Geometric determinants of local hemodynamics in severe carotid artery stenosis
Dara Azar1, William M Torres2, Lindsey A Davis3
1Biomedical Engineering Program, College of Engineering and Computing, University of South Carolina, Columbia, SC, USA.
Insights
Severe carotid artery stenosis (CAS) treatment decisions can be improved. Beyond stenosis degree, multipoint geometric metrics from CT angiography enhance predictions of blood flow stress, aiding stroke risk assessment.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Cardiovascular Science
Background:
- Severe carotid artery stenosis (CAS) often necessitates carotid endarterectomy (CEA) to reduce stroke risk.
- Current guidelines for CEA decision-making rely heavily on the degree of lumen diameter loss (stenosis percentage).
- The degree of stenosis is presumed to correlate with wall shear stress (WSS) and stroke risk, but this relationship may be incomplete.
Purpose of the Study:
- To investigate the influence of plaque morphology and local vessel geometry on hemodynamics in severe CAS.
- To explore geometric descriptors beyond the degree of stenosis for improved hemodynamic prediction.
- To assess if multipoint geometric metrics can enhance the prediction of shear stress-based risk factors.
Main Methods:
- Retrospective analysis of 50 patients with severe internal CAS (>60% stenosis) using pre-CEA computed tomography angiography (CTA) images.
- Extraction of multipoint geometric metrics characterizing the stenosed arterial region.
- Computational fluid dynamics (CFD) simulations to quantify local WSS and other hemodynamic parameters.
- Correlation and regression analyses to link geometric and hemodynamic metrics, including patient stratification by stenosis degree.
Main Results:
- The degree of stenosis alone is insufficient for comprehensive hemodynamic prediction in severe CAS.
- Multipoint geometric metrics derived from CTA provide additional valuable information about local hemodynamics.
- Incorporating these geometric descriptors significantly enhances the prediction of WSS-based metrics.
Conclusions:
- Geometric factors beyond simple stenosis percentage play a crucial role in determining hemodynamics in severe CAS.
- Readily available multipoint geometric metrics from CTA can improve the prediction of shear stress and associated stroke risk.
- These findings suggest a refinement of current criteria for guiding CEA interventions.
Abstract:
In cases of severe carotid artery stenosis (CAS), carotid endarterectomy (CEA) is performed to recover lumen patency and alleviate stroke risk. Under current guidelines, the decision to surgically intervene relies primarily on the percent loss of native arterial lumen diameter within the stenotic region (i.e. the degree of stenosis). An underlying premise is that the degree of stenosis modulates flow-induced wall shear stress elevations at the lesion site, and thus indicates plaque rupture potential and stroke risk. Here, we conduct a retrospective study on pre-CEA computed tomography angiography (CTA) images from 50 patients with severe internal CAS (>60% stenosis) to better understand the influence of plaque and local vessel geometry on local hemodynamics, with geometrical descriptors that extend beyond the degree of stenosis. We first processed CTA images to define a set of multipoint geometric metrics characterizing the stenosed region, and next performed computational fluid dynamics simulations to quantify local wall shear stress and associated hemodynamic metrics. Correlation and regression analyses were used to relate obtained geometric and hemodynamic metrics, with inclusion of patient sub-classification based on the degree of stenosis. Our results suggest that in the context of severe CAS, prediction of shear stress-based metrics can be enhanced by consideration of readily available, multipoint geometric metrics in addition to the degree of stenosis.
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