PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 17, 2022Scientific Reports57 citationsOpen Access

Accuracy of vascular tortuosity measures using computational modelling

VKVishesh KashyapRGRamtin GharleghiDLDarson Dezheng Li

Structured PICO

Which coronary tortuosity metric correlates best with low time-averaged wall shear stress in patients without coronary artery disease?

P
Population
127 patients without coronary artery disease evaluated using Computed Tomography Coronary Angiogram (CTCA) data.
I
Intervention
Curvature-based tortuosity metrics (average absolute-curvature, root-mean-squared curvature, and average squared-derivative-curvature) applied to the left main coronary artery bifurcation and its branches.
C
Comparator
Tortuosity index (non-curvature-based measure).
O
Outcome
Correlation with the percentage of vessel area showing a < 0.4 Pa time-averaged wall shear stress (TAWSS) modelled using computational fluid dynamics.surrogate

Curvature-based tortuosity measures, specifically average-absolute-curvature, significantly outperform the traditional tortuosity index in correlating with low wall shear stress, providing a better benchmark for assessing coronary disease risk.

Abstract

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.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Kashyap et al. (2022) studied this question.

synapsesocial.com/papers/69d7c55005ee2ba81dbedd17https://doi.org/10.1038/s41598-022-04796-w
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Clinical Implication of Coronary Tortuosity in Patients with Coronary Artery Disease2011 · 114 citations
  2. 2Importance of left anterior descending coronary artery curvature in determining cross-sectional plaque distribution assessed by intravascular ultrasound1998 · 25 citations
  3. 3Coronary Artery Tortuosity in Spontaneous Coronary Artery Dissection2014 · 317 citations
  4. 4Hemodynamic Shear Stress and Its Role in Atherosclerosis1999 · 3,648 citations
  5. 5Proceedings of IEEE International Conference on Computer Vision1995 · 2,323 citations