ArticleAbdominal radiology (New York)2026
Prognostic prediction model for rectal cancer based on CMS subtype indicators and SHAP-based interpretable analysis.
Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesTo develop an interpretable radiomics model for predicting 3-year progression-free survival (PFS) in rectal cancer (RC) by integrating consensus molecular subtype (CMS) indicators and Shapley additive explanations (SHAP) analysis with ultra-high b-value diffusion-weighted imaging (DWI).
methodsThis retrospective study included 153 RC patients randomly assigned to training (n = 107) and validation (n = 46) cohorts. All patients underwent 3.0T DWI with b-values of 0, 1500, 2000, and 3000 s/mm
resultsIn the validation cohort, radscore2 (area under the curve (AUC) = 0.787) outperformed radscore1 (AUC = 0.751) in predicting 3-year PFS. Model 5 (clinical + radscore2) achieved the highest AUC (0.823) with good calibration. NRI analysis showed significant improvement for model 5 compared with the clinical model (NRI = 0.540, p = 0.001). SHAP analysis identified α_logarithm_ngtdm_Contrast (0.463) and α_gradient_firstorder_TotalEnergy (0.445) as the most important features.
conclusionThe integration of CMS-surrogate guided feature selection and SHAP analysis could construct an interpretable radiomics model with good performance in predicting 3-year PFS in rectal cancer.
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