ArticleCancer imaging : the official publication of the International Cancer Imaging Society2025
Parameter-driven habitat imaging based on intravoxel incoherent motion MRI for preoperative prediction of muscle invasion in bladder cancer.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2025. 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
backgroundTo develop a parameter-driven habitat imaging based on intravoxel incoherent motion (IVIM) MRI and to validate its effectiveness in preoperatively predicting muscle invasion in bladder cancer (BC).
methodsThis prospective study enrolled 693 pathology-confirmed BC patients who preoperatively underwent multi-b-value diffusion-weighted imaging (DWI). DWI images were acquired using a 3.0 T MRI scanner with 11 b values. Patients were randomly divided into training and testing sets (7:3). K-means clustering was applied to diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps to assign all voxels to distinct intra-tumoral habitats. The voxel proportion (p) and corresponding IVIM values were extracted for each habitat. Features were selected using intraclass correlation coefficient and Pearson correlation analysis. Three random forest models were then constructed: a habitat model, a clinical-radiologic model, and a combined model integrating both. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and Shapley additive explanations (SHAP) was used to interpret feature contributions.
resultsTwo habitats (K = 2) were identified, including a low perfusion and restricted diffusion (LP-RD) habitat with decreased D, D* and f, and a high perfusion and unrestricted diffusion (HP-UD) habitat with increased D, D* and f. The habitat model achieved AUCs of 0.950 and 0.814 in the training and testing sets, respectively. Incorporating clinical-radiologic factors into the combined model improved its performance, reaching AUC values of 0.987 and 0.832. SHAP analysis identified the p and D* values in the HP-UD habitat, and tumor location as the top contributors to the combined model’s predictions.
conclusionsThe parameter-driven habitat imaging based on IVIM MRI offers a promising and noninvasive tool for preoperative assessment of muscle invasion in BC. It may help guide treatment stratification and reduce unnecessary interventions. Future studies will validate these findings in multi-center cohorts and advance integration into clinical workflows.
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