Although white matter hyperintensities (WMHs) are associated with the risk for Alzheimer disease, it is unknown whether they represent an independent source of impairment or interact with known ...markers of disease.
To examine the degree to which WMHs predict aggressive cognitive decline among individuals with mild cognitive impairment, either independently or by modifying the effects of entorhinal cortex volume (ECV), a marker of Alzheimer disease-related neurodegeneration.
The Alzheimer's Disease Neuroimaging Initiative is a longitudinal study with 6-month follow-up visits. Three hundred thirty-two participants (mean SD age, 74.6 7.4 years; 118 women) of a total of 374 participants diagnosed as having mild cognitive impairment were included. Participants were excluded if they did not have longitudinal data, apolipoprotein E genotype data, or had evidence of supratentorial infarct.
A decline in Mini-Mental State Examination score of 3 points over 6 months or 6 points over 1 year between consecutive visits was defined as aggressive decline. White matter hyperintensity volume and ECV were entered as predictors in Cox proportional hazards models and Wilcoxon-Breslow tests to examine their impact on this outcome, adjusting for sex, age, education, and apolipoprotein E status.
Greater WMH volume at baseline, apolipoprotein E ε4 status, and smaller ECV at baseline were associated with an increased risk for aggressive decline (hazard ratio HR, 1.23; 95% CI, 1.05-1.43; P = .01 for WMH volume; HR, 1.49; 95% CI, 1.09-2.05; P = .04 for apolipoprotein E ε4 status; HR, 0.66; 95% CI, 0.55-0.79; P < .001 for ECV). White matter hyperintensity volume modified the effect of ECV on aggressive decline risk: individuals with high ECV and low WMH were at particularly low likelihood of decline (χ2 = 15, P = .001). Participants with Mini-Mental State Examination scores that declined by 3 or more points over 6 months or 6 or more points over 12 months were more likely to have converted to Alzheimer disease by the end of the follow-up period (χ2 = 82, P < .001).
White matter hyperintensity burden and ECV predict rapid cognitive decline among individuals with mild cognitive impairment both additively and multiplicatively.
Aging is accompanied by clinically silent cerebral white matter injury identified through white matter hyperintensities (WMHs) on fluid-attenuated inversion recovery (FLAIR)- and diffusion tensor ...imaging-based measures of white matter integrity. The temporal course of FLAIR and diffusion tensor imaging changes within WMHs and their less-injured periphery (ie, their penumbra), however, has not been fully studied. We used longitudinal diffusion tensor imaging and FLAIR to explore these changes.
One hundred fifteen participants, aged 73.7±6.7 years, received clinical evaluations and MRIs on 2 dates. WMHs and fractional anisotropy (FA) maps were produced from FLAIR and diffusion tensor imaging and coregistered to a standardized space. Each distinct WMH was categorized as growing, stagnant, or noncontiguous incident. The penumbra of each WMH was similarly categorized as corresponding to a stagnant, growing, or noncontiguous incident WMH. Linear mixed-effect models were used to assess whether FA and FLAIR measurements changed between baseline and follow-up and differed between tissue categories.
Baseline FA differed significantly by tissue category, with the following ordering of categories from highest to lowest FA: penumbra of noncontiguous incident, then stagnant, then growing WMHs; noncontiguous incident, then stagnant, then growing WMHs. Despite differences in baseline values, all tissue categories experienced declines in FA over time. Only noncontiguous incident WMHs showed significant FLAIR signal increases over time, and FLAIR signal significantly decreased in stagnant WMHs.
WMHs and their penumbra vary in severity and together span a continuous spectrum of white matter injury that worsens with time. FLAIR fails to capture this continuous injury process fully but does identify a subclass of lesions that seem to improve over time.
Summary Background Previous studies have identified effects of age and vascular risk factors on brain injury in elderly individuals. We aimed to establish whether the effects of high blood pressure ...in the brain are evident as early as the fifth decade of life. Methods In an investigation of the third generation of the Framingham Heart Study, we approached all participants in 2009 to ask whether they would be willing to undergo MRI. Consenting patients underwent clinical assessment and cerebral MRI that included T1-weighted and diffusion tensor imaging to obtain estimates of fractional anisotropy, mean diffusivity, and grey-matter volumes. All images were coregistered to a common minimum deformation template for voxel-based linear regressions relating fractional anisotropy, mean diffusivity, and grey-matter volumes to age and systolic blood pressure, with adjustment for potential confounders. Findings 579 (14·1%) of 4095 participants in the third-generation cohort (mean age 39·2 years, SD 8·4) underwent brain MRI between June, 2009 and June, 2010. Age was associated with decreased fractional anisotropy and increased mean diffusivity in almost all cerebral white-matter voxels. Age was also independently associated with reduced grey-matter volumes. Increased systolic blood pressure was linearly associated with decreased regional fractional anisotropy and increased mean diffusivity, especially in the anterior corpus callosum, the inferior fronto-occipital fasciculi, and the fibres that project from the thalamus to the superior frontal gyrus. It was also strongly associated with reduced grey-matter volumes, particularly in Brodmann's area 48 on the medial surface of the temporal lobe and Brodmann's area 21 of the middle temporal gyrus. Interpretation Our results suggest that subtle vascular brain injury develops insidiously during life, with discernible effects even in young adults. These findings emphasise the need for early and optimum control of blood pressure. Funding National Institutes of Health and National Heart, Lung, and Blood Institute; National Institute on Aging; and National Institute of Neurological Disorders and Stroke.
