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A novel CFD-based computed index of microcirculatory resistance (IMR) derived from coronary angiography to assess coronary microcirculation.

Authors :
Jiang J
Li C
Hu Y
Li C
He J
Leng X
Xiang J
Ge J
Wang J
Source :
Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2022 Jun; Vol. 221, pp. 106897. Date of Electronic Publication: 2022 May 18.
Publication Year :
2022

Abstract

Objectives: This study sought to present a novel approach for computation of the index of microcirculatory resistance (IMR) and to evaluate its diagnostic performance.<br />Background: IMR is a quantitative assessment to identify coronary microvascular dysfunction. However, its clinical use remains extremely limited. Calculation of IMR from coronary angiography images may increase the utility of coronary microvasculature assessment.<br />Methods: 203 patients with 203 vessels were included in this study. Physiology measurements were obtained with pressure-wire in the whole cohort. The computational fluid dynamics (CFD)-based AccuIMR was computed and evaluated in a blinded fashion using wire-based IMR as the reference standard.<br />Results: The overall diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of AccuIMR for detecting coronary microvascular disease were 91.1% (95% CI: 86.4% to 94.7%), 89.4% (95% CI: 80.9% to 95.0%), 92.4% (95% CI: 86.0% to 96.5%), 89.4% (95% CI: 81.8% to 94.1%), and 92.2% (95% CI: 86.7% to 95.8%), respectively. The correlation coefficient equaled to 0.81 (p < 0.001) between AccuIMR and wire-based IMR with the receiver-operating curve had area under the curve of 0.924 (95% CI: 0.878 to 0.956).<br />Conclusions: AccuIMR is a novel pressure-wire free approach to assess coronary microvascular disease with great diagnostic performance, which can be a valid, efficient, and cost-reducing tool to provide an easier routine assessment of coronary microcirculation.<br />Competing Interests: Conflict of Interest The authors have no conflict of interest to declare that are relevant to the content of this article.<br /> (Copyright © 2022 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1872-7565
Volume :
221
Database :
MEDLINE
Journal :
Computer methods and programs in biomedicine
Publication Type :
Academic Journal
Accession number :
35636354
Full Text :
https://doi.org/10.1016/j.cmpb.2022.106897