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| Item Type: | Review |
|---|---|
| Title: | Clinical importance of all the characteristics of late gadolinium enhancement from acquisition to expert and artificial intelligence analysis: state-of-the-art |
| Creators Name: | Florence, Jeremy, Unger, Alexandre, Gonçalves, Trecy, Liberato, Gabriela, Garot, Jérôme, Soulat, Gilles, Pontana, François, Dacher, Jean-Nicolas, Bohbot, Yohann, Schulz-Menger, Jeanette, Toupin, Solenn, Lima, Joao A.C. and Pezel, Théo |
| Abstract: | Late gadolinium enhancement (LGE) assessed by cardiovascular magnetic resonance is the cornerstone in the assessment of myocardial tissue characterization, providing crucial diagnostic and prognostic information across a wide spectrum of cardiac conditions. While LGE is traditionally evaluated for its presence and extent, a comprehensive assessment of its diverse characteristics, called “LGE granularity”—including its location, extent, and pattern—offers deeper insights into myocardial pathophysiology. The clinical significance of LGE is influenced by various factors, ranging from acquisition protocols including choice of contrast-media and post-processing techniques to interpretation by expert readers and, more recently, artificial intelligence (AI)-based analysis. Advances in imaging protocols have refined LGE detection and quantification, improving diagnostic accuracy and reproducibility. Furthermore, AI approaches are revolutionizing LGE assessment by enabling automated segmentation, feature extraction, and risk stratification. Despite the widespread clinical use of LGE, challenges remain in standardizing acquisition parameters and harmonizing interpretation criteria across centers. Additionally, the integration of AI into clinical workflows raises important considerations regarding validation, generalizability, and physician acceptance. However, emerging evidence suggests that AI-based LGE analysis may improve prognostic modeling, facilitate earlier disease detection, and enhance personalized therapeutic decision-making. This review provides a state-of-the-art of LGE’s technical, interpretative, and prognostic aspects, highlighting the role of AI in myocardial tissue characterization. By bridging traditional expert analysis with cutting-edge computational techniques, the future of LGE assessment aims to refine cardiac risk stratification and guide precision medicine in cardiology. |
| Keywords: | Review, Cardiovascular Magnetic Resonance, Late Gadolinium Enhancement, Artificial Intelligence, Cardiomyopathies, Acquisition, Imaging Protocol, Standardized Analysis |
| Source: | Journal of Cardiovascular Magnetic Resonance |
| ISSN: | 1097-6647 |
| Publisher: | Elsevier |
| Page Range: | 102764 |
| Date: | 11 June 2026 |
| Official Publication: | https://doi.org/10.1016/j.jocmr.2026.102764 |
| PubMed: | View item in PubMed |
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