动态CT灌注成像在冠状动脉疾病患者中的血流储备测量。

Radiology advances Pub Date : 2024-11-25 eCollection Date: 2024-10-01 DOI:10.1093/radadv/umae031
Aaron So, Ki Seok Choo, Ji Won Lee, Yun-Hyeon Kim, Mustafa Haider, Mahmud Hasan, Serag El-Ganga, Akshaye Goela, Patrick Teefy, Yeon Hyeon Choe
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引用次数: 0

摘要

目的:目的是评估一种新型的CT动态血管成像(CT- dai)算法在冠状动脉疾病(CAD)患者中快速测量分数血流储备(FFR)的准确性。材料与方法:回顾性研究14例CAD患者(年龄58.5±10.6岁,男性11例),行双源CT应激动态CT心肌灌注扫描。纳入的患者在灌注图像中有邻近狭窄的可分析的冠状动脉近端和远端段,并对该狭窄进行了相应的有创导管FFR测量。使用基于CT-DAI算法的内部软件,根据从应激心肌灌注图像中获得的病变前后冠状动脉时间增强曲线计算FFR。然后将CT-DAI得出的FFR值与相应的导管有创FFR值进行比较。结果:CT-DAI衍生的FFR值与14例患者的所有15条冠状动脉的有创FFR值一致,每条血管和每例患者的诊断准确率为100%。CT-DAI法测得的FFR (M = 0.768, SD = 0.156)与有创导管法测得的FFR (M = 0.796, SD = 0.149)呈良好的线性相关(R = 0.910, P= 0.655)。Bland-Altman分析未发现显著的比例偏倚。结论:新的CT- dai算法可以直接从动态CT心肌灌注图像中可靠地计算冠状动脉狭窄的FFR,便于CAD患者心外膜冠状动脉狭窄的快速现场血流动力学评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractional flow reserve measurement using dynamic CT perfusion imaging in patients with coronary artery disease.

Purposes: The objective was to evaluate the accuracy of a novel CT dynamic angiographic imaging (CT-DAI) algorithm for rapid fractional flow reserve (FFR) measurement in patients with coronary artery disease (CAD).

Materials and methods: This retrospective study included 14 patients (age 58.5 ± 10.6 years, 11 males) with CAD who underwent stress dynamic CT myocardial perfusion scanning with a dual-source CT scanner. The included patients had analyzable proximal and distal coronary artery segments adjacent to the stenosis in the perfusion images and had corresponding invasive catheter-based FFR measurements for that stenosis. An in-house software based on the CT-DAI algorithm was used to compute FFR using the pre- and post- lesion coronary time-enhancement curves obtained from the stress myocardial perfusion images. The CT-DAI derived FFR values were then compared to the corresponding catheter-based invasive FFR values. A coronary artery stenosis was considered functionally significant for FFR value <0.8.

Results: The CT-DAI derived FFR values were in agreement with the invasive FFR values in all 15 coronary arteries in 14 patients, resulting in 100% per-vessel and per-patient diagnostic accuracy. FFR derived using CT-DAI (M = 0.768, SD = 0.156) showed an excellent linear correlation (R = 0.910, P < .001) and statistical indifference (P= .655) with that measured using invasive catheter-based method (M = 0.796, SD = 0.149). Bland-Altman analysis showed no significant proportional bias.

Conclusion: The novel CT-DAI algorithm can reliably compute FFR across a coronary artery stenosis directly from dynamic CT myocardial perfusion images, facilitating rapid on-site hemodynamic assessment of the epicardial coronary artery stenosis in patients with CAD.

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