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Abstract Objective Although acute brain infarcts are common after surgical aortic valve replacement (SAVR), they are often unassociated with clinical stroke symptoms. The relationship between clinically “silent” infarcts and in‐hospital delirium remains uncertain; obscured, in part, by how infarcts have been traditionally summarized as global metrics, independent of location or structural consequence. We sought to determine if infarct location and related structural connectivity changes were associated with postoperative delirium after SAVR. Methods A secondary analysis of a randomized multicenter SAVR trial of embolic protection devices (NCT02389894) was conducted, excluding participants with clinical stroke or incomplete neuroimaging (N = 298; 39% female, 7% non‐White, 74 ± 7 years). Delirium during in‐hospital recovery was serially screened using the Confusion Assessment Method. Parcellation and tractography atlas‐based neuroimaging methods were used to determine infarct locations and cortical connectivity effects. Mixed‐effect, zero‐inflated gaussian modeling analyses, accounting for brain region‐specific infarct characteristics, were conducted to examine for differences within and between groups by delirium status and perioperative neuroprotection device strategy. Results 23.5% participants experienced postoperative delirium. Delirium was associated with significantly increased lesion volumes in the right cerebellum and temporal lobe white matter, while diffusion weighted imaging infarct‐related structural disconnection (DWI‐ISD) was observed in frontal and temporal lobe regions (p‐FDR

Background Cardiovascular risk factors are associated with cognitive decline and dementia. Magnetic resonance imaging provides sensitive measurement of brain morphology and vascular brain injury. However, associations of risk factors with brain magnetic resonance imaging findings have largely been studied in White participants. We investigated associations of race, ethnicity, and cardiovascular risk factors with brain morphology and white matter (WM) injury in a diverse population. Methods and Results In the Multi‐Ethnic Study of Atherosclerosis, measures were made in 2018 to 2019 of total brain volume, gray matter and WM volume, and WM injury, including WM hyperintensity volume and WM fractional anisotropy. We assessed cross‐sectional associations of race and ethnicity and of cardiovascular risk factors with magnetic resonance imaging measures. Magnetic resonance imaging data were complete in 1036 participants; 25% Black, 15% Chinese‐American, 19% Hispanic, and 41% White. Mean (SD) age was 72 (8) years and 53% were women. Although WM injury was greater in Black than in White participants in a minimally adjusted model, additional adjustment for cardiovascular risk factors and socioeconomic status each attenuated this association, rendering it nonsignificant. Overall, greater average WM hyperintensity volume was associated with older age and current smoking (69% greater vs never smoking); lower fractional anisotropy was additionally associated with higher diastolic blood pressure, use of antihypertensive medication, and diabetes. Conclusions We found no statistically significant difference in measures of WM injury by race and ethnicity after adjustment for cardiovascular risk factors and socioeconomic status. In all racial and ethnic groups, older age, current smoking, hypertension, and diabetes were strongly associated with WM injury.

Abstract Introduction We sought to investigate associations of regional white matter hyperintensities (WMHs) within white matter (WM) tracts with cardiovascular risk and brain aging‐related atrophy throughout adulthood in the general population, leveraging state of the art pattern analysis methods. Methods We analyzed a large sample (n = 2367) from the Study of Health in Pomerania, Germany (range 20–90 years). WMHs were automatically segmented on T1‐weighted and fluid‐attenuated inversion recovery magnetic resonance images, and WMH volumes were calculated in WM regions defined using the John Hopkins University WM tractography atlas. Regions with the highest average WMH volume were selected. We calculated a subject‐specific index, Spatial Pattern of Alteration for Recognition of Brain Aging, to measure age‐related atrophy patterns. The Framingham cardiovascular disease risk score summarized the individual cardiovascular risk profile. We used structural equation models, independently for each region, using Spatial Pattern of Alteration for Recognition of Brain Aging as a dependent variable, age as an independent variable, and cardiovascular disease risk score and regional WMH volumes as mediators. Results Selected 12 WM regions included 75% of the total WMH burden in average. Structural equation models showed that the age effect on Spatial Pattern of Alteration for Recognition of Brain Aging was mediated by WMHs to a different extent in the superior frontal WM, anterior corona radiata, inferior frontal WM, superior corona radiata, superior longitudinal fasciculus, middle temporal WM, posterior corona radiata, superior parietal WM, splenium of corpus callosum, posterior thalamic radiation, and middle occipital WM (variance explained between 2.8% and 10.3%, P

Abstract Introduction Cognitive tests and nonamyloid imaging biomarkers do not consistently identify preclinical AD. The objective of this study was to evaluate whether white matter hyperintensity (WMH) volume, a cerebrovascular disease marker, is more associated with preclinical AD than conventional AD biomarkers and cognitive tests. Methods Elderly controls enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 158) underwent florbetapir‐PET scans, psychometric testing, neuroimaging with MRI and PET, and APOE genetic testing. Elderly controls the Parkinson's progression markers initiative (PPMI, n = 58) had WMH volume, cerebrospinal fluid (CSF) Aβ1–42, and APOE status measured. Results In the ADNI cohort, only WMH volume and APOE ε4 status were associated with cerebral Aβ (standardized β = 0.44 and 1.25, P = .03 and .002). The association between WMH volume and APOE ε4 status with cerebral Aβ (standardized β = 1.12 and 0.26, P = .048 and .045) was confirmed in the PPMI cohort. Discussion WMH volume is more highly associated with preclinical AD than other AD biomarkers.