Artificial intelligence-assisted echocardiographic monitoring in pediatric patients on extracorporeal membrane oxygenation.

Journal: Frontiers in cardiovascular medicine
Published Date: Dec 11, 2024

Abstract

BACKGROUND: Percutaneous extracorporeal membrane oxygenation (ECMO) is administered to pediatric patients with cardiogenic shock or cardiac arrest. The traditional method uses focal echocardiography to complete the left ventricular measurement. However, echocardiographic determination of the ejection fraction (EF) by manual tracing of the endocardial borders is time consuming and operator dependent. The standard visual assessment is also an inherently subjective procedure. Artificial intelligence (AI) based machine learning-enabled image analysis might provide rapid, reproducible measurements of left ventricular volumes and EF for ECMO patients.

Authors

  • Weiling Chen
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.
  • Jinhui Wu
    School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
  • Zhenxuan Zhang
    School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
  • Zhifan Gao
    School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
  • Xunyi Chen
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.
  • Yu Zhang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Zhou Lin
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.
  • Zijian Tang
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.
  • Wei Yu
    Quality Control Department, Jiangxi Provincial Blood Center Nanchang 330052, Jiangxi, China.
  • Shumin Fan
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.
  • Heye Zhang
    School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.
  • Bei Xia
    Department of Ultrasonography, Shenzhen Children's Hospital, Shenzhen, China.

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