Int J Cardiovasc Imaging. 2025 Nov 7. doi: 10.1007/s10554-025-03554-z. Online ahead of print.
ABSTRACT
Femoral artery pseudoaneurysms are a recognized complication of coronary angiography performed via femoral access, with incidence rates ranging from 0.2% to 8%. Identifying high-risk patients could guide procedural modifications to reduce this risk. This study evaluated whether computed tomography (CT)-derived measurements of adipose tissue and muscle mass predict femoral artery pseudoaneurysm development. In this retrospective cohort study, we included 148 patients who underwent coronary angiography via femoral access and had a thorax CT scan with 3 months of angiography at Health Sciences University Sultan 2. Abdülhamid Han Training and Research Hospital. CT images were analyzed at the 12th thoracic vertebra to measure adipose and muscle tissue areas, normalized by height squared to derive adiposity and muscularity indices. Patients were divided into those with pseudoaneurysms (n = 49) and controls (n = 99). Statistical analyses included t-tests, Mann-Whitney U tests, logistic regression, and receiver operating characteristic (ROC) curve analysis. Patients with pseudoaneurysms had significantly higher adipose tissue (median 241 cm² vs. 104 cm², p < 0.001) and adiposity index (median 14.11 vs. 7.29, p < 0.001) compared to controls. Multivariate logistic regression identified adipose tissue (OR 1.038, 95% CI 1.007-1.071, p = 0.017) and adiposity index (OR 1.294, 95% CI 1.065-1.572, p = 0.010) as independent predictors of pseudoaneurysm development. ROC analysis showed adipose tissue (AUC 0.801, threshold > 136 cm², specificity 75%, sensitivity 86%) and adiposity index (AUC 0.774, threshold > 10.03, specificity 71%, sensitivity 78%) had good predictive ability. CT-derived adipose tissue and adiposity index measurements are significant predictors of femoral artery pseudoaneurysm following coronary angiography. Pre-procedural CT assessment could identify high-risk patients, potentially guiding safer procedural strategies.
PMID:41201707 | DOI:10.1007/s10554-025-03554-z