Introduction
Fluid‐attenuated Inversion Recovery (FLAIR) and dual T2w and proton density (PD) magnetic resonance images (MRIs) are considered to be the optimum sequences for detecting white matter ...hyperintensities (WMHs) in aging and Alzheimer's disease populations. However, many existing large multisite studies forgo their acquisition in favor of other MRI sequences due to economic and time constraints.
Methods
In this article, we have investigated whether FLAIR and T2w/PD sequences are necessary to detect WMHs in Alzheimer's and aging studies, compared to using only T1w images. Using a previously validated automated tool based on a Random Forests classifier, WMHs were segmented for the baseline visits of subjects from ADC, ADNI1, and ADNI2/GO studies with and without T2w/PD and FLAIR information. The obtained WMH loads (WMHLs) in different lobes were then correlated with manually segmented WMHLs, each other, age, cognitive, and clinical measures to assess the strength of the correlations with and without using T2w/PD and FLAIR information.
Results
The WMHLs obtained from T1w‐Only segmentations correlated with the manual WMHLs (ADNI1: r = .743, p < .001, ADNI2/GO: r = .904, p < .001), segmentations obtained from T1w + T2w + PD for ADNI1 (r = .888, p < .001) and T1w + FLAIR for ADNI2/GO (r = .969, p < .001), age (ADNI1: r = .391, p < .001, ADNI2/GO: r = .466, p < .001), and ADAS13 (ADNI1: r = .227, p < .001, ADNI2/GO: r = .190, p < 0.001), and NPI (ADNI1: r = .290, p < .001, ADNI2/GO: r = 0.144, p < .001), controlling for age.
Conclusion
Our results suggest that while T2w/PD and FLAIR provide more accurate estimates of the true WMHLs, T1w‐Only segmentations can still provide estimates that hold strong correlations with the actual WMHLs, age, and performance on various cognitive/clinical scales, giving added value to datasets where T2w/PD or FLAIR are not available.
White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are ...important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown.
We compare 10 different linear and nonlinear classification techniques to identify WMHs from MRI data. Each classifier is trained and optimized based on a set of features obtained from co-registered MR images containing spatial location and intensity information. We further assess the performance of the classifiers using different combinations of MRI contrast information. The performances of the different classifiers were compared on three heterogeneous multi-site datasets, including images acquired with different scanners and different scan-parameters. These included data from the ADC study from University of California Davis, the NACC database and the ADNI study. The classifiers (naïve Bayes, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, bagging, and boosting) were evaluated using a variety of voxel-wise and volumetric similarity measures such as Dice Kappa similarity index (SI), Intra-Class Correlation (ICC), and sensitivity as well as computational burden and processing times. These investigations enable meaningful comparisons between the performances of different classifiers to determine the most suitable classifiers for segmentation of WMHs. In the spirit of open-source science, we also make available a fully automated tool for segmentation of WMHs with pre-trained classifiers for all these techniques.
Random Forests yielded the best performance among all classifiers with mean Dice Kappa (SI) of 0.66±0.17 and ICC=0.99 for the ADC dataset (using T1w, T2w, PD, and FLAIR scans), SI=0.72±0.10, ICC=0.93 for the NACC dataset (using T1w and FLAIR scans), SI=0.66±0.23, ICC=0.94 for ADNI1 dataset (using T1w, T2w, and PD scans) and SI=0.72±0.19, ICC=0.96 for ADNI2/GO dataset (using T1w and FLAIR scans). Not using the T2w/PD information did not change the performance of the Random Forest classifier (SI=0.66±0.17, ICC=0.99). However, not using FLAIR information in the ADC dataset significantly decreased the Dice Kappa, but the volumetric correlation did not drastically change (SI=0.47±0.21, ICC=0.95).
Our investigations showed that with appropriate features, most off-the-shelf classifiers are able to accurately detect WMHs in presence of FLAIR scan information, while Random Forests had the best performance across all datasets. However, we observed that the performances of most linear classifiers and some nonlinear classifiers drastically decline in absence of FLAIR information, with Random Forest still retaining the best performance.
To test if sugar sweetened beverages (SSBs) and sugar sweetened solids (SSSs) have differential effects on body weight and reward processing in the brain.
In a single blind randomized controlled ...pilot trial (RCT), twenty participants with BMI between 20 and 40 kg/m2 were randomized to consume a 20 fluid ounce soda (SSB, 248 kcal) or the equivalent in solid form (SSS; similar to thick gelatin or gummy candy) daily. At baseline and day 28, fasting body weight and fed-state BOLD fMRI of the brain were assessed. Differences in fMRI signals between views of low-fat (LF (<30%)) high sugar (HS (>30%)) food, and non-food images were calculated in brain regions implicated in energy homeostasis, taste, and reward.
All participants in the SSB (6F 4M; 8 Caucasian; 36±14 y, 28.2±5.5 kg/m2; Mean±SD) and SSS (3F 7M; 6 Caucasian; 39±12; 26.3±4.4) groups completed the study. Weight change was 0.27±0.78 kg between SSB and SSS participants. Changes in the fMRI response to LF/HS foods in reward, homeostatic and taste regions tended to not be different between the groups over the four weeks. However, activation of the right substantia nigra increased following the SSB but decreased activation following the SSS in response to LF/HS foods over 28 days (-0.32±0.12). Ratings of wanting for LF/HS