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Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics

Neeraj Kavan Chakshu, Jason Carson, Igor Sazonov Orcid Logo, Perumal Nithiarasu Orcid Logo

International Journal for Numerical Methods in Biomedical Engineering, Volume: 38, Issue: 3

Swansea University Authors: Neeraj Kavan Chakshu, Jason Carson, Igor Sazonov Orcid Logo, Perumal Nithiarasu Orcid Logo

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DOI (Published version): 10.1002/cnm.3559

Abstract

Fractional flow reserve (FFR) provides the functional relevance of coronary atheroma. The FFR-guided strategy has been shown to reduce unnecessary stenting, improve overall health outcome, and to be cost-saving. The non-invasive, coronary Computerised Tomography (CT) angiography-derived FFR (cFFR) i...

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Published in: International Journal for Numerical Methods in Biomedical Engineering
ISSN: 2040-7939 2040-7947
Published: Wiley 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa58926
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last_indexed 2023-01-11T14:39:51Z
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spelling 2022-10-31T19:16:20.2717522 v2 58926 2021-12-06 Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics e21c85ee9062e9be0fff8ab9d77b14d7 Neeraj Kavan Chakshu Neeraj Kavan Chakshu true false ced1a1a2f38e4b283f16f138ce1131c5 Jason Carson Jason Carson true false 05a507952e26462561085fb6f62c8897 0000-0001-6685-2351 Igor Sazonov Igor Sazonov true false 3b28bf59358fc2b9bd9a46897dbfc92d 0000-0002-4901-2980 Perumal Nithiarasu Perumal Nithiarasu true false 2021-12-06 ACEM Fractional flow reserve (FFR) provides the functional relevance of coronary atheroma. The FFR-guided strategy has been shown to reduce unnecessary stenting, improve overall health outcome, and to be cost-saving. The non-invasive, coronary Computerised Tomography (CT) angiography-derived FFR (cFFR) is an emerging method in reducing invasive catheter based measurements. This CFD-based method is laborious as it requires expertise in multidisciplinary analysis of combining image analysis and computational mechanics. In this work, we present a rapid method, powered by unsupervised learning, to automatically calculate cFFR from CT scans without manual intervention. Journal Article International Journal for Numerical Methods in Biomedical Engineering 38 3 Wiley 2040-7939 2040-7947 Fractional Flow Reserve, Vessel Segmentation, Passive digital twin, CFD, Coronary system, Computervision, Automation 11 3 2022 2022-03-11 10.1002/cnm.3559 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University SU Library paid the OA fee (TA Institutional Deal) Global Challenges Research Fund. Grant Number: RB1819APM003SWANKARU; Medical Research Council. Grant Number: MR/S004076/1; College of Engineering, Swansea University 2022-10-31T19:16:20.2717522 2021-12-06T15:58:10.1147787 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Neeraj Kavan Chakshu 1 Jason Carson 2 Igor Sazonov 0000-0001-6685-2351 3 Perumal Nithiarasu 0000-0002-4901-2980 4 58926__21973__294430ffeda643748d5530ece98ad356.pdf 58926.pdf 2021-12-30T17:14:27.9877679 Output 2151101 application/pdf Version of Record true © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License true eng http://creativecommons.org/licenses/by/4.0/
title Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
spellingShingle Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
Neeraj Kavan Chakshu
Jason Carson
Igor Sazonov
Perumal Nithiarasu
title_short Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
title_full Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
title_fullStr Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
title_full_unstemmed Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
title_sort Automating fractional flow reserve (FFR) calculation from CT scans: A rapid workflow using unsupervised learning and computational fluid dynamics
author_id_str_mv e21c85ee9062e9be0fff8ab9d77b14d7
ced1a1a2f38e4b283f16f138ce1131c5
05a507952e26462561085fb6f62c8897
3b28bf59358fc2b9bd9a46897dbfc92d
author_id_fullname_str_mv e21c85ee9062e9be0fff8ab9d77b14d7_***_Neeraj Kavan Chakshu
ced1a1a2f38e4b283f16f138ce1131c5_***_Jason Carson
05a507952e26462561085fb6f62c8897_***_Igor Sazonov
3b28bf59358fc2b9bd9a46897dbfc92d_***_Perumal Nithiarasu
author Neeraj Kavan Chakshu
Jason Carson
Igor Sazonov
Perumal Nithiarasu
author2 Neeraj Kavan Chakshu
Jason Carson
Igor Sazonov
Perumal Nithiarasu
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container_title International Journal for Numerical Methods in Biomedical Engineering
container_volume 38
container_issue 3
publishDate 2022
institution Swansea University
issn 2040-7939
2040-7947
doi_str_mv 10.1002/cnm.3559
publisher Wiley
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
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description Fractional flow reserve (FFR) provides the functional relevance of coronary atheroma. The FFR-guided strategy has been shown to reduce unnecessary stenting, improve overall health outcome, and to be cost-saving. The non-invasive, coronary Computerised Tomography (CT) angiography-derived FFR (cFFR) is an emerging method in reducing invasive catheter based measurements. This CFD-based method is laborious as it requires expertise in multidisciplinary analysis of combining image analysis and computational mechanics. In this work, we present a rapid method, powered by unsupervised learning, to automatically calculate cFFR from CT scans without manual intervention.
published_date 2022-03-11T02:27:05Z
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