Contrast-Enhanced CT-Based Deep Learning Radiomics Nomogram for the Survival Prediction in Gallbladder Cancer.

Journal: Academic radiology
Published Date: Dec 6, 2023

Abstract

RATIONALE AND OBJECTIVES: An accurate prognostic model is essential for the development of treatment strategies for gallbladder cancer (GBC). This study proposes an integrated model using clinical features, radiomics, and deep learning based on contrast-enhanced computed tomography (CT) images for survival prediction in patients with GBC after surgical resection.

Authors

  • Fan-Xiu Meng
    Faculty of Graduate Studies, Shanxi Medical University, Taiyuan, 030000, China (F.X.M., W.H.S.); Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China (F.X.M.).
  • Jian-Xin Zhang
    Department of Medical Imaging, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, 030013, China (J.X.Z.).
  • Ya-Rong Guo
    Department of Oncology, First Hospital of Shanxi Medical University, Taiyuan, 030000, China (Y.R.G.).
  • Ling-Jie Wang
    Department of CT Imaging, First Hospital of Shanxi Medical University, Taiyuan, 030000, China (L.J.W.).
  • He-Zhao Zhang
    Department of Hepatopancreatobiliary Surgery, First Hospital of Shanxi Medical University, Taiyuan, 030000, China (J.X., H.Z.Z.).
  • Wen-Hao Shao
    Faculty of Graduate Studies, Shanxi Medical University, Taiyuan, 030000, China (F.X.M., W.H.S.).
  • Jun Xu
    Department of Nephrology, The Affiliated Baiyun Hospital of Guizhou Medical University, Guizhou, China.

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