Deep learning-based lymph node metastasis status predicts prognosis from muscle-invasive bladder cancer histopathology.

Journal: World journal of urology
PMID: 39792275

Abstract

PURPOSE: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients.

Authors

  • Qingyuan Zheng
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Panpan Jiao
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.
  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Junjie Fan
  • Yunxun Liu
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
  • Xiangxiang Yang
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-dong Road, Wuhan, Hubei, 430060, P.R. China.
  • Jingping Yuan
    Department of Pathology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Zhiyuan Chen
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Xiuheng Liu
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

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