Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making - Takeaways - MDSpire

Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making

  • By

  • Yanwei Zhang

  • Gang Wu

  • Fengze Sun

  • Bin Wang

  • Yicheng Guo

  • Jitao Wu

  • June 19, 2026

  • 0 min

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  • 1

    Upper tract urothelial carcinoma (UTUC) is a rare but aggressive malignancy, accounting for 5–10% of all urothelial carcinoma cases.

  • 2

    Conventional imaging and biopsy methods have limitations in accurately assessing tumor grade and invasiveness in UTUC.

  • 3

    Radiomics and deep learning models have shown promise in predicting pathological grade and assessing muscle invasion in UTUC.

  • 4

    Most studies on radiomics and deep learning in UTUC are retrospective, single-center, and limited by small sample sizes.

  • 5

    Future research should focus on standardization, external validation, and demonstrating clinical utility of radiomics and deep learning in UTUC.

Original Source(s)

Radiomics and deep learning in upper tract urothelial carcinoma: advancing preoperative risk stratification and clinical decision-making

  • by Yanwei Zhang, Gang Wu, Fengze Sun, Bin Wang, Yicheng Guo, Jitao Wu

  • June 19, 2026

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