Gosling, R.C. orcid.org/0000-0001-7465-3563, Gunn, E., Wei, H.L. orcid.org/0000-0002-4704-7346 et al. (7 more authors) (2022) Incorporating clinical parameters to improve the accuracy of angiography-derived computed fractional flow reserve. European Heart Journal - Digital Health, 3 (3). pp. 481-488. ISSN 2634-3916
Abstract
Aims Angiography-derived fractional flow reserve (angio-FFR) permits physiological lesion assessment without the need for an invasive pressure wire or induction of hyperaemia. However, accuracy is limited by assumptions made when defining the distal boundary, namely coronary microvascular resistance (CMVR). We sought to determine whether machine learning (ML) techniques could provide a patient-specific estimate of CMVR and therefore improve the accuracy of angio-FFR.
Methods and results Patients with chronic coronary syndromes underwent coronary angiography with FFR assessment. Vessel-specific CMVR was computed using a three-dimensional computational fluid dynamics simulation with invasively measured proximal and distal pressures applied as boundary conditions. Predictive models were created using non-linear autoregressive moving average with exogenous input (NARMAX) modelling with computed CMVR as the dependent variable. Angio-FFR (VIRTUheart™) was computed using previously described methods. Three simulations were run: using a generic CMVR value (Model A); using ML-predicted CMVR based upon simple clinical data (Model B); and using ML-predicted CMVR also incorporating echocardiographic data (Model C). The diagnostic (FFR ≤ or >0.80) and absolute accuracies of these models were compared. Eighty-four patients underwent coronary angiography with FFR assessment in 157 vessels. The mean measured FFR was 0.79 (±0.15). The diagnostic and absolute accuracies of each personalized model were: (A) 73% and ±0.10; (B) 81% and ±0.07; and (C) 89% and ±0.05, P < 0.001.
Conclusion The accuracy of angio-FFR was dependent in part upon CMVR estimation. Personalization of CMVR from standard clinical data resulted in a significant reduction in angio-FFR error.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Stable angina; Fractional flow reserve; Transthoracic echocardiogram |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) The University of Sheffield > Sheffield Teaching Hospitals |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/H00453X/1 ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL EP/I011056/1 WELLCOME TRUST (THE) 214567/Z/18/Z British Heart Foundation FS/16/48/32306 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 Oct 2022 14:14 |
Last Modified: | 24 Jan 2025 17:43 |
Status: | Published |
Publisher: | Oxford University Press (OUP) |
Refereed: | Yes |
Identification Number: | 10.1093/ehjdh/ztac045 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:191309 |