Development and validation of a deep learning-based fully automated algorithm for pre-TAVR CT assessment of the aortic valvular complex and detection of anatomical risk factors: a retrospective, multicentre study.

Journal: EBioMedicine
Published Date: Sep 9, 2023

Abstract

BACKGROUND: Pre-procedural computed tomography (CT) imaging assessment of the aortic valvular complex (AVC) is essential for the success of transcatheter aortic valve replacement (TAVR). However, pre-TAVR assessment is a time-intensive process, and the visual assessment of anatomical structures at the AVC shows interobserver variability. This study aimed to develop and validate a deep learning-based algorithm for pre-TAVR CT assessment and anatomical risk factor detection.

Authors

  • Moyang Wang
    National Center for Cardiovascular Disease, Fuwai Hospital, Beijing, China.
  • Guannan Niu
    National Center for Cardiovascular Disease, Fuwai Hospital, Beijing, China.
  • Yang Chen
    Orthopedics Department of the First Affiliated Hospital of Tsinghua University, Beijing, China.
  • Zheng Zhou
    State Key Laboratory of Genetic Engineering, School of Life Sciences and Shanghai Cancer Hospital/Cancer Institute, Fudan University, Shanghai 200438, China.
  • Dejing Feng
    National Center for Cardiovascular Disease, Fuwai Hospital, Beijing, China.
  • Yuxuan Zhang
    School of Electrical Engineering, Yanshan University, 438 Hebei Avenue, Qinhuangdao 066004, China. Electronic address: 1535937433@qq.com.
  • Yongjian Wu

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