Performance of Integrated Near-Infrared Spectroscopy and Intravascular Ultrasound (NIRS-IVUS) System against Quantitative Flow Ratio (QFR)

Author:

Dobrolińska Magdalena M.ORCID,Gąsior Paweł M.ORCID,Pociask ElżbietaORCID,Smolka Grzegorz,Ochala Andrzej,Wojakowski WojciechORCID,Roleder Tomasz

Abstract

Quantitative flow ratio (QFR) is a new opportunity to analyze functional stenosis during invasive coronary angiography. Together with a well-known intravascular ultrasound (IVUS) and a new player in the field, near-infrared spectroscopy (NIRS), it is gaining a lot of interest. The aim of the study was to compare QFR results with integrated IVUS-NIRS results acquired simultaneously in the same coronary lesion. We retrospectively enrolled 66 patients in whom 66 coronary lesions were assessed by NIRS-IVUS and QFR. Lesions were divided into two groups based on QFR results as QFR-positive group (QFR ≤ 0.8) or QFR-negative group (QFR > 0.8). Based on ROC curve analysis, the best cut-off values of minimal lumen area (MLA), minimal lumen diameter (MLD) and percent diameter stenosis for predicting QFR ≤ 80 were 2.4 (AUC 0.733, 95%CI 0.61, 0.834), 1.6 (AUC 0.768, 95%CI 0.634, 0.872) and 59.5 (AUC 0.918, 95%CI 0.824, 0.971), respectively. In QFR-positive lesions, the maxLCBI4mm was significantly higher than in QFR-negative lesions (450.12 ± 251.0 vs. 329.47 ± 191.14, p = 0.046). The major finding of the present study is that values of IVUS-MLA, IVUS-MLD and percent diameter stenosis show a good efficiency in predicting QFR ≤ 0.80. Moreover, QFR-positive lesions are characterized by higher maxLCBI4mm as compared to the QFR-negative group.

Publisher

MDPI AG

Subject

Clinical Biochemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3