Assessment of muscularis propria invasion in urothelial bladder carcinoma using continuous-time random walk and...

Accurate assessment of muscle layer invasion in bladder cancer is required to distinguish muscle-invasive bladder cancer (MIBC) from non-MIBC (NMIBC). The present prospective study evaluated continuous-time random-walk (CTRW) and stretched-exponential model (SEM) diffusion parameters against conventional apparent diffusion coefficient (ADC) and vesical imaging-reporting and data system (VI-RADS) scores. A total of 106 patients (62 MIBC and 44 NMIBC) who underwent 3.0T multiparametric magnetic resonance imaging, including multi-b-value diffusion-weighted imaging, at The Second Affiliated Hospital of Kunming Medical University (Kunming, China) were analyzed. CTRW and SEM parameters were extracted, and VI-RADS scores were assigned. Significant differences were found between groups for VI-RADS ≥4, SEM-ADC, CTRW-α and CTRW-β (P<0.05). Multivariate logistic regression identified VI-RADS ≥4 and CTRW-β as independent predictors of muscle invasion. While VI-RADS alone achieved an area under the curve (AUC) of 0.85, the combined model incorporating SEM-ADC, CTRW-α and VI-RADS achieved the highest overall performance (AUC=0.91; 95% CI: 0.86-0.96), significantly outperforming VI-RADS alone (raw P=0.002, Bonferroni-corrected P=0.004). Additionally, diffusion kurtosis was positively correlated with invasion depth (r=0.62). These findings indicate that advanced diffusion parameters, particularly CTRW-α and SEM-ADC, effectively differentiate MIBC from NMIBC. When integrated with VI-RADS, they significantly enhance diagnostic accuracy compared with VI-RADS alone (AUC: 0.91 vs. 0.85; P=0.030). Decision curve analysis confirmed clinical utility, with the combined model providing a mean net benefit gain of 0.10 (95% CI: 0.06-0.14) across the clinically relevant threshold range, corresponding with 10 additional correct diagnoses per 100 patients. These quantitative diffusion metrics represent promising non-invasive biomarkers for guiding therapeutic decisions.