Non-invasive diagnostic value of pericoronary fat attenuation index for identifying culprit lesions in acute coronary syndrome

Objectives

This study aimed to determine the efficacy of fat attenuation index (FAI) as a non-invasive diagnostic tool in the precise identification of culprit lesions in individuals diagnosed with acute coronary syndrome (ACS).

Methods

A retrospective analysis of 230 patients with non-ST-segment elevation ACS. PCAT attenuation (FAI_standard) was measured in the proximal 40-mm segment of each major coronary artery. Furthermore, the average PCAT attenuation of the identified lesions was designated as FAI_lesion. The average PCAT attenuation across the complete length of coronary artery, referred to as FAI_average, was computed. Plaque characteristics (volume, composition) were analyzed via coronary computed tomography angiography. Multivariable logistic regression identified predictors of culprit lesions, and diagnostic performance was assessed using area under the curve (AUC) and decision curve analysis.

Results

Culprit lesions exhibited significantly elevated levels of PCAT attenuation across the parameters of FAI_standard, FAI_average, and FAI_lesion. FAI_lesion demonstrated superior diagnostic accuracy versus FAI_standard and FAI_average, and also emerged as the strongest independent predictor (Odds ratio = 2.598, P < 0.001). In training and test sets, a composite model integrating FAI_lesion with additional indices demonstrated enhanced diagnostic efficacy for the detection of culprit lesions in patients with ACS (AUC = 0.960, 0.803). Low-attenuation plaque volume (<30 HU) was independently associated with culprit lesions (OR = 3.12, P = 0.002).

Conclusion

FAI_lesion, a superior non-invasive biomarker for high-risk ACS lesions compared to traditional FAI, enables earlier precise risk stratification through clinical integration.