Fig. 1

General workflow. Isotropic spatial resampling was applied on preoperative CT-scan images to segment 160 colorectal liver metastases (CRLM) resected in 122 colorectal cancer (CRC) patients who underwent partial hepatectomy. Matching CRLM, identified by their pathology report block numbers and anatomical description, were included in tissue microarrays for automated quantification of CD73 intra-tumoral expression by immunofluorescence. Radiomic features were extracted from the resulting three-dimensional regions of interest (ROI) (18 first-order statistics, 14 shape features and 75 textural features) and preprocessed. Subsequently, an Attentive Interpretable Tabular Learning (TabNet) model was trained to predict CD73 expression dichotomized as CD73^High vs. CD73^Low based on the surface area expressing CD73 over the total surface of assessable tissue. The model was then evaluated, and its predictions were interpreted using ROC curve and the Shapley Additive Explanations technique (SHAP). The association between radiomic CD73 (rad-CD73) and oncological survival outcomes was analyzed by Kaplan–Meier and logrank test