Aurélien Bustin, Matthias Stuber, Victor de Villedon de Naide, Manuel Villegas-Martínez, Kalvin Narceau, Thaïs Génisson, Théo Richard, Pauline Gut, Valéry Ozenne, Marion Constantin, Guido Caluori, Konstantinos Vlachos, Géraldine Montier, Daphné Pasche, Théo Bedague, Jean‐David Maes, Soumaya Sridi, Claire Bazin, Gaël Dournes, Stéphanie Clément-Guinaudeau, Ilyes Ben Lala, Mélèze Hocini, Michel Montaudon, Pierre Jaı̈s, Hubert Cochet
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. Cardiovascular disease remains the leading global cause of death, highlighting the need for better imaging of myocardial injury. Here, the authors show that SPOT, an AI powered dual bright- and black-blood imaging approach, improves myocardial scar detection and measurement for more accurate diagnosis and treatment of heart disease.