Additional value of CT fraction flow reserve in predicting the occurrence of major adverse cardiovascular events in patients with type 2 diabetes mellitus
10.3760/cma.j.cn112149-20240417-00219
- VernacularTitle:CT血流储备分数预测2型糖尿病患者发生主要不良心血管事件的增益价值
- Author:
Yuanyuan WANG
1
;
Ting LU
1
;
Mengyuan JING
1
;
Huaze XI
1
;
Qing LIU
1
;
Qiu SUN
1
;
Hao ZHU
1
;
Junlin ZHOU
1
Author Information
1. 兰州大学第二临床医学院 兰州大学第二医院放射科 甘肃省医学影像重点实验室 医学影像人工智能甘肃省国际科技合作基地，兰州 730000
- Publication Type:Journal Article
- Keywords:
Coronary artery disease;
Diabetes mellitus, type 2;
Angiography;
Fractional flow reserve, myocardial;
Risk assessment
- From:
Chinese Journal of Radiology
2025;59(4):425-431
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the additional prognostic value of coronary CT angiography (CCTA)-based flow reserve fraction (CT-FFR) over semi-quantitative CCTA risk scores in predicting the occurrence of major adverse cardiovascular events (MACE) in type 2 diabetic patients.Methods:A total of 231 patients with type 2 diabetes mellitus who underwent CCTA at Lanzhou University from May 2020 to April 2021 were retrospectively enrolled. Clinical baseline data were collected, and patients were divided into a MACE-positive group (20 cases) and a MACE-negative group (211 cases) based on follow-up results. The CCTA images of all patients were analyzed by semi-quantitative CCTA risk score, which included coronary artery disease reporting and data system classification, segment involvement score, segmental stenosis score, Leaman score, and Leiden score. CT-FFR measurements of CCTA data of all patients were performed using Coronary Analysis software. t-test, U-test, and χ2 test were used to compare baseline parameters between MACE-positive and MACE-negative groups. The Cox proportional hazards regression model was used to analyze the relationship between semi-quantitative CCTA risk score and CT-FFR with the occurrence of MACE, and the area under the curve (AUC) of the receiver operating characteristic (ROC) was used to calculate the efficacy of the prediction model established by the semi-quantitative CCTA risk score combined with CT-FFR. Results:There was no statistically significant difference in baseline data between patients in the MACE-positive and MACE-negative groups ( P>0.05), and there were significant differences in semi-quantitative CCTA risk scores and CT-FFR ( P<0.05). Multivariate Cox proportional risk regression analysis of CT-FFR≤0.80 ( HR=3.860, 95% CI 1.477-10.087, P=0.006) and Leaman score≥5 ( HR=5.210, 95% CI 1.136-23.908, P=0.029) were the best and independent predictors for the occurrence of MACE events. The combined CT-FFR and Leaman score prediction model (AUC=0.791, 95% CI 0.733-0.842, P<0.001) was a better predictor of MACE than CT-FFR alone (AUC=0.718, 95% CI 0.656-0.775, P<0.001) and Leaman score alone (AUC=0.711, 95% CI 0.648-0.768, P<0.001) both had better predictive efficacy ( Z=2.62, 1.98, P=0.009, 0.047). Conclusion:CT-FFR independently predict the occurrence of MACE in patients with type 2 diabetes mellitus and significantly improve the predictive capacity of semi-quantitative CCTA risk score for MACE.
