Validation of a Deep Learning-based Automatic Detection Algorithm for Measurement of Endotracheal Tube-to-Carina Distance on Chest Radiographs.

Journal: Anesthesiology
PMID:

Abstract

BACKGROUND: Improper endotracheal tube (ETT) positioning is frequently observed and potentially hazardous in the intensive care unit. The authors developed a deep learning-based automatic detection algorithm detecting the ETT tip and carina on portable supine chest radiographs to measure the ETT-carina distance. This study investigated the hypothesis that the algorithm might be more accurate than frontline critical care clinicians in ETT tip detection, carina detection, and ETT-carina distance measurement.

Authors

  • Min-Hsin Huang
    Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
  • Chi-Yeh Chen
    Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan; MOST AI Biomedical Research Center, Tainan, Taiwan.
  • Ming-Huwi Horng
    Department of Computer Science and Information Engineering, National Pingtung University, No. 4-18, Min Sheng Road, Pingtung 90003, Taiwan.
  • Chung-I Li
    Department of Statistics, College of Management, National Cheng Kung University, Tainan, Taiwan.
  • I-Lin Hsu
    Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
  • Che-Min Su
    Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
  • Yung-Nien Sun
    Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan.
  • Chao-Han Lai
    Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Biochemistry and Molecular Biology, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.