Research on the distribution spectrum of atherosclerotic plaques in patients with suspected coronary artery disease and the noninvasive screening model for coronary atherosclerosis burden

Pengxi Han; Jinyan Tang; Ximing Wang; Yuwen Su; Guijie Li; Kai Deng

doi:10.21037/qims-20-901

Research on the distribution spectrum of atherosclerotic plaques in patients with suspected coronary artery disease and the noninvasive screening model for coronary atherosclerosis burden

Quant Imaging Med Surg. 2021 Jul;11(7):3274-3285. doi: 10.21037/qims-20-901.

Authors

Pengxi Han¹, Jinyan Tang², Ximing Wang³, Yuwen Su¹, Guijie Li⁴, Kai Deng¹

Affiliations

¹ Department of Radiology, the First Affiliated Hospital of Shandong First Medical University, Jinan, China.
² Department of Pediatrics, Xiangxi Autonomous Prefecture People's Hospital, Jishou, China.
³ Department of Radiology, Shandong Provincial Hospital of Shandong First Medical University, Jinan, China.
⁴ Department of Interventional Radiology, the First Affiliated Hospital of Shandong First Medical University, Jinan, China.

Abstract

Background: This study aimed to establish a non-invasive and simple screening model of coronary atherosclerosis burden based on the associations between multiple blood parameters and total plaque score (TPS), segment-stenosis score (SSS), coronary artery disease severity (CADS) in coronary artery disease (CAD) and thus reduce unnecessary coronary angiography (CAG).

Methods: A total of 1,366 patients with suspected CAD who underwent CAG were included in this study. The clinical risk factors [age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), fasting plasma glucose (FPG), and glycated hemoglobin (GHB)] were collected. The presence of plaques and lumen stenosis was assessed based on CAG imaging. The TPS, SSS, and CADS were calculated, and the distribution spectrum of atherosclerotic plaques was described. Kruskal-Wallis test for multiple comparison tests was performed to analyze the differences in groups of different risk factors. The selected independent predictors were put into a multivariate logistic model, and the variables were further screened by stepwise regression to establish a screening model. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the selected model's discriminant effect.

Results: The distributions of TPS and SSS scores were both right-skewed. Among males, both TPS and SSS scores were higher than in females (χ²=46.7659, P<0.0001, χ²=51.6603, P<0.0001). Both TPS and SSS scores increased with age (χ²=123.4456, P<0.0001, χ²=123.4456, P<0.0001). For TPS, the most common position was proximal left anterior descending artery (P-LAD, 51.39%). In SSS, the P-LAD plaque was highest: 0: 48.61%, 1: 10.32%, 2: 9.15%, and 3: 31.92%. The TPS score >5, SSS score >5, and CAD >0 were valuable indicators for SBP, FPG, TG, HDL, and GHB. In the model, TPS score >5, SSS score >5, and CADS >0, the area under ROC curve (AUC) was 0.753 [95% confidence interval (CI): 0.713 to 0.789], 0.728 (95% CI: 0.687 to 0.766), and 0.756 (95% CI: 0.717 to 0.793), respectively.

Conclusions: The most common site of lesions was P-LAD. These models can be used as non-invasive and simple initial screening tools without CAG.

Keywords: Coronary artery disease (CAD); coronary angiography (CAG); non-invasive screening model; plaque distribution spectrum.