ArticleScientific reports2024
Quantification of myocardial scar of different etiology using dark- and bright-blood late gadolinium enhancement cardiovascular magnetic resonance.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 17 citations in OpenAlex.
- Enhancing risk prediction for sudden cardiac death: quantitative late gadolinium enhancement analysis in hypertrophic cardiomyopathy.Insights into imaging · 2026Article
- Visual standardized quantification of late gadolinium enhancement, a contour-less method for late gadolinium enhancement quantification.European heart journal. Imaging methods and practice · 2026Article
- Microstructural disease and hypoperfusion in dilated cardiomyopathy underpin midwall septal fibrosis.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2026Article
- Dynamic microRNA Signatures as Biomarkers for Cardiac Ischemia and Remodeling.International journal of molecular sciences · 2026Article
- Late-gadolinium enhancement predicts appropriate device therapies in nonischemic recipients of primary prevention implantable cardioverter-defibrillators.Heart rhythm · 2025Article
- Cardiac magnetic resonance research advances in myocardial fibrosis of hypertrophic cardiomyopathy.Frontiers in cardiovascular medicine · 2025Review
- Quantification of myocardial oxygen extraction fraction on noncontrast MRI enabled by deep learning.Radiology advances · 2024Article
- Automated cardiovascular MR myocardial scar quantification with unsupervised domain adaptation.European radiology experimental · 2024Article
- Conditions for late gadolinium enhancement MRI in myocardial infarction model rats that better reflect microscopic tissue staining.Scientific reports · 2024Article
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10 authors at 6 institutions in 5 countries.
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Abstract
Dark-blood late gadolinium enhancement (LGE) has been shown to improve the visualization and quantification of areas of ischemic scar compared to standard bright-blood LGE. Recently, the performance of various semi-automated quantification methods has been evaluated for the assessment of infarct size using both dark-blood LGE and conventional bright-blood LGE with histopathology as a reference standard. However, the impact of this sequence on different quantification strategies in vivo remains uncertain. In this study, various semi-automated scar quantification methods were evaluated for a range of different ischemic and non-ischemic pathologies encountered in clinical practice. A total of 62 patients referred for clinical cardiovascular magnetic resonance (CMR) were retrospectively included. All patients had a confirmed diagnosis of either ischemic heart disease (IHD; n = 21), dilated/non-ischemic cardiomyopathy (NICM; n = 21), or hypertrophic cardiomyopathy (HCM; n = 20) and underwent CMR on a 1.5 T scanner including both bright- and dark-blood LGE using a standard PSIR sequence. Both methods used identical sequence settings as per clinical protocol, apart from the inversion time parameter, which was set differently. All short-axis LGE images with scar were manually segmented for epicardial and endocardial borders. The extent of LGE was then measured visually by manual signal thresholding, and semi-automatically by signal thresholding using the standard deviation (SD) and the full width at half maximum (FWHM) methods. For all quantification methods in the IHD group, except the 6 SD method, dark-blood LGE detected significantly more enhancement compared to bright-blood LGE (p < 0.05 for all methods). For both bright-blood and dark-blood LGE, the 6 SD method correlated best with manual thresholding (16.9% vs. 17.1% and 20.1% vs. 20.4%, respectively). For the NICM group, no significant differences between LGE methods were found. For bright-blood LGE, the 5 SD method agreed best with manual thresholding (9.3% vs. 11.0%), while for dark-blood LGE the 4 SD method agreed best (12.6% vs. 11.5%). Similarly, for the HCM group no significant differences between LGE methods were found. For bright-blood LGE, the 6 SD method agreed best with manual thresholding (10.9% vs. 12.2%), while for dark-blood LGE the 5 SD method agreed best (13.2% vs. 11.5%). Semi-automated LGE quantification using dark-blood LGE images is feasible in both patients with ischemic and non-ischemic scar patterns. Given the advantage in detecting scar in patients with ischemic heart disease and no disadvantage in patients with non-ischemic scar, dark-blood LGE can be readily and widely adopted into clinical practice without compromising on quantification.
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