基于冠脉CTA减影的斑块定量参数对冠状动脉钙化所致狭窄程度的评估OACSTPCD

Objective:To explore the feasibility of plaque quantitative parameters based on coronary CT angiography(CCTA)subtraction in evaluating the degree of stenosis caused by coronary artery calcification.Methods:A total of 184 patients who underwent CCTA subtraction examination in our hospital from April 2021 to June 2023 were selected.After imaging examination,they were divided into positive group(n=84)and negative group(n=100)according to the degree of lumen stenosis.General data and plaque quantitative parameters of the two groups were compared.Receiver operating characteristic(ROC)was used to evaluate the value of plaque quantitative parameters of CCTA subtraction in the diagnosis of significant coronary artery stenosis caused by calcification.Hierarchical regression model was used to analyze the relationship between different plaque quantitative parameters and coronary artery stenosis caused by calcification.Multivariate Logistic regression was used to analyze the risk factors of coronary artery stenosis induced by calcification.The subjects were randomly divided into a training set(n=92)and a verification set(n=92)at a 1:1 ratio,and the artificial neural network(ANN)prediction model was constructed and evaluated.Results:There was significant difference in calcification score between positive group and negative group(P＜0.05).Compared with the negative group,the plaque length,total plaque volume,plaque load,calcified plaque volume,calcified plaque proportion and average density of calcified components in the positive group were higher(P＜0.05).Plaque length,total plaque volume,plaque load,calcified plaque volume,proportion of calcified plaque,and average density of calcified components of CCTA subtractive plaque quantitative parameters were effective in the diagnosis of significant coronary artery stenosis caused by calcification.And combined diagnosis of coronary artery calcification caused by obvious stenosis,diagnosis efficiency is higher.Stratified regression analysis showed that plaque length,total plaque volume,plaque load,calcified plaque volume,calcified plaque proportion,and average density of calcified components had positive effects on the significant stenosis caused by coronary artery calcification(P＜0.05).Multivariate Logistic regression analysis showed that calcification score,plaque length,total plaque volume,plaque load,calcified plaque volume,calcified plaque proportion,and increased mean density of calcified components were all risk factors for significant coronary artery stenosis in patients undergoing CCTA subtraction examination(P＜0.05).Seven variables selected by multivariate Logistic regression were used as ANN input variables,among which plaque length,total plaque volume,plaque load and calcified plaque volume had the greatest influence on the significant stenosis caused by coronary artery calcification.ROC curve shows that the model has good differentiation and accuracy.Conclusion:Plaque quantitative parameters based on CCTA subtraction can improve the diagnostic efficacy of CCTA in the diagnosis of significant stenosis caused by coronary artery calcification to a certain extent,and the combination of plaque quantitative parameters in the diagnosis of significant stenosis caused by coronary artery calcification has a good diagnostic efficacy.