Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

Journal: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
PMID: 39127260

Abstract

BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data introduces variability and limits the reproducibility of aortic hemodynamics visualization and quantitative flow-related parameter computation. This paper explores the potential of deep learning to improve 4D flow CMR segmentation by developing models for automatic segmentation and analyzes the impact of the training data on the generalization of the model across different sites, scanner vendors, sequences, and pathologies.

Authors

  • Chiara Manini
    Deutsches Herzzentrum der Charité (DHZC), Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany. Electronic address: chiara.manini@dhzc-charite.de.
  • Markus Hullebrand
  • Lars Walczak
    Deutsches Herzzentrum der Charité (DHZC), Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany; Fraunhofer MEVIS, Berlin, Germany.
  • Sarah Nordmeyer
    Department of Diagnostic and Interventional Radiology, Tübingen University Hospital, Tübingen, Germany.
  • Lina Jarmatz
    Deutsches Herzzentrum der Charité (DHZC), Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany.
  • Titus Kuehne
    Institute of Imaging Science and Computational Modelling, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • Heiko Stern
    Congenital Heart Disease and Pediatric Cardiology, German Heart Center Munich, Munich, Germany.
  • Christian Meierhofer
    Congenital Heart Disease and Pediatric Cardiology, German Heart Center Munich, Munich, Germany.
  • Andreas Harloff
    Department of Neurology and Neurophysiology, University Medical Center Freiburg - Faculty of Medicine, University of Freiburg, Freiburg, Germany.
  • Jennifer Erley
    German Center for Cardiovascular Research (DZHK), Berlin, Germany; Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany.
  • Sebastian Kelle
    Department of Internal Medicine/Cardiology German Heart Center, Berlin, Germany.
  • Peter Bannas
    Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Ralf Felix Trauzeddel
    German Center for Cardiovascular Research (DZHK), Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125 Berlin, Germany; Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité - Universitätsmedizin Berlin and the Max-Delbrück-Center for Molecular Medicine, Berlin, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Anesthesiology and Intensive Care Medicine, Charité Campus Benjamin Franklin, Hindenburgdamm 30, 12203 Berlin, Germany.
  • Jeanette Schulz-Menger
    Charité-Universitätsmedizin Berlin, Experimental and Clinical Research Center, Working Group On CMR and HELIOS Klinikum Berlin Buch, Cardiology Berlin, DZHK partnersite Berlin, Berlin, Germany.
  • Anja Hennemuth
    Charité - Universitätsmedizin Berlin, Berlin, Germany; Fraunhofer MEVIS, Bremen, Germany; German Centre for Cardiovascular Research, Berlin, Germany.

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