Cargando…
Accuracy of vascular tortuosity measures using computational modelling
Severe coronary tortuosity has previously been linked to low shear stresses at the luminal surface, yet this relationship is not fully understood. Several previous studies considered different tortuosity metrics when exploring its impact of on the wall shear stress (WSS), which has likely contribute...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764056/ https://www.ncbi.nlm.nih.gov/pubmed/35039557 http://dx.doi.org/10.1038/s41598-022-04796-w |
_version_ | 1784634079297142784 |
---|---|
author | Kashyap, Vishesh Gharleghi, Ramtin Li, Darson D. McGrath-Cadell, Lucy Graham, Robert M. Ellis, Chris Webster, Mark Beier, Susann |
author_facet | Kashyap, Vishesh Gharleghi, Ramtin Li, Darson D. McGrath-Cadell, Lucy Graham, Robert M. Ellis, Chris Webster, Mark Beier, Susann |
author_sort | Kashyap, Vishesh |
collection | PubMed |
description | Severe coronary tortuosity has previously been linked to low shear stresses at the luminal surface, yet this relationship is not fully understood. Several previous studies considered different tortuosity metrics when exploring its impact of on the wall shear stress (WSS), which has likely contributed to the ambiguous findings in the literature. Here, we aim to analyze different tortuosity metrics to determine a benchmark for the highest correlating metric with low time-averaged WSS (TAWSS). Using Computed Tomography Coronary Angiogram (CTCA) data from 127 patients without coronary artery disease, we applied all previously used tortuosity metrics to the left main coronary artery bifurcation, and to its left anterior descending and left circumflex branches, before modelling their TAWSS using computational fluid dynamics (CFD). The tortuosity measures included tortuosity index, average absolute-curvature, root-mean-squared (RMS) curvature, and average squared-derivative-curvature. Each tortuosity measure was then correlated with the percentage of vessel area that showed a < 0.4 Pa TAWSS, a threshold associated with altered endothelial cell cytoarchitecture and potentially higher disease risk. Our results showed a stronger correlation between curvature-based versus non-curvature-based tortuosity measures and low TAWSS, with the average-absolute-curvature showing the highest coefficient of determination across all left main branches (p < 0.001), followed by the average-squared-derivative-curvature (p = 0.001), and RMS-curvature (p = 0.002). The tortuosity index, the most widely used measure in literature, showed no significant correlation to low TAWSS (p = 0.86). We thus recommend the use of average-absolute-curvature as a tortuosity measure for future studies. |
format | Online Article Text |
id | pubmed-8764056 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-87640562022-01-18 Accuracy of vascular tortuosity measures using computational modelling Kashyap, Vishesh Gharleghi, Ramtin Li, Darson D. McGrath-Cadell, Lucy Graham, Robert M. Ellis, Chris Webster, Mark Beier, Susann Sci Rep Article Severe coronary tortuosity has previously been linked to low shear stresses at the luminal surface, yet this relationship is not fully understood. Several previous studies considered different tortuosity metrics when exploring its impact of on the wall shear stress (WSS), which has likely contributed to the ambiguous findings in the literature. Here, we aim to analyze different tortuosity metrics to determine a benchmark for the highest correlating metric with low time-averaged WSS (TAWSS). Using Computed Tomography Coronary Angiogram (CTCA) data from 127 patients without coronary artery disease, we applied all previously used tortuosity metrics to the left main coronary artery bifurcation, and to its left anterior descending and left circumflex branches, before modelling their TAWSS using computational fluid dynamics (CFD). The tortuosity measures included tortuosity index, average absolute-curvature, root-mean-squared (RMS) curvature, and average squared-derivative-curvature. Each tortuosity measure was then correlated with the percentage of vessel area that showed a < 0.4 Pa TAWSS, a threshold associated with altered endothelial cell cytoarchitecture and potentially higher disease risk. Our results showed a stronger correlation between curvature-based versus non-curvature-based tortuosity measures and low TAWSS, with the average-absolute-curvature showing the highest coefficient of determination across all left main branches (p < 0.001), followed by the average-squared-derivative-curvature (p = 0.001), and RMS-curvature (p = 0.002). The tortuosity index, the most widely used measure in literature, showed no significant correlation to low TAWSS (p = 0.86). We thus recommend the use of average-absolute-curvature as a tortuosity measure for future studies. Nature Publishing Group UK 2022-01-17 /pmc/articles/PMC8764056/ /pubmed/35039557 http://dx.doi.org/10.1038/s41598-022-04796-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kashyap, Vishesh Gharleghi, Ramtin Li, Darson D. McGrath-Cadell, Lucy Graham, Robert M. Ellis, Chris Webster, Mark Beier, Susann Accuracy of vascular tortuosity measures using computational modelling |
title | Accuracy of vascular tortuosity measures using computational modelling |
title_full | Accuracy of vascular tortuosity measures using computational modelling |
title_fullStr | Accuracy of vascular tortuosity measures using computational modelling |
title_full_unstemmed | Accuracy of vascular tortuosity measures using computational modelling |
title_short | Accuracy of vascular tortuosity measures using computational modelling |
title_sort | accuracy of vascular tortuosity measures using computational modelling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764056/ https://www.ncbi.nlm.nih.gov/pubmed/35039557 http://dx.doi.org/10.1038/s41598-022-04796-w |
work_keys_str_mv | AT kashyapvishesh accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT gharleghiramtin accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT lidarsond accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT mcgrathcadelllucy accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT grahamrobertm accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT ellischris accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT webstermark accuracyofvasculartortuositymeasuresusingcomputationalmodelling AT beiersusann accuracyofvasculartortuositymeasuresusingcomputationalmodelling |