Combined imaging of myocardial scar and fat using AI-guided dual bright- and black-blood late gadolinium enhancement

Aims Characterization of myocardial scar and fat is clinically important for diagnosis, risk stratification, and procedural planning in cardiomyopathies. While black-blood late gadolinium enhancement (LGE) improves scar conspicuity, fat remains hyperintense and may confound interpretation. We aimed to develop and evaluate SPOT-DIXON, a dual bright- and black-blood LGE sequence with Dixon water-fat separation and artificial intelligence (AI)-guided analysis, enabling simultaneous and co-registered quantification of myocardial scar and intra- and extra-cardiac fat. Methods SPOT-DIXON alternates bright- and black-blood LGE preparations on consecutive heartbeats while acquiring dual-echo data for Dixon water-fat separation. Simulations, phantom experiments, and validations in a prospective cohort of 36 patients referred for cardiac MRI were performed. An AI model automatically segmented the left ventricular (LV) wall on bright-blood water images, with contours propagation to scar and fat images. Results Simulations and phantoms confirmed preserved bright- and black-blood contrast and accurate water-fat separation. In patients, AI-based LV wall segmentation showed excellent agreement with manual delineation (global DICE=84.4 ± 4.0%). SPOT-DIXON yielded higher scar volume, burden, and transmurality measurements than reference sequences, while LV wall volume was similar between sequences. Novel quantitative metrics, including intramyocardial fat burden expressed relative to scar mass, were feasible only with SPOT-DIXON. Acquisition times were comparable across sequences (5min55s ± 2min17 s), while AI-based analysis substantially reduced post-processing time to 2.1 ± 0.7 seconds. Conclusion AI-guided SPOT-DIXON enables simultaneous, co-registered assessment of myocardial scar and fat within a single LGE acquisition. This approach overcomes key limitations of current workflows and introduces novel quantitative markers of fibrofatty remodelling with potential clinical relevance in cardiomyopathies.