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https://pubmed.ncbi.nlm.nih.gov/34662699/, White matter hyperintensities (WMH) are areas of increased signal visualized on T2-weighted fluid attenuated inversion recovery (FLAIR) brain magnetic resonance imaging (MRI) sequences. They are typically attributed to small vessel cerebrovascular disease in the context of aging. Among older adults, WMH are associated with risk of cognitive decline and dementia, stroke, and various other health outcomes. There has been increasing interest in incorporating quantitative WMH measurement as outcomes in clinical trials, observational research, and clinical settings. Here, we present a novel, fully automated, unsupervised detection algorithm for WMH segmentation and quantification. The algorithm uses a robust preprocessing pipeline, including brain extraction and a sample-specific mask that incorporates spatial information for automatic false positive reduction, and a half Gaussian mixture model (HGMM). The method was evaluated in 24 participants with varying degrees of WMH (4.9-78.6 cm3) from a community-based study of aging and dementia with dice coefficient, sensitivity, specificity, correlation, and bias relative to the ground truth manual segmentation approach performed by two expert raters. Results were compared with those derived from commonly used available WMH segmentation packages, including SPM lesion probability algorithm (LPA), SPM lesion growing algorithm (LGA), and Brain Intensity AbNormality Classification Algorithm (BIANCA). The HGMM algorithm derived WMH values that had a dice score of 0.87, sensitivity of 0.89, and specificity of 0.99 compared to ground truth. White matter hyperintensity volumes derived with HGMM were strongly correlated with ground truth values (r = 0.97, p = 3.9e-16), with no observable bias (-1.1 [-2.6, 0.44], p-value = 0.16). Our novel algorithm uniquely uses a robust preprocessing pipeline and a half-Gaussian mixture model to segment WMH with high agreement with ground truth for large scale studies of brain aging.

INTRODUCTIONNumerous neuroimaging studies demonstrated racial and ethnic disparities in brain health at older ages. It remains unclear whether racial and ethnic disparities increase with aging and whether they are already apparent in midlife.METHODSWe investigated differences in MRI markers of aging and cerebrovascular disease in 969 participants from the Washington Heights-Inwood Columbia Aging Project (WHICAP; mean age: 75 years) and 496 participants from the Offspring study (mean age: 55 years) across race and ethnicity (white, Black, Latinx).RESULTSOlder whites had greater cortical thickness compared with Latinxs, who also had greater thickness than Blacks. Cortical thickness was similar across race in the middle-aged cohort. Regarding white matter hyperintensity (WMH) volume, Blacks had disproportionately greater WMH volume compared to both whites and Latinxs at older ages. Racial disparities are already apparent in midlife, where Blacks have disproportionately greater WMH than whites.DiscussionThese findings suggest that racial disparities in WMH volume are already apparent in midlife.

IntroductionAssessment of cognition and everyday function is essential in clinical trials for Alzheimer’s disease (AD). Two novel measures of cognition (No Practice Effects (NPE) cognitive battery and Miami Computerized Functional Assessment Scale (CFAS)) were designed to have robust psychometric properties and reduced practice and ceiling effects. This study aims to evaluate if the NPE and CFAS demonstrate stronger psychometric properties and reduced practice effects compared with established measures, including the Preclinical Alzheimer Cognitive Composite (PACC), Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Functional Activities Questionnaire (FAQ).MethodsThis parallel group, four-site study will randomize 320 cognitively intact adults aged 60 to 85 years to novel or well-established measures of cognition and function. All participants will receive assessments at baseline (week 0), week 12, and week 52, as well as a brain MRI scan and Apolipoprotein E genetic test at study entry. Analyses will determine psychometric properties of the NPE and CFAS, compare the sensitivity of measures to AD risk markers, and identify cognitive domains within the NPE.DiscussionPractice effects have been a major limitation of Alzheimer’s disease clinical trials that typically assess cognitive changes over serial assessments. Detection of functional impairment in cognitively normal individuals with biomarkers for Alzheimer’s disease requires instruments sensitive to very subtle functional changes. This study is intended to support the validation of two new composite measures, the NPE battery and the CFAS, which may advance clinical testing of interventions for individuals across the spectrum of early stage Alzheimer’s disease.Trial RegistrationNCT03900273

Introduction Assessment of cognition and everyday function is essential in clinical trials for Alzheimer's disease (AD). Two novel measures of cognition (No Practice Effects (NPE) cognitive battery and Miami Computerized Functional Assessment Scale (CFAS)) were designed to have robust psychometric properties and reduced practice and ceiling effects. This study aims to evaluate if the NPE and CFAS demonstrate stronger psychometric properties and reduced practice effects compared with established measures, including the Preclinical Alzheimer Cognitive Composite (PACC), Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), and Functional Activities Questionnaire (FAQ). Methods This parallel group, four-site study will randomize 320 cognitively intact adults aged 60 to 85 years to novel or well-established measures of cognition and function. All participants will receive assessments at baseline (week 0), 3-months, and 12-months, as well as a brain MRI scan and Apolipoprotein E genetic test at study entry. Analyses will determine psychometric properties of the NPE and CFAS, compare the sensitivity of measures to AD risk markers, and identify cognitive domains within the NPE. Discussion Practice effects have been a major limitation of Alzheimer's disease clinical trials that typically assess cognitive changes over serial assessments. Detection of functional impairment in cognitively normal individuals with biomarkers for Alzheimer's disease requires instruments sensitive to very subtle functional changes. This study is intended to support the validation of two new composite measures, the NPE battery and the CFAS, which may advance clinical testing of interventions for individuals across the spectrum of early stage Alzheimer's disease. Trial Registration: NCT03900273