Deep Learning-Based Algorithm for the Detection and Characterization of MRI Safety of Cardiac Implantable Electronic Devices on Chest Radiographs.

Journal: Korean journal of radiology
PMID: 34431249

Abstract

OBJECTIVE: With the recent development of various MRI-conditional cardiac implantable electronic devices (CIEDs), the accurate identification and characterization of CIEDs have become critical when performing MRI in patients with CIEDs. We aimed to develop and evaluate a deep learning-based algorithm (DLA) that performs the detection and characterization of parameters, including MRI safety, of CIEDs on chest radiograph (CR) in a single step and compare its performance with other related algorithms that were recently developed.

Authors

  • Ue-Hwan Kim
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
  • Moon Young Kim
    Department of Radiology, SMG-SNU Boramae Medical Center, Seoul, Korea.
  • Eun-Ah Park
    Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Whal Lee
    Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea.
  • Woo-Hyun Lim
    Division of Cardiology, Department of Internal Medicine, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea.
  • Hack-Lyoung Kim
    Department of Internal Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, South Korea (H.-L.K.).
  • Sohee Oh
    Department of Biostatistics, Seoul National University College of Medicine and SMG-SNU Boramae Medical Center, Seoul, Korea.
  • Kwang Nam Jin
    Department of Radiology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, South Korea.

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