A Novel Deep Learning-based Pathomics Score for Prognostic Stratification in Pancreatic Ductal Adenocarcinoma.

Journal: Pancreas
PMID: 40314741

Abstract

BACKGROUND AND OBJECTIVES: Accurate survival prediction for pancreatic ductal adenocarcinoma (PDAC) is crucial for personalized treatment strategies. This study aims to construct a novel pathomics indicator using hematoxylin and eosin-stained whole slide images and deep learning to enhance PDAC prognosis prediction.

Authors

  • Wenbin Liu
    Department of Radiology, Changhai Hospital.
  • Jing Li
    Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
  • Xiaohan Yuan
    Department of Radiology, Changhai Hospital.
  • Chengwei Chen
    Department of Radiology, Changhai Hospital.
  • Yixuan Shen
    Department of Radiology, Changhai Hospital.
  • Xinyue Zhang
    Department of Radiology, Changhai Hospital.
  • Jieyu Yu
    Department of Radiology, Changhai Hospital.
  • Mengmeng Zhu
    Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming, Yunnan, China.
  • Xu Fang
    Department of Radiology, Changhai Hospital.
  • Fang Liu
    The First Clinical Medical College of Gannan Medical University, Ganzhou 341000, Jiangxi Province, China.
  • Tiegong Wang
    Department of Radiology, Changhai Hospital.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Jie Fan
    Department of Pathology, Huashan Hospital.
  • Hui Jiang
    Queensland Alliance for Environmental Health Science (QAEHS), University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4012, Australia.
  • Jianping Lu
    Department of Radiology, Changhai Hospital.
  • Chengwei Shao
    Department of Radiology, Changhai Hospital.
  • Yun Bian
    Department of Radiology, Changhai Hospital.

Keywords

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