Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence.

Journal: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Published Date: Apr 11, 2022

Abstract

BACKGROUND: Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development.

Authors

  • Shuo Wang
    College of Tea & Food Science, Anhui Agricultural University, Hefei, China.
  • Daksh Chauhan
    University of Chicago, Chicago, IL, United States of America.
  • Hena Patel
    Department of Medicine, University of Chicago, University of Chicago Medical Center, 5758 S. Maryland Avenue, Chicago, IL, MC906760637, USA.
  • Alborz Amir-Khalili
    Circle Cardiovascular Imaging, Calgary, AB, Canada.
  • Isabel Ferreira da Silva
    Circle Cardiovascular Imaging, Calgary, Canada.
  • Alireza Sojoudi
    Circle Cardiovascular Imaging, Calgary, AB, Canada.
  • Silke Friedrich
    Circle Cardiovascular Imaging, Calgary, Canada.
  • Amita Singh
    Department of Medicine, University of Chicago, University of Chicago Medical Center, 5758 S. Maryland Avenue, Chicago, IL, MC906760637, USA.
  • Luis Landeras
    Department of Radiology, University of Chicago, Chicago, IL, USA.
  • Tamari Miller
    Department of Medicine, University of Chicago, University of Chicago Medical Center, 5758 S. Maryland Avenue, Chicago, IL, MC906760637, USA.
  • Keith Ameyaw
    Department of Medicine, University of Chicago, University of Chicago Medical Center, 5758 S. Maryland Avenue, Chicago, IL, MC906760637, USA.
  • Akhil Narang
    Cardiac Imaging Center, University of Chicago Medical Center, Chicago, Illinois.
  • Keigo Kawaji
    Illinois Institute of Technology, Chicago, IL, United States of America.
  • Qiang Tang
    Center of Bioinformatics (COBI), Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
  • Victor Mor-Avi
    Cardiac Imaging Center, University of Chicago Medical Center, Chicago, Illinois.
  • Amit R Patel
    Cardiac Imaging Center, University of Chicago Medical Center, Chicago, Illinois.

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