ArticleQuantitative imaging in medicine and surgery2026
bp-VI-RADS combined with normalized apparent diffusion coefficient enhances diagnostic efficacy for muscle-invasive bladder cancer.
Article in Quantitative imaging in medicine and surgery, 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
Background: Magnetic resonance imaging (MRI) facilitates the preoperative staging of bladder cancer through the Vesical Imaging-Reporting and Data System (VI-RADS), which employs a 5-point scale to assess the likelihood of muscle invasion. However, the VI-RADS relies on qualitative evaluation, and diagnostic uncertainty arises for patients with a score of 3, for whom muscle invasiveness cannot be determined. Biparametric magnetic resonance imaging (bp-MRI), which incorporates T2-weighted and diffusion-weighted imaging (DWI), has a diagnostic accuracy comparable to that of multiparametric protocols without the need for contrast agents. The apparent diffusion coefficient (ADC) derived from DWI reflects tumor aggressiveness, but is susceptible to technical variability, necessitating the normalization of the ADC to improve reproducibility. This study aimed to evaluate the diagnostic value of the normalized apparent diffusion coefficient (nADC) in bp-MRI for muscle-invasive bladder cancer (MIBC) cases, and to investigate whether integrating nADC with the VI-RADS enhances staging performance, particularly for uncertain lesions with a score of 3. Methods: This study retrospectively enrolled 172 bladder cancer patients who underwent MRI between January 2021 and March 2023. Three radiologists performed VI-RADS scoring on bp-MRI, two of whom manually delineated regions of interest (ROIs) on ADC maps using three-dimensional Slicer software. The mean apparent diffusion coefficient (ADC Results: The AUC for the VI-RADS was 0.87 (cut-off value ≥4, sensitivity 0.69, specificity 0.94). Among the individual parameters, the urine-normalized apparent diffusion coefficient (nADC Conclusions: nADC values (especially the nADC
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