Deep Learning Predicts Lymphovascular Invasion Status in Muscle Invasive Bladder Cancer Histopathology.

Journal: Annals of surgical oncology
PMID: 39472420

Abstract

BACKGROUND: Lymphovascular invasion (LVI) is linked to poor prognosis in patients with muscle-invasive bladder cancer (MIBC). Accurately identifying the LVI status in MIBC patients is crucial for effective risk stratification and precision treatment. We aim to develop a deep learning model to identify the LVI status in whole-slide images (WSIs) of MIBC patients.

Authors

  • Panpan Jiao
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.
  • Shaolin Wu
    Department of Nephrology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang, China.
  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Xinmiao Ni
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Jiejun Wu
    Department of Urology, Renmin Hospital of Wuhan University, 99 Zhang Zhi-Dong Road, Wuhan, 430060, Hubei, People's Republic of China.
  • Kai Wang
    Department of Rheumatology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
  • Xiuheng Liu
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Zhiyuan Chen
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
  • Qingyuan Zheng
    Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

Keywords

External Resources

Popular Topics
Recent Journals