The Use of Carotid Web Angioarchitecture in Stratification of Stroke Risk

Introduction: We aim to validate a carotid web (CW) angioarchitecture-based stroke risk stratification assessment with a larger cohort of patients with incidentally found asymptomatic CW.

Methods: A retrospective analysis of our electronic medical record database identified all patients with a diagnosis of CW from 2017-2024 at our institution. We included symptomatic patients and those with asymptomatic carotid webs, meaning patients with incidentally found webs and no history of stroke or transient ischemic attack (TIA). Patient charts were reviewed for demographics, imaging, comorbidities, hospital course, and incidence of stroke after diagnosis of an asymptomatic carotid web. All angles were measured as described in our previous work on a sagittal reconstruction of CTA imaging of the neck in which the common carotid artery (CCA), external carotid artery (ECA), and ICA could be well visualized, along with the CW itself. A standard logistic regression was performed to evaluate the association between the number of high-risk angles and stroke risk.

Results: 26 asymptomatic and nine symptomatic patients were identified. Patients were categorized as having 0, 1, or 2+ high-risk angle values. A standard logistic regression was performed to evaluate the association between the number of high-risk angles and stroke risk. Patients with more high-risk angles had a markedly higher risk of stroke (OR = 5.91, 95% CI: [4.25, 8.24]). The probability of stroke increased with the number of high-risk angles: patients with 2+ high-risk angles (83.4%) had the highest stroke probability compared to those with 0 (2.8%) or 1 (27.7%) high-risk angles. In the asymptomatic cohort, mean angles all fell below the high-risk threshold values. In the symptomatic cohort, mean angles were above the high-risk threshold values, whereas the mean CPT (53.6°) angle fell below the cut-off value for designation as a high-risk angle.

Conclusion : Given the successful stratification of CWs into high and low-risk groups in this study, the utilization of geometric CW parameters may play a crucial role in improvement of patient selection for intervention in patients with an incidental diagnosis of CW.