Detection of Diffuse to Focal Myocardial Fibrosis by Cardiovascular Magnetic Resonance Against Histology in Mini-Swine

doi:10.1101/2025.01.13.632871

Detection of Diffuse to Focal Myocardial Fibrosis by Cardiovascular Magnetic Resonance Against Histology in Mini-Swine

2025 · doi:10.1101/2025.01.13.632871

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This study evaluated how well cardiovascular magnetic resonance (CMR) techniques detect myocardial fibrosis across a range of severities, using a mini-swine model (16 with myocardial infarction and 2 healthy) with histology as the gold standard. Researchers acquired cine imaging, late gadolinium enhancement (LGE), and T1/ECV mapping using two T1-mapping sequences (MOLLI 5(3)3 and ShMOLLI 5(1)1(1)1), then categorized tissue based on triphenyl tetrazolium chloride staining and quantified fibrotic burden by collagen volume fraction (CVF). For severe fibrosis, LGE, T1, and ECV showed excellent discrimination (AUCs ~0.88–0.96), with ECVShMOLLI performing best and better differentiating severe fibrosis and MI than ECV-MOLLI; for mild fibrosis in remote myocardium, T1ShMOLLI and ECVShMOLLI differentiated remote from healthy where LGE and other mapping approaches did not. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Background Myocardial fibrosis predicts adverse outcomes in myocardial infarction (MI) and other cardiovascular conditions. Cardiovascular magnetic resonance (CMR) can non-invasively detect focal and diffuse myocardial fibrosis, but comprehensive validation against histology remains scarce. Aims To assess the comparative diagnostic performance of CMR methods in detecting myocardial fibrosis, using a mini-swine model and histology as gold standard. Methods Eighteen mini-swine (16 MI; 2 healthy) underwent CMR cine, LGE, T1- and ECV-mapping. Two commonly-used T1-mapping methods – MOLLI 5(3)3 and ShMOLLI 5(1)1(1)1 – were included. Pathological sections were categorized as infarcted, peri-infarct, remote and healthy myocardium based on triphenyl tetrazolium chloride staining. Fibrotic burden was quantified by collagen volume fraction (CVF) into severe (CVF≥30%), moderate (CVF=10-25%), and mild (CVF=3-14%). The relationships between LGE, T1, ECV and CVF, and diagnostic performance using area-under-the-curve (AUC), were analyzed. Results For detecting severe fibrosis, LGE, T1 and ECV all had excellent diagnostic performance (AUC: LGE=0.93, ECV ShMOLLI =0.96, T1 ShMOLLI =0.91, T1 MOLLI =0.93, ECV MOLLI =0.88). ECV ShMOLLI showed significantly better discriminatory accuracy than ECV MOLLI in detecting severe fibrosis and MI (both p<0.05), with the highest correlation to CVF (ECV ShMOLLI r=0.86, ECV MOLLI r=0.82, T1 ShMOLLI r=0.77, T1 MOLLI r=0.77, semi-quantitative LGE r=0.75). Only T1 ShMOLLI and ECV ShMOLLI , but not LGE or T1 MOLLI /ECV MOLLI , differentiated remote myocardium with mild fibrosis (CVF=8.23%) from healthy myocardium (CVF=2.01%). Conclusions CMR can detect severe to mild myocardial fibrosis as validated against histology. For low-grade fibrosis, T1-mapping significantly outperformed LGE. Choice of CMR methodologies matters for myocardial fibrosis detection, which has importance for clinical trial design.

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Abstract

Methods

Eighteen mini-swine (16 MI; 2 healthy) underwent CMR cine, LGE, T1- and ECV-mapping. Two commonly-used T1-mapping methods – MOLLI 5(3)3 and ShMOLLI 5(1)1(1)1 – were included. Pathological sections were categorized as infarcted, peri-infarct, remote and healthy myocardium based on triphenyl tetrazolium chloride staining. Fibrotic burden was quantified by collagen volume fraction (CVF) into severe (CVF≥30%), moderate (CVF=10-25%), and mild (CVF=3-14%). The relationships between LGE, T1, ECV and CVF, and diagnostic performance using area-under-the-curve (AUC), were analyzed.

Results

For detecting severe fibrosis, LGE, T1 and ECV all had excellent diagnostic performance (AUC: LGE=0.93, ECVShMOLLI=0.96, T1ShMOLLI=0.91, T1MOLLI=0.93, ECVMOLLI=0.88). ECVShMOLLI showed significantly better discriminatory accuracy than ECVMOLLI in detecting severe fibrosis and MI (both p<0.05), with the highest correlation to CVF (ECVShMOLLI r=0.86, ECVMOLLI r=0.82, T1ShMOLLI r=0.77, T1MOLLI r=0.77, semi-quantitative LGE r=0.75). Only T1ShMOLLI and ECVShMOLLI, but not LGE or T1MOLLI/ECVMOLLI, differentiated remote myocardium with mild fibrosis (CVF=8.23%) from healthy myocardium (CVF=2.01%).

Conclusions

CMR can detect severe to mild myocardial fibrosis as validated against histology. For low-grade fibrosis, T1-mapping significantly outperformed LGE. Choice of CMR methodologies matters for myocardial fibrosis detection, which has importance for clinical trial design. Competing Interest Statement The authors have declared no competing interest. Abbreviations List - AUC - area-under-the-curve - CAG - Coronary angiography - CMR - cardiovascular magnetic resonance - CVF - collagen volume fraction - ECV - extracellular volume fraction - LGE - late gadolinium enhancement - MI - myocardial infarction - MOLLI - modified Look-Locker inversion recovery - ROC - Receiver operating characteristic - ShMOLLI - shortened MOLLI - TTC - triphenyl tetrazolium chloride

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