CT-based multimodal radiogenomic model integrating tumor and perirenal fat features for prognosis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), the most common renal cell carcinoma subtype (60%-85%), remains challenging due to suboptimal TNM-based risk stratification and limited precision in adjuvant targeted therapy (5.4%-10.5% survival benefit with overtreatment risk). Perirenal fat, linked to ccRCC prognosis via volume and density, is underexplored in integration with radiogenomics (tumor molecular features) for comprehensive prognosis. Retrospective analysis included a training cohort (Xijing Hospital, n = 226) and testing cohort (TCIA/TCGA, n = 134) of resectable ccRCC patients with preoperative contrast-enhanced CT and exome sequencing data. CT-based tumor/perirenal fat radiomic features were extracted via 3D Slicer/PyRadiomics, with scores built using LASSO and stepwise Cox regression. Genetic scores derived from 639 cancer-related genes (top 20 mutated genes) and clinical scores (e.g., TNM stage) were constructed via Cox regression. A multimodal nomogram integrating these scores was validated using C-index, time-dependent AUC, and SHAP analysis. The nomogram outperformed unimodal scores, with C-indices of 0.856 (training) and 0.859 (testing). Time-dependent AUCs for 1-5-year PFS were consistently higher. SHAP identified tumor/perirenal fat scores, TP53 mutation, and grade G4 as key contributors.Multiple machine learning algorithms were used to predict four genes with prognostic value, and their correlations in multimodal data were analyzed. Subgroup analyses confirmed robust risk stratification. Patients with targeted therapy risk difference rate ≥ 47% had longer PFS with therapy (HR = 0.545, p = 0.038), while those with < 10% fared better without therapy (HR = 2.051, p = 0.035), with similar trends in high-risk subgroups. Targeted therapy-related analyses are exploratory and require prospective validation. This CT-based multimodal nomogram integrates radiomic, genomic, and clinical data to characterize ccRCC across scales, providing auxiliary reference for screening patients who may gain potential survival benefit from adjuvant targeted therapy, reducing overtreatment/undertreatment.