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News
Normalizing epicardial fat to heart size on CT scans could be a powerful tool for ruling out coronary artery disease (CAD). A study of over 27,500 CT scans found that a heart-size-adjusted fat ratio (EATVh) with a cutoff of 0.1 achieved a 97.1% negative predictive value for obstructive CAD. It also eliminates sex-based differences in fat measurements, making it more equitable across genders.
Researchers may have found a smarter way to use CT imaging data already being collected: by normalizing epicardial fat volume to total heart size, clinicians could reliably rule out obstructive coronary artery disease (CAD) in most patients.
The study, published in the European Journal of Radiology, analyzed data from over 27,500 CT scans — including a large Swedish population cohort and a Finnish clinical cohort of symptomatic patients. Using a deep learning model, researchers calculated the ratio of epicardial adipose tissue volume to total heart volume (EATVh) and found that a cutoff of 0.1 effectively identified low-risk patients with high confidence. A standout finding: normalizing to heart size eliminated the significant sex-based differences seen in raw fat measurements, making the metric more consistent and equitable across genders.
By the Numbers:
Why it matters: This approach could allow clinicians to confidently rule out obstructive CAD using non-invasive imaging already performed in routine care, potentially reducing the need for further testing in low-risk patients — and doing so more consistently across sexes.
