# Relationship Between Carotid Artery Anatomy and Geometry and White Matter Hyperintensities and Accompanying Comorbid Factors

## TL;DR

This study finds that unusual shapes of carotid arteries are linked to brain imaging changes called white matter hyperintensities, which are tied to aging and vascular risks.

## Contribution

The study identifies carotid artery geometry as a novel independent risk factor for white matter hyperintensities.

## Key findings

- Increased carotid bifurcation and internal carotid artery angles are more common in individuals with white matter hyperintensities.
- Higher internal carotid artery tortuosity is associated with the presence of white matter hyperintensities.
- Age, hypertension, and stroke history are independent risk factors for white matter hyperintensities alongside carotid artery geometry.

## Abstract

White matter hyperintensities (WMH) are common brain imaging findings and are associated with aging and vascular risk factors. This study examined whether anatomical and geometrical features of the carotid arteries are related to the presence and severity of WMH. Using three-dimensional models derived from computed tomography angiography, we found that increased carotid bifurcation and internal carotid artery angles, as well as higher internal carotid artery tortuosity, were more frequent in individuals with WMH. These vascular features, together with age, hypertension, and prior stroke, were identified as independent risk factors for WMH. Our findings suggest that carotid artery geometry may play a role in the development and progression of WMH and could help identify individuals at higher risk.

Background/Objectives: This study aimed to investigate the relationship between carotid artery anatomy and geometry and white matter hyperintensities (WMH) and to determine whether it is a risk factor for the disease. Methods: The geometry and anatomy of both carotid arteries were evaluated with the three-dimensional vessel model obtained from the computed tomography angiography (CTA) data, and the segmentation software calculated the geometrical features of the arteries. In this model, vascular diameter, vascular cross-sectional area, carotid bifurcation and internal carotid artery (ICA) angles, as well as ICA tortuosity index (TI) measurements of the common carotid artery (CCA) and ICA were determined. Results: Compared with the non-WMH group, increased carotid bifurcation and ICA angle and higher ICA TI values were found in the WMH group (p < 0.001). In multivariate regression analysis, increased carotid bifurcation angle, higher ICA TI values, age, hypertension, and stroke history were identified as independent risk factors for the development of WMH (p < 0.05). In addition, age, carotid bifurcation angles and ICA angles were found to be associated with the severity of WMH (p < 0.05). Conclusions: Considering the vascular pathologies involved in the pathogenesis of WMH, identifying these risk factors may help determine individuals who are at an increased risk.