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DOI 10.1007/s00261-025-05023-6

Медицинская библиотека · Abdominal radiology (New York) · 2025

Recurrence risk prediction for non-muscle-invasive bladder urothelial carcinoma using diffusion and clinicopathology features.

Zhang Xiaoxian, Guo Jinxia, Wang Lifeng, Ma Yuedi, Kang Liuqing, Yang Dong, Chen Xuejun, Xu Chunmiao

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Аннотация

PURPOSE: To investigate the prognostic value of apparent diffusion coefficient (ADC) metrics, MRI characteristics, and clinicopathological parameters in predicting non-muscle-invasive bladder urothelial carcinoma (UCB) recurrence, and to develop a novel multiparametric risk stratification framework.

METHODS

This retrospective single-center study (n = 135) with histologically confirmed non-muscle-invasive UCB diagnosed between January 2015 and March 2023. ADC values, vesical imaging reporting and data system (VI-RADS) scores, and clinicopathological variables were analyzed with recurrence-free survival (RFS) as the primary endpoint. Prognostic determinants were identified using univariate and multivariate Cox proportional hazard regression models. An advanced risk stratification system was developed using independent predictors and validated against the European Association of Urology (EAU) risk classification using concordance index (C-index).

RESULTS

Multivariate analysis identified three independent predictors: ADC values (HR = 0.104, 95% confidence interval (CI) 0.025-0.436), hemoglobin levels (HR = 0.463, 95% CI 0.223-0.960), and pathological grade (HR = 2.079, 95% CI 1.098-3.936). The combined model incorporating these parameters demonstrated moderate predictive accuracy (C-index = 0.724, 95% CI 0.655-0.794). Notably, VI-RADS scores showed no independent prognostic value. Risk stratification based on ADC (≤ 1343.22 × 10⁻⁶ mm²/s), hemoglobin (< 113.2 g/L), and pathological grade demonstrated superior discriminative capacity compared to EAU criteria (C-index: 0.667 vs. 0.605).

CONCLUSION

A multidimensional prognostic framework integrating quantitative ADC metrics, hemoglobin levels, and pathological grading significantly outperforms conventional EAU stratification in predicting non-muscle-invasive UCB recurrence, providing clinically actionable thresholds for personalized risk stratification and UCB management.

Для цитирования: Zhang Xiaoxian, Guo Jinxia, Wang Lifeng, Ma Yuedi, Kang Liuqing, Yang Dong, Chen Xuejun, Xu Chunmiao. Recurrence risk prediction for non-muscle-invasive bladder urothelial carcinoma using diffusion and clinicopathology features.. Abdominal radiology (New York). 2025. DOI: 10.1007/s00261-025-05023-6.

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