Tufaro, V;
Torii, R;
Erdogan, E;
Kitslaar, P;
Koo, BK;
Rakhit, R;
Karamasis, GV;
... Bourantas, CV; + view all
(2022)
An automated software for real-time quantification of wall shear stress distribution in quantitative coronary angiography data.
International Journal of Cardiology
, 357
pp. 14-19.
10.1016/j.ijcard.2022.03.022.
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Abstract
Background: Wall shear stress (WSS) estimated in 3D-quantitative coronary angiography (QCA) models appears to provide useful prognostic information and identifies high-risk patients and lesions. However, conventional computational fluid dynamics (CFD) analysis is cumbersome limiting its application in the clinical arena. This report introduces a user-friendly software that allows real-time WSS computation and examines its reproducibility and accuracy in assessing WSS distribution against conventional CFD analysis. Methods: From a registry of 414 patients with borderline negative fractional flow reserve (0.81–0.85), 100 lesions were randomly selected. 3D-QCA and CFD analysis were performed using the conventional approach and the novel CAAS Workstation WSS software, and QCA as well as WSS estimations of the two approaches were compared. The reproducibility of the two methodologies was evaluated in a subgroup of 50 lesions. Results: A good agreement was noted between the conventional approach and the novel software for 3D-QCA metrics (ICC range: 0.73–0-93) and maximum WSS at the lesion site (ICC: 0.88). Both methodologies had a high reproducibility in assessing lesion severity (ICC range: 0.83–0.97 for the conventional approach; 0.84–0.96 for the CAAS Workstation WSS software) and WSS distribution (ICC: 0.85–0.89 and 0.83–0.87, respectively). Simulation time was significantly shorter using the CAAS Workstation WSS software compared to the conventional approach (4.13 ± 0.59 min vs 23.14 ± 2.56 min, p < 0.001). Conclusion: CAAS Workstation WSS software is fast, reproducible, and accurate in assessing WSS distribution. Therefore, this software is expected to enable the broad use of WSS metrics in the clinical arena to identify high-risk lesions and vulnerable patients.
| Type: | Article |
|---|---|
| Title: | An automated software for real-time quantification of wall shear stress distribution in quantitative coronary angiography data |
| Location: | Netherlands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ijcard.2022.03.022 |
| Publisher version: | https://doi.org/10.1016/j.ijcard.2022.03.022 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Cardiac & Cardiovascular Systems, Cardiovascular System & Cardiology, Vulnerable plaque, Computational fluid dynamics, Wall shear stress, IN-VIVO, PLAQUE, PREDICTION, ATHEROSCLEROSIS, PROGRESSION, EVENTS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10207424 |
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