Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance.

Cardiology journal Pub Date : 2024-01-01 Epub Date: 2023-11-15 DOI:10.5603/cj.90744
Weili Pan, Wenjuan Wei, Yumeng Hu, Li Feng, Yongkui Ren, Xinsheng Li, Changling Li, Jun Jiang, Jianping Xiang, Xiaochang Leng, Da Yin
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Abstract

Background: This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function.

Methods: The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results: Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson's correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of -0.037 (limits of agreement: -0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78).

Conclusions: This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis.

一种新的基于光学相干层析的分数血流储备算法用于评估冠状动脉狭窄意义的诊断准确性。
背景:本研究旨在介绍一种新的光学相干层析衍生的分数血流储备(FFR)计算方法,并评估该算法在评估生理功能方面的诊断性能。方法:采用冠状动脉光学相干断层成像与血管造影相融合的方法,生成一种新的FFR算法(AccuFFRoct)来评估冠状动脉狭窄的功能性缺血。本研究共纳入34例连续患者,使用AccuFFRoct计算这些患者的FFR。以线测FFR作为参考标准,我们通过准确性、敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)来评估我们方法的性能。结果:AccuFFRoct识别血流动力学显著性冠状动脉狭窄的血管准确性、敏感性、特异性、PPV和NPV分别为93.8%、94.7%、92.3%、94.7%和92.3%。AccuFFRoct与FFR具有良好的相关性(Pearson相关系数r = 0.80, p < 0.001)。Bland-Altman分析显示平均差值为-0.037(一致性限:-0.189至0.115)。AccuFFRoct识别生理显著性狭窄的受者-操作特征曲线下面积(AUC)为0.94,高于最小管腔面积(MLA, AUC = 0.91),显著高于内径狭窄(%DS, AUC = 0.78)。结论:本临床研究表明,当使用有创FFR测量作为参考时,AccuFFRoct可用于临床实施。它可以提供重要的见解冠状动脉成像优于目前的方法基于冠状动脉狭窄的程度。
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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