Left Atrial Function and Arrhythmias in Relation to Small Vessel Disease on Brain MRI: The Multi‐Ethnic Study of Atherosclerosis

Abstract

Background Atrial fibrillation (AF) is associated with increased stroke risk and accelerated cognitive decline, but the association of early manifestations of left atrial (LA) impairment with subclinical changes in brain structure is unclear. We investigated whether abnormal LA structure and function, greater supraventricular ectopy, and intermittent AF are associated with small vessel disease on magnetic resonance imaging of the brain. Methods and Results In the Multi‐Ethnic Study of Atherosclerosis, 967 participants completed 14‐day ambulatory electrocardiographic monitoring, speckle tracking echocardiography and, a median 17 months later, magnetic resonance imaging of the brain. We assessed associations of LA volume index and reservoir strain, supraventricular ectopy, and prevalent AF with brain magnetic resonance imaging measures of small vessel disease and atrophy. The mean age of participants was 72 years; 53% were women. In multivariable models, LA enlargement was associated with lower white matter fractional anisotropy and greater prevalence of microbleeds; reduced LA strain, indicating worse LA function, was associated with more microbleeds. More premature atrial contractions were associated with lower total gray matter volume. Compared with no AF, intermittent AF (prevalent AF with <100% AF during electrocardiographic monitoring) was associated with lower white matter fractional anisotropy (−0.25 SDs [95% CI, −0.44 to −0.07]) and greater prevalence of microbleeds (prevalence ratio: 1.42 [95% CI, 1.12–1.79]). Conclusions In individuals without a history of stroke or transient ischemic attack, alterations of LA structure and function, including enlargement, reduced strain, frequent premature atrial contractions, and intermittent AF, were associated with increased markers of small vessel disease. Detailed assessment of LA structure and function and extended ECG monitoring may enable early identification of individuals at greater risk of small vessel disease.

Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA

“…A clinical study reported higher microbleed prevalence in patients with atrial fibrillation than in those without, but the analyses were not adjusted for other microbleed risk factors 27 . We previously showed that greater left atrial volume index was associated with microbleeds in MESA participants 20 . Taken together, these findings support the involvement of atrial fibrillation in the pathophysiology of microbleeds, but do not provide insight as to whether atrial fibrillation is causally related to microbleeds or is a manifestation of underlying vascular pathology or shared risk factors.…”

“…Microbleeds were initially identified by a deep learning‐based method that used T2‐weighted quantitative susceptibility mapping and SWI images to segment the lesions and differentiate microbleeds from iron deposits (Figure 1). 8 Identified lesions were then reviewed by a radiologist (JBW) who made the final classification, as previously described 20 . Microbleed location was classified by mapping the 146 Multi‐atlas region Segmentation Using Ensembles (MUSE)–based regions of interest 21 to the Microbleed Anatomical Rating Scale (MARS) regions of interest 22 and grouping them into three categories: lobar (frontal, parietal, temporal, occipital, and insula), deep (basal ganglia, thalamus, internal capsule, corpus callosum, and deep and periventricular white matter [WM]), and infratentorial (brainstem and cerebellum).…”

“…8 Identified lesions were then reviewed by a radiologist (JBW) who made the final classification, as previously described. 20…”

“…MRI scanner parameters are in the Supplemental Methods in supporting information. 20 Microbleeds were initially identified by a deep learning-based method that used T2-weighted quantitative susceptibility mapping and SWI images to segment the lesions and differentiate microbleeds from iron deposits (Figure 1). 8 Identified lesions were then reviewed by a radiologist (JBW) who made the final classification, as previously described.…”

Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers

“…We worked with the same WML segmentations used in previous SPRINT studies. 26 , 27 , 28 These WML segmentations were derived with a deep learning method 31 and applied in large cohort studies 11 , 32 , 33 , 34 with similar settings. We calculated the total WMLs, mean FA, and MD for all the WM regions of interest (ROIs) of the Type III WM parcellation map.…”