AUTHOR=Zhang Jing , Zhao Shuo , Hou Xunyao , Wang Xinyao , Guo Yunliang , Wang Ximing 

TITLE=Association between carotid plaque calcification and clinical outcomes of symptomatic cerebral small vessel disease

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1628353

DOI=10.3389/fneur.2025.1628353

ISSN=1664-2295

ABSTRACT=ObjectiveAtherosclerosis is the most common pathological change of cerebral small vessel disease (CSVD). This study aimed to investigate correlations between carotid atherosclerotic calcification and clinical outcomes of symptomatic CSVD.MethodsWe retrospectively evaluated 210 symptomatic CSVD patients who underwent carotid computed tomography angiography (CTA) and brain magnetic resonance imaging (MRI). Clinical outcomes were evaluated using modified Rankin Scale (mRS) at 90 days after acute event. The presence and characteristics of carotid calcification (including size, number and location), carotid plaque burden and CSVD markers were analyzed. Logistic regression analysis was used to explore associations between carotid calcification and CSVD outcomes. Key confounding variables (age, sex, hypertension, diabetes mellitus, hyperlipidemia, coronary heart disease, smoking history, drinking history, ulceration, positive remodeling and positive soft plaque) were adjusted in multivariate analysis. The areas under the curve (AUC) of receiver operating characteristic (ROC) curves were used to analyze predictive performance of various radiological variables for CSVD outcomes.ResultsA total of 129 patients with poor outcomes and 81 with good outcomes were analyzed. The incidence of calcification plaque in poor outcome group was higher than those in good outcome group (p = 0.001). Logistic regression found that the presence of calcification, surface calcification, multiple calcifications, thick/mixed calcifications, carotid stenosis degree and total CSVD score were associated with adverse outcomes in symptomatic CSVD before and after adjusting for confounding factors (all p < 0.05). ROC analysis showed that the prediction model with integrated carotid calcification exhibited enhanced performance with a sensitivity of 75.19% and specificity of 70.37% (AUC = 0.752, p < 0.001).ConclusionCarotid calcification characteristics were associated with clinical outcomes of symptomatic CSVD, which could be used as predictive indicators of CSVD outcomes.