantly increased diagnostic confidence (P < 0.001). Although the performance increase lacked statistical significance (P = 0.104–0.281), the radiomics model proved valuable in differentiating small hepatic lesions and enhancing diagnostic confidence. This study highlights the potential of MRI-based radiomics in improving accuracy and confidence in the diagnosis of periampullary cancer-related hepatic lesions.

Keywords

• Decision support techniques
• Liver
• Liver abscess
• Neoplasm metastasis
• Magnetic resonance imaging