Fractional flow reserve calculation optimized by myocardial computed tomography perfusion information.

IF 2.3 2区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Quantitative Imaging in Medicine and Surgery Pub Date : 2025-09-01 Epub Date: 2025-08-19 DOI:10.21037/qims-24-2172
Peiming Qin, Yan Yi, Cheng Xu, Limiao Zou, Fenggang Jia, Jian Guo, Ming Wang, Yan Zhang, Ziquan Wang, Pei Dong, Dijia Wu, Xiaodong Wang, Yining Wang
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引用次数: 0

Abstract

Background: Current computed tomography angiography-derived fractional flow reserve (CT-FFR) diagnosis leaves room for improvement in diagnosing coronary heart disease. In this study, the computed fluid dynamics boundary condition optimization method was used to calculate CT-FFR aiming to improve the diagnostic accuracy of CT-FFR for coronary heart disease.

Methods: The two enhancement approaches are as follows: (A) inlet flow optimization, which involves determining the total coronary inlet flow rate by summing the myocardial blood flow (MBF) across the entire left ventricular myocardium; and (B) inlet & outlet flow optimization: building upon method A, where the outlet flow of coronary artery branches is calculated through blood supply area analysis.

Results: A total of 100 fractional flow reserve pressure guide wire measurement sites from 47 cases were used to evaluate the above two methods comparing with the traditional computed fluid dynamics method without computed tomography perfusion (CTP) images. In traditional method, the accuracy was 88%, the sensitivity was 91.4% (95% confidence interval: 75.8-97.7%), and the specificity was 86.2% (95% confidence interval: 74.8-93.1%). In Method A, the accuracy improved by 5% (93%), the sensitivity remained unchanged (91.4%, 95% confidence interval: 75.8-97.7%), and the specificity increased by 7.6% (93.8%, 95% confidence interval: 84.2-98%). In Method B, the accuracy increased by 6% (94%), the sensitivity increased to 100% (95% confidence interval: 87.7-100%), and the specificity increased by 4.8% (94%, 95% confidence interval: 80.3-96.2%).

Conclusions: The computed fluid dynamics calculation, guided by MBF values from stress CTP imaging, helps enhance the consistency between CT-FFR calculation and invasive fractional flow reserve measurements.

Abstract Image

Abstract Image

Abstract Image

利用心肌ct灌注信息优化分流储备计算。
背景:目前的CT-FFR诊断在冠心病的诊断中仍有提高的空间。本研究采用计算流体力学边界条件优化方法计算CT-FFR,旨在提高CT-FFR对冠心病的诊断准确性。方法:两种增强方法:(A)入口血流优化,通过对整个左心室心肌的心肌血流量(MBF)求和来确定总冠状动脉入口血流速率;(B)进出口流量优化:以方法A为基础,通过血供面积分析计算冠状动脉分支出口流量。结果:选取47例患者的100个分流储备压力导丝测量点,与传统的不含ct灌注(CTP)图像的计算流体力学方法进行比较,对上述两种方法进行评价。传统方法的准确率为88%,灵敏度为91.4%(95%可信区间:75.8 ~ 97.7%),特异性为86.2%(95%可信区间:74.8 ~ 93.1%)。方法A的准确度提高了5%(93%),灵敏度保持不变(91.4%,95%可信区间:75.8 ~ 97.7%),特异性提高了7.6%(93.8%,95%可信区间:84.2 ~ 98%)。方法B准确度提高6%(94%),灵敏度提高到100%(95%可信区间:87.7 ~ 100%),特异性提高4.8%(94%,95%可信区间:80.3 ~ 96.2%)。结论:在应力CTP成像MBF值的指导下,计算流体动力学计算有助于增强CT-FFR计算与有创分流储量测量的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Quantitative Imaging in Medicine and Surgery
Quantitative Imaging in Medicine and Surgery Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
4.20
自引率
17.90%
发文量
252
期刊介绍: Information not localized
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