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Accuracy of vascular tortuosity measures using computational modelling.

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.

SUBMITTER: Kashyap V

PROVIDER: S-EPMC8764056 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Accuracy of vascular tortuosity measures using computational modelling.

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