Multi-parametric Algorithm for Epicardial Adipose Tissue Quantification in Patients with Non-Ischemic Heart Disease

Area of Science:

• Cardiology
• Radiology
• Biomedical Imaging

Background:

• Epicardial adipose tissue (EAT) plays a role in cardiovascular pathogenesis.
• Cardiac magnetic resonance (CMR) is the gold standard for EAT volume (EATV) quantification but has limitations.
• Non-contrast chest CT (NCCT) is a widely available imaging modality.

Purpose of the Study:

• To investigate the feasibility of using NCCT for EATV assessment.
• To compare EATV and EAT thickness measurements between NCCT and CMR.
• To validate NCCT as an alternative to CMR for EAT quantification.

Main Methods:

• 120 non-ischemic heart disease patients underwent both NCCT and CMR.
• EATV was measured using CMR volumetry and NCCT threshold segmentation.
• EAT thickness was quantified at six anatomical sites on both modalities.

Main Results:

• NCCT-based EATV measurements were not significantly different from CMR volumetry (P>0.05).
• EAT thickness measurements showed no significant differences between NCCT and CMR across all sites (all P>0.05).
• NCCT provides comparable EATV measurements to the CMR reference standard.

Conclusions:

• NCCT-based grayscale threshold segmentation is a feasible method for EATV assessment.
• NCCT is a rapid, cost-effective, and clinically viable alternative for accurate EAT quantification.
• This finding supports the broader clinical utility of NCCT in cardiovascular imaging.