five

2018 JACC CI (Static CTP accuracy)

收藏
Mendeley Data2026-04-18 收录
下载链接:
https://data.mendeley.com/datasets/bphvwn8rn9
下载链接
链接失效反馈
官方服务:
资源简介:
OBJECTIVES The goal of this study was to evaluate the diagnostic accuracy of stress computed tomography myocardial perfusion (CTP) for the detection of functionally significant coronary artery disease (CAD) by using invasive coronary angiography (ICA) plus invasive fractional flow reserve (FFR) as the reference standard in consecutive intermediate- to high-risk symptomatic patients. BACKGROUND Stress CTP recently emerged as a potential strategy to combine the anatomic and functional evaluation of CAD in a single scan. METHODS A total of 100 consecutive symptomatic patients scheduled for ICA were prospectively enrolled. All patients underwent rest coronary computed tomography angiography (CTA) followed by stress static CTP with a whole-heart coverage CT scanner (Revolution CT, GE Healthcare, Milwaukee, Wisconsin). Diagnostic accuracy and overall effective dose were assessed and compared versus those of ICA and invasive FFR. RESULTS The prevalence of obstructive CAD and functionally significant CAD were 69% and 44%, respectively. Coronary CTA alone demonstrated a per-vessel and per-patient sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of 98%, 76%, 99%, 63%, and 83% and of 98%, 54%, 96%, 68%, and 76%, respectively. Combining coronary CTA with stress CTP, per-vessel and per-patient sensitivity, specificity, negative predictive value, positive predictive value, and accuracy were 91%, 94%, 96%, 86%, and 93% and 98%, 83%, 98%, 86%, and 91%, with a significant improvement in specificity, positive predictive value, and accuracy in both models. The mean effective dose for coronary CTA and stress CTP were 2.8  1.4 mSv and 2.5  1.1 mSv. CONCLUSIONS The inclusion of stress CTP for the evaluation of patients with an intermediate to high risk for CAD is feasible and improved the diagnostic performance of coronary CTA for detecting functionally significant CAD.
创建时间:
2019-09-15
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作