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Background: White matter hyperintensities (WMH), associated with both dementia risk and progression, can individually progress, remain stable, or even regress influencing cognitive decline related to specific cerebrovascular-risks. This study details the development and validation of a registration protocol to assess regional, within-subject, longitudinal WMH changes (ΔWMH) that is currently lacking in the field., New Method: 3D-FLAIR images (baseline and one-year-visit) were used for protocol development and validation. The method was validated by assessing the correlation between forward and reverse longitudinal registration, and between summated regional progression-regression volumes and Global ΔWMH. The clinical relevance of growth-regression ΔWMH were explored in relation to an executive function test., Results: MRI scans for 79 participants (73.5 ± 8.8 years) were used in this study. Global ΔWMH vs. summated regional progression-regression volumes were highly associated (r2 = 0.90; p-value < 0.001). Bi-directional registration validated the registration method (r2 = 0.999; p-value < 0.001). Growth and regression, but not overall ΔWMH, were associated with one-year declines in performance on Trial-Making-Test-B., Comparison With Existing Method(s): This method presents a unique registration protocol for maximum tissue alignment, demonstrating three distinct patterns of longitudinal within-subject ΔWMH (stable, growth and regression)., Conclusions: These data detail the development and validation of a registration protocol for use in assessing within-subject, voxel-level alterations in WMH volume. The methods developed for registration and intensity correction of longitudinal within-subject FLAIR images allow regional and within-lesion characterization of longitudinal ΔWMH. Assessing the impact of associated cerebrovascular-risks and longitudinal clinical changes in relation to dynamic regional ΔWMH is needed in future studies., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Disparate research sites using identical or near-identical magnetic resonance imaging (MRI) acquisition techniques often produce results that demonstrate significant variability regarding volumetric quantification of white matter hyperintensities (WMH) in the aging population. The sources of such variability have not previously been fully explored., New Method: 3D FLAIR sequences from a group of randomly selected aged subjects were analyzed to identify sources-of-variability in post-acquisition processing that can be problematic when comparing WMH volumetric data across disparate sites. The methods developed focused on standardizing post-acquisition protocol processing methods to develop a protocol with less than 0.5% inter-rater variance., Results: A series of experiments using standard MRI acquisition sequences explored post-acquisition sources-of-variability in the quantification of WMH volumetric data. Sources-of-variability included: the choice of image center, software suite and version, thresholding selection, and manual editing procedures (when used). Controlling for the identified sources-of-variability led to a protocol with less than 0.5% variability between independent raters in post-acquisition WMH volumetric quantification., Comparison With Existing Method(s): Post-acquisition processing techniques can introduce an average variance approaching 15% in WMH volume quantification despite identical scan acquisitions. Understanding and controlling for such sources-of-variability can reduce post-acquisition quantitative image processing variance to less than 0.5%., Discussion: Considerations of potential sources-of-variability in MRI volume quantification techniques and reduction in such variability is imperative to allow for reliable cross-site and cross-study comparisons., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background and Purpose: Interpreting the clinical significance of moderate-to-severe global cerebral atrophy (GCA) is a conundrum for many clinicians, who visually interpret brain imaging studies in routine clinical practice. GCA may be attributed to normal aging, Alzheimer's disease (AD), or cerebrovascular disease (CVD). Understanding the relationships of GCA with aging, AD, and CVD is important for accurate diagnosis and treatment decisions for cognitive complaints., Methods: To elucidate the relative associations of age, moderate-to-severe white matter hyperintensities (WMHs), and moderate-to-severe medial temporal lobe atrophy (MTA), with moderate-to-severe GCA, we visually rated clinical brain imaging studies of 325 participants from a community based sample. Logistic regression analysis was conducted to assess the relations of GCA with age, WMH, and MTA., Results: The mean age was 76.2 (±9.6) years, 40.6% were male, and the mean educational attainment was 15.1 (±3.7) years. Logistic regression results demonstrated that while a 1-year increase in age was associated with GCA (OR = 1.04; P = .04), MTA (OR = 3.7; P < .001), and WMH (OR = 8.80; P < .001) were strongly associated with GCA in our study population. Partial correlation analysis showed that the variance of GCA explained by age is less than the variance attributed to MTA and WMH (r = .13, .21, and .43, respectively)., Conclusions: Moderate-to-severe GCA is most likely to occur in the presence of AD or CVD and should not be solely attributed to age when evaluating clinical imaging findings in the workup of cognitive complaints. Developing optimal diagnostic and treatment strategies for cognitive decline in the setting of GCA requires an understanding of its risk factors in the aging population., (Copyright © 2018 by the American Society of Neuroimaging.)

Background: Alzheimer's disease (AD) pathology and hypertension (HTN) are risk factors for development of white matter (WM) alterations and might be independently associated with these alterations in older adults., Objective: To evaluate the independent and synergistic effects of HTN and AD pathology on WM alterations., Methods: Clinical measures of cerebrovascular disease risk were collected from 62 participants in University of Kentucky Alzheimer's Disease Center studies who also had cerebrospinal fluid (CSF) sampling and MRI brain scans. CSF Aβ1-42 levels were measured as a marker of AD, and fluid-attenuated inversion recovery imaging and diffusion tensor imaging were obtained to assess WM macro- and microstructural properties. Linear regression analyses were used to assess the relationships among WM alterations, cerebrovascular disease risk, and AD pathology. Voxelwise analyses were performed to examine spatial patterns of WM alteration associated with each pathology., Results: HTN and CSF Aβ1-42 levels were each associated with white matter hyperintensities (WMH). Also, CSF Aβ1-42 levels were associated with alterations in normal appearing white matter fractional anisotropy (NAWM-FA), whereas HTN was marginally associated with alterations in NAWM-FA. Linear regression analyses demonstrated significant main effects of HTN and CSF Aβ1-42 on WMH volume, but no significant HTN×CSF Aβ1-42 interaction. Furthermore, voxelwise analyses showed unique patterns of WM alteration associated with hypertension and CSF Aβ1-42., Conclusion: Associations of HTN and lower CSF Aβ1-42 with WM alteration were statistically and spatially distinct, suggesting independent rather than synergistic effects. Considering such spatial distributions may improve diagnostic accuracy to address each underlying pathology.