Work

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

Year: 2025

Type: article

Abstract: 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.

Source: European Journal of Radiology Open

DOI: 10.1016/j.ejro.2025.100682

Authors: Fengfeng Yang, Zhengyang Li, Haoran Cai, Jing Zhu, Huijia Liu, Yang Zhao

Institution: Second Hospital of Tianjin Medical University

Language: English

Topic: Cardiac Imaging and Diagnostics

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,610