Empirical assessment of the assumptions of ComBat with diffusion tensor imaging.

Purpose: Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides unique information about white matter microstructure in the brain but is susceptible to confounding effects introduced by scanner or acquisition differences. ComBat is a leading approach for addressing these site biases. However, despite its frequent use for harmonization, ComBat's robustness toward site dissimilarities and overall cohort size have not yet been evaluated in terms of DTI. Approach: As a baseline, we match N=358 participants from two sites to create a "silver standard" that simulates a cohort for multi-site harmonization. Across sites, we harmonize mean fractional anisotropy and mean diffusivity, calculated using participant DTI data, for the regions of interest defined by the JHU EVE-Type III atlas. We bootstrap 10 iterations at 19 levels of total sample size, 10 levels of sample size imbalance between sites, and 6 levels of mean age difference between sites to quantify (i) ßAGE, the linear regression coefficient of the relationship between FA and age; (ii) Î³/f*, the ComBat-estimated site-shift; and (iii) Î´/f*, the ComBat-estimated site-scaling. We characterize the reliability of ComBat by evaluating the root mean squared error in these three metrics and examine if there is a correlation between the reliability of ComBat and a violation of assumptions. Results: ComBat remains well behaved for ßAGE when N>162 and when the mean age difference is less than 4 years. The assumptions of the ComBat model regarding the normality of residual distributions are not violated as the model becomes unstable. Conclusion: Prior to harmonization of DTI data with ComBat, the input cohort should be examined for size and covariate distributions of each site. Direct assessment of residual distributions is less informative on stability than bootstrap analysis. We caution use ComBat of in situations that do not conform to the above thresholds.

Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis.

Importance: Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain. Objective: Toperform a whole-brain investigation of ePVSs in a large community-based cohort. Design, Setting, and Participants: This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included. Main Outcomes and Measures: Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models. Results: In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (ß = 3.59 × 10-3; 95% CI, 2.80 × 10-3 to 4.39 × 10-3), systolic blood pressure (ß = 8.35 × 10-4; 95% CI, 5.19 × 10-4 to 1.15 × 10-3), use of antihypertensives (ß = 3.29 × 10-2; 95% CI, 1.92 × 10-2 to 4.67 × 10-2), and negatively associated with Black race (ß = -3.34 × 10-2; 95% CI, -5.08 × 10-2 to -1.59 × 10-2). Thalamic ePVS volume was positively associated with age (ß = 5.57 × 10-4; 95% CI, 2.19 × 10-4 to 8.95 × 10-4) and use of antihypertensives (ß = 1.19 × 10-2; 95% CI, 6.02 × 10-3 to 1.77 × 10-2). Insular region ePVS volume was positively associated with age (ß = 1.18 × 10-3; 95% CI, 7.98 × 10-4 to 1.55 × 10-3). Brainstem ePVS volume was smaller in Black than in White participants (ß = -5.34 × 10-3; 95% CI, -8.26 × 10-3 to -2.41 × 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (ß = 1.14 × 10-4; 95% CI, 3.38 × 10-5 to 1.95 × 10-4) and negatively associated with age (ß = -3.38 × 10-4; 95% CI, -5.40 × 10-4 to -1.36 × 10-4). Temporal region ePVS volume was negatively associated with age (ß = -1.61 × 10-2; 95% CI, -2.14 × 10-2 to -1.09 × 10-2), as well as Chinese American (ß = -2.35 × 10-1; 95% CI, -3.83 × 10-1 to -8.74 × 10-2) and Hispanic ethnicities (ß = -1.73 × 10-1; 95% CI, -2.96 × 10-1 to -4.99 × 10-2). Conclusions and Relevance: In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations.

State School Policies as Predictors of Physical and Mental Health: A Natural Experiment in the REGARDS Cohort.

We used differences in state school policies as natural experiments to evaluate the joint influence of educational quantity and quality on late-life physical and mental health. Using US Census microsample data, historical measures of state compulsory schooling and school quality (term length, student-teacher ratio, and attendance rates) were combined via regression modeling on a scale corresponding to years of education (policy-predicted years of education (PPYEd)). PPYEd values were linked to individual-level records for 8,920 black and 14,605 white participants aged ≥45 years in the Reasons for Geographic and Racial Differences in Stroke study (2003-2007). Linear and quantile regression models estimated the association between PPYEd and Physical Component Summary (PCS) and Mental Component Summary (MCS) from the Short Form Health Survey. We examined interactions by race and adjusted for sex, birth year, state of residence at age 6 years, and year of study enrollment. Higher PPYEd was associated with better median PCS (ß = 1.28, 95% confidence interval (CI): 0.40, 1.49) and possibly better median MCS (ß = 0.46, 95% CI: -0.01, 0.94). Effect estimates were higher among black (vs. white) persons (PCS × race interaction, ß = 0.22, 95% CI: -0.62, 1.05, and MCS × race interaction, ß = 0.18; 95% CI: -0.08, 0.44). When incorporating both school quality and duration, this quasiexperimental analysis found mixed evidence for a causal effect of education on health decades later.