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AI-powered SPOT imaging for enhanced myocardial scar detection and quantification.

December 17, 2025pubmed logopapers

Authors

Bustin A,Stuber M,de Villedon de Naide V,Villegas-Martinez M,Narceau K,Génisson T,Richard T,Gut P,Ozenne V,Constantin M,Caluori G,Vlachos K,Montier G,Pasche D,Bedague T,Maes JD,Sridi S,Bazin C,Dournes G,Clément-Guinaudeau S,Ben Lala I,Hocini M,Montaudon M,Jaïs P,Cochet H

Affiliations (8)

  • IHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France. [email protected].
  • Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France. [email protected].
  • Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland. [email protected].
  • IHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
  • Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
  • Center for Biomedical Imaging (CIBM), Lausanne, Switzerland.
  • Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
  • Department of Cardiac Electrophysiology, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.

Abstract

Cardiovascular disease is the leading global cause of death, underscoring the need for accurate assessment of myocardial injury. The current gold standard, bright-blood late gadolinium enhanced MRI, suffers from poor contrast at the blood-scar interface, reducing sensitivity for subendocardial scar detection and limiting reproducibility. Moreover, reliance on expert manual analysis makes interpretation labor-intensive and variable. Here, we present SPOT, a multi-spectral bright- and black-blood imaging sequence that provides unprecedented scar-to-blood contrast and clear anatomical detail. Integrated with an artificial intelligence (AI) framework for automated image analysis, SPOT enables rapid, fully automated, and operator-independent quantification of myocardial injury. Validated in simulations, animal infarct models, and patients with heart disease, this combined imaging-AI platform delivers accurate detection and quantification in a single acquisition. This innovation presents significant opportunities for earlier diagnosis and enhanced therapeutic management of ischemic heart disease, with potential applications in a wide spectrum of other clinical settings.

Topics

CicatrixMyocardiumMagnetic Resonance ImagingMyocardial InfarctionArtificial IntelligenceJournal Article

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