Comparison of synthetic LGE with optimal inversion time vs. conventional LGE via representation learning: Quantification of Bias in Population Analysis.

Journal: Computers in biology and medicine
Published Date: Jul 16, 2025

Abstract

PURPOSE: Late Gadolinium Enhancement (LGE) images are crucial elements of CMR protocols for evaluating myocardial infarct (MI) severity and size. However, these images rely on signal intensity changes and manual inversion time (TI) settings, leading to suboptimal lesion/remote contrast in many cases. Here, we propose an original approach to evaluate the impact of suboptimal TI on the retrospective analysis of ST-elevation MI (STEMI) patients, using a representation learning methodology tailored to consider infarct- and image-based characteristics across the studied population.

Authors

  • Romain Deleat-Besson
    University of Michigan, Ann Arbor, MI 48109, USA.
  • Magalie Viallon
    Universite Claude Bernard Lyon 1, INSA-Lyon, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France; Department of Radiology, CHU Saint-Etienne, UJM Saint-Etienne, France.
  • Lorena Petrusca
    Universite Claude Bernard Lyon 1, INSA-Lyon, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France; Department of Radiology, CHU Saint-Etienne, UJM Saint-Etienne, France.
  • Pierre Croisille
    CREATIS-LRMN, INSERM U630, INSA Lyon, Villeurbanne, France.
  • Nicolas Duchateau
    Inria Asclepios research project, Sophia Antipolis, France.

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