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Academic radiology · 2025

Multimodal Diffusion MRI Synergized with VI-RADS for Precision Grading of Bladder Urothelial Carcinoma: A Prospective Diagnostic Model Validation.

СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Zhang Xiaoxian, Wang Shaoyu, Wang Mengzhu, Wang Lifeng, Zhang Shouning, Chen Xuejun, Xu Chunmiao

Аннотация

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), neurite orientation dispersion and density imaging (NODDI), and the Vesical Imaging-Reporting and Data System (VI-RADS) in discriminating the pathological grade of bladder urothelial carcinoma (UCB).

MATERIALS AND METHODS: This prospective study enrolled patients with pathologically confirmed UCB between May 2023 and December 2023. Preoperative MRI protocols included spin-echo echo-planner imaging (SE-EPI) and conventional DWI. Quantitative parameters from SE-EPI (DTI, DKI, MAP, NODDI) and apparent diffusion coefficient (ADC) values were measured. Group comparisons between low-grade and high-grade UCB were performed using t-tests or Mann-Whitney U tests. Receiver operating characteristic (ROC) analysis and DeLong's test were used to evaluate diagnostic performance.

RESULTS: A total of 50 patients with UCB (low-grade/ high-grade = 16/34) were included. VI-RADS score and mean kurtosis (MK) derived from DKI emerged as independent predictors for differentiating low-grade and high-grade UCB (area under the curve (AUC): 0.692 and 0.865, respectively). The combination of VI-RADS and DKI-MK achieved superior diagnostic performance (AUC: 0.915, sensitivity: 0.941) compared to VI-RADS alone (AUC: 0.692, sensitivity: 0.471; p < 0.001) or ADC alone (AUC: 0.787, sensitivity: 0.813; p < 0.05).

CONCLUSION: Integrating VI-RADS with DKI-MK significantly enhances preoperative assessment of UCB pathological grading, demonstrating higher accuracy and sensitivity than VI-RADS or ADC alone. This approach improves diagnostic objectivity by combining qualitative imaging criteria with quantitative diffusion metrics, offering potential clinical utility for treatment stratification.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты