Predictive value of flow reserve fraction based on coronary CT angiography combined with peripheral fat decay index in early of coronary heart disease

CHEN Pengcheng; LU Zhiqian; TANG Long; CHEN Rui

doi:10.20258/j.cnki.1006-9011.2025.08.012

Abstract：Objective To investigate the early diagnostic value of fractional flow reserve(CT-FFR)combined with perivascu-lar fat attenuation index(FAI)based on coronary CT angiography(CCTA)for coronary heart disease.Methods A total of 109 patients with suspected or known CHD(156 diseased vessels)who underwent coronary angiography and CCTA were selected.According to the results of coronary angiography,the diseased vessels were divided into CHD group(88 vessels)and non-CHD group(68 vessels)according to the degree of stenosis.The CCTA parameters,in terms of CT-FFR,FAI,plaque burden,plaque volume(total plaque volume,calcified plaque volume,lipid plaque volume,fibrous plaque volume),plaque length,narrowest lumen diameter,narrowest lumen area,diameter stenosis rate,and area stenosis rate,were compared between the two groups.Univariate and multivariate Logistic regression analysis were used to screen the risk factors of coronary heart disease.The re-ceiver operating characteristic(ROC)curve was drawn,and the diagnostic efficacy of CCTA parameters for coronary heart dis-ease was evaluated according to the area under the curve(AUC).The R software was used to construct the nomogram,and the calibration curve and decision curve were used to evaluate the prediction performance of the model.Results The CT-FFR and narrowest lumen diameter in the CHD group were lower than those in the non-CHD group,FAI,plaque burden,total plaque vol-ume,lipid plaque volume,plaque length,diameter stenosis and area stenosis were higher than those in the non-CHD group,and the differences were statistically significant(all P<0.001).Multivariate Logistic regression analysis showed that CT-FFR(OR=0.019,95%CI:0.006-0.066,P<0.01),FAI(OR=1.881,95%CI:1.087-3.257,P<0.05),lipid plaque volume(OR=0.312,95%CI:0.115-0.848,P<0.05)and area stenosis(OR=1.052,95%CI:0.739-1.498,P<0.05)were independent risk factors for CHD.ROC curve analysis showed that the AUC of CT-FFR,FAI,plaque characteristics and the combination of the three for predicting coronary heart disease were 0.889,0.843,0.762 and 0.931,respectively,and the prediction efficiency of the combination of the three was higher than that of the individual indicators(all P<0.001).The nomogram prediction model based on CT-FFR,FAI and plaque characteristics had a good calibration(P=0.894),and the decision curve showed that the model had a high positive clinical net benefit within the threshold range of 0.10-0.95.Conclusion The nomogram model based on CT-FFR,FAI and plaque features has high predictive value for coronary heart disease,which can provide reference for early clinical diagnosis.