Multimodal ultrasound-based morphological differences between symptomatic and asymptomatic carotid web.

OBJECTIVE

We aimed to investigate the differences between symptomatic and asymptomatic carotid webs (CWs) using clinical and ultrasound morphological features and identify potential risk factors for CW-associated ischemic stroke.

METHODS

We retrospectively recruited 45 patients diagnosed with CW between January 2021 and September 2024 using digital subtraction angiography or computed tomography angiography. Patients were categorized according to the occurrence of CW-associated stroke. Multimodal ultrasound was used to identify the morphological characteristics of the CWs, carotid stenosis rate and hemodynamic alterations. Binary-variable logistic regression was used to assess the high-risk ultrasound morphologic features of CW-induced ischemic stroke.

RESULTS

Forty-five patients with CWs were identified, of whom 15 had stroke-related symptomatic CWs. Symptomatic patients demonstrated higher hyperlipidemia prevalence, had greater web dimensions (length, 5.80 ± 1.64 vs. 4.41 ± 1.67 mm, p = 0.011; thickness, 1.88 ± 0.43 vs. 1.38 ± 0.39 mm, p < 0.001), and a higher prevalence of curved CW shape (80.0% vs. 43.3%, p = 0.044). CW-induced stenosis was more severe in the symptomatic group than in the asymptomatic group (46.35 ± 9.89% vs. 40.13 ± 11.44%), although the majority of the stenoses were mild (<50%). Hemodynamically, while flow velocities were comparable, symptomatic cases showed significantly lower resistance index (0.59 ± 0.10 vs. 0.65 ± 0.07, p = 0.02). Multivariate analysis identified CW length (OR = 2.10, 95% CI 1.08-4.06; p = 0.028), CW thickness (OR = 21.80, 95% CI 2.43-196.00; p = 0.006), and lower RI as independently associated factors of symptomatic CWs. ROC analysis yielded optimal cutoffs of >1.65 mm for thickness (AUC = 0.813), > 5.20 mm for length (AUC = 0.723), and ≤ 0.691 for RI (AUC = 0.698).

CONCLUSION

Symptomatic CWs exhibit distinct morphological and hemodynamic features than asymptomatic CWs. These ultrasound-detectable characteristics may help identify high-risk patients for stroke prevention.