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June 14, 2026Journal of Cardiovascular Magnetic ResonanceOpen Access

Clinical Importance of All the Characteristics of Late Gadolinium Enhancement from Acquisition to Expert and Artificial Intelligence Analysis: State-of-the-Art

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Key result

AI analysis of LGE may improve prognostic modeling, early disease detection, and personalized treatment decisions.

Why the study?

Despite the widespread clinical use of late gadolinium enhancement, challenges remain in standardizing acquisition parameters, harmonizing interpretation criteria, and addressing considerations for integrating artificial intelligence into clinical workflows.

Design

State-of-the-art review

Authors

JFJeremy FlorenceAUAlexandre UngerTGTrecy Gonçalves

Discussion

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Overview

Granular LGE assessment may refine CMR-based diagnosis and prognosis; extends traditional evaluation but leaves prospective validation open.

Key Points

  • This review explores the clinical importance and technical aspects of late gadolinium enhancement in cardiac imaging, highlighting the integration of artificial intelligence.
  • Comprehensive assessment of LGE characteristics including granularity, location, extent, and pattern.
  • Analysis of advances in imaging protocols and their impact on diagnostic accuracy and reproducibility.
  • Discussion on the role of AI in automating LGE assessment and improving prognostic modeling.
  • LGE provides critical diagnostic and prognostic information across various cardiac conditions.
  • AI-enhanced LGE analysis may improve risk stratification and facilitate earlier disease detection.
  • Challenges in standardizing acquisition parameters and harmonizing interpretation criteria remain.

PICO

P
Population
Cardiac conditions
E
Exposure / Comparator
Late gadolinium enhancement (LGE) and Artificial Intelligence (AI) analysis

This review summarizes the technical, interpretative, and prognostic aspects of late gadolinium enhancement, emphasizing the transformative potential of artificial intelligence in myocardial tissue characterization.

Limitations

  • Challenges remain in standardizing acquisition parameters and harmonizing interpretation criteria across centers.
  • Integration of AI into clinical workflows raises important considerations regarding validation, generalizability, and physician acceptance.

Cite This Study

Florence et al. (2026) conducted a review in Cardiac conditions. Late gadolinium enhancement (LGE) and Artificial Intelligence (AI) analysis was evaluated. Artificial intelligence-based analysis of late gadolinium enhancement may improve prognostic modeling, facilitate earlier disease detection, and enhance personalized therapeutic decision-making.

synapsesocial.com/papers/6a2e4524b1cc60ccdea8a737https://doi.org/10.1016/j.jocmr.2026.102764
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Late Gadolinium Enhancement Cardiac Magnetic Resonance Imaging: From Basic Concepts to Emerging Methods2022 · 30 citations
  2. 2Myocardial Late Gadolinium Enhancement (LGE) in Cardiac Magnetic Resonance Imaging (CMR)—An Important Risk Marker for Cardiac Disease2024 · 50 citations
  3. 3The Prognostic Impact of Myocardial Late Gadolinium Enhancement2014 · 9 citations
  4. 4Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization2024 · 2 citations
  5. 5Prognostic significance of artificial intelligence quantified late gadolinium enhancement in hypertrophic cardiomyopathy2026