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

Aurelien Bustin1,2,3, Matthias Stuber4,5,6, Victor de Villedon de Naide4,7

  • 1IHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France. aurelien.bustin@ihu-liryc.fr.

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|December 17, 2025
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Summary

A new imaging technique, SPOT, combined with AI, accurately detects and quantifies myocardial injury. This approach overcomes limitations of current methods, offering faster and more reliable assessments for heart disease patients.

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Area of Science:

  • Cardiovascular Imaging
  • Artificial Intelligence in Medicine
  • Medical Diagnostics

Background:

  • Cardiovascular disease is a leading cause of death globally.
  • Current MRI methods for myocardial injury assessment have limitations in scar detection and reproducibility.
  • Manual analysis of cardiac MRI is time-consuming and prone to variability.

Purpose of the Study:

  • To introduce SPOT, a novel multi-spectral imaging sequence for enhanced myocardial scar visualization.
  • To integrate SPOT with an AI framework for automated quantification of myocardial injury.
  • To evaluate the diagnostic accuracy and efficiency of the combined SPOT-AI platform.

Main Methods:

  • Development of a multi-spectral bright- and black-blood imaging sequence (SPOT).
  • Integration of an artificial intelligence framework for automated image analysis.
  • Validation of the SPOT-AI platform in simulations, animal models, and human patients.

Main Results:

  • SPOT provides superior scar-to-blood contrast compared to conventional MRI.
  • The AI framework enables rapid, automated, and operator-independent quantification of myocardial injury.
  • The combined platform demonstrated accurate detection and quantification in diverse validation settings.

Conclusions:

  • The SPOT-AI platform offers a significant advancement in assessing myocardial injury.
  • This innovation facilitates earlier diagnosis and improved management of ischemic heart disease.
  • Potential applications extend to various other clinical scenarios requiring myocardial assessment.