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Published on: September 22, 2023
[Value of Multivariate Computed Tomography Angiography for Predicting Major Adverse Cardiac Events in Patients With
Bo Tu1, Weiliang Xiao1, Zhihua Pan1
1· ( 610051)Department of Radiology, The Second Affiliated Hospital of Chengdu Medical College (China National Nuclear Corporation 416 Hospital), Chengdu 610051, China.
Objective:
To investigate the predictive value of computed tomography angiography (CTA)-derived fractional flow reserve (FFR), fat attenuation index (FAI), and plaque characteristics for the occurrence of major adverse cardiac events (MACE) in patients with coronary artery heart disease (CAD).
Methods:
A total of 205 CAD patients were retrospectively enrolled at our hospital, and their demographic and clinical data were analyzed accordingly. All patients underwent CTA, and their FFR, FAI and plaque characteristics were measured. According to the occurrence of MACE within a 36-month follow-up period, the patients were divided into a MACE group (n = 42) and a non-MACE group (n = 163). The clinical data, FFR, FAI, and plaque characteristics were compared between the 2 groups, and logistic regression analysis was performed to identify factors associated with MACE in CAD patients. FFR, FAI, and plaque burden (PB) were further compared among patients with different degrees of coronary artery stenosis, and Spearman correlation analysis was performed to evaluate the associations of FFR, FAI, and PB with the severity of coronary artery stenosis. Receiver operating characteristic (ROC) curves were plotted to assess the predictive value of FFR, FAI, and PB for MACE in CAD patients.
Results:
Compared with those in the non-MACE group, the body mass index (BMI), the proportion of patients with vascular lesions involving 2 or more coronary arteries, the proportion of patients with severe coronary stenosis, FAI, lipid plaque volume, non-calcified plaque volume, and PB were significantly higher (all P < 0.05) in the MACE group, whereas FFR was significantly lower (P < 0.05) in the MACE group. Variables with variance inflation factor (VIF) < 3 on collinearity diagnostics were included in multivariate logistic regression analysis. The results showed that multivessel lesion (odds ratio [OR], 2.188; 95% CI, 1.304-3.671), severe coronary artery stenosis (OR, 2.918; 95% CI, 1.608-5.295), increased FAI (OR, 2.635; 95% CI, 1.510-4.598), and increased PB (OR, 2.396; 95% CI, 1.382-4.157) were risk factors for MACE in CAD patients (P < 0.05), while increased FFR (OR, 0.373; 95% CI, 0.221-0.630) was a protective factor (P < 0.05). Stratified analysis by the severity of coronary artery stenosis showed that patients with mild stenosis had significantly higher FFR and significantly lower FAI and PB than those with moderate or severe stenosis (all P < 0.05), and that patients with moderate stenosis had significantly higher FFR and significantly lower FAI and PB than those with severe stenosis (all P < 0.05). Spearman correlation coefficient analysis revealed that the severity of coronary artery stenosis was positively correlated with FAI (r = 0.687; 95% CI, 0.598-0.760) and PB (r = 0.664; 95% CI, 0.571-0.741) (P < 0.05), but negatively correlated with FFR (r = -0.712; 95% CI, -0.782 to -0.628; P < 0.05). ROC curve analysis showed that the areas under the curve (AUCs) for predicting MACE in CAD patients using FFR, FAI, and PB individually were 0.831 (95% CI, 0.750-0.876), 0.790 (95% CI, 0.719-0.861), and 0.724 (95% CI, 0.646-0.802), respectively, whereas the combined model using the 3 parameters achieved an AUC of 0.927 (95% CI, 0.890-0.964), demonstrating superior predictive performance.
Conclusion:
CTA-derived FFR, FAI, and PB are significantly correlated with the severity of coronary artery stenosis in patients with CAD. Combined assessment of these parameters demonstrates higher predictive value for the occurrence of MACE in patients with CAD.
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An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...