Association between intracranial vessel calcifications, structural brain damage, and cognitive impairment after minor strokes: a prospective study.

Abstract

Vascular calcifications are a hallmark of atherosclerosis, and in the coronary arteries are routinely used as a prognostic marker. Calcifications of intracranial vessels (ICC) are frequently observed on non-contrast CT (NCCT) and their effect on post-stroke cognitive impairment (PSCI) remains unclear. Our aim was to explore the association of ICC with prospective long-term cognitive function and advanced MRI-measures in a large prospective cohort of cognitively intact mild stroke survivors. Data from the Tel-Aviv brain acute stroke cohort (TABASCO) study [ClinicalTrials.gov #NCT01926691] were analyzed. This prospective cohort study (n = 575) aimed to identify predictors of PSCI, in cognitively intact mild stroke survivors. A quantitative assessment of the intracranial calcium content - The ICC score (ICCS) was calculated semi-automatically on NCCT using a validated calcium quantification application. Participants underwent a 3 T-MRI and prospective comprehensive cognitive clinical and laboratory assessments at enrollment, 6, 12, and 24-months. Data were available for 531 participants (67.4 years, 59.5% males). The incidence of PSCI at two-years doubled in the high ICCS group (26% vs. 13.7%, p < 0.001). The high ICCS group had significantly greater small-vessel-disease (SVD) tissue changes and reduced microstructural-integrity assessed by Diffusion-Tensor-Imaging (DTI) maps (p < 0.05 for all). In multivariate analysis, a higher ICCS was independently associated with brain atrophy manifested by lower normalized white and gray matter, hippocampal and thalamic volumes (β = -0.178, β = -0.2, β = -0.137, β = -0.157; p < 0.05) and independently predicted PSCI (OR 1.83, 95%CI 1.01-3.35). Our findings suggest that the ICCS, which is a simple and readily available imaging marker on NCCT, is associated with brain atrophy, microstructural damage, the extent of SVD, and may predict PSCI. This finding has implications for identifying individuals at risk for PSCI and implementing targeted interventions to mitigate this risk.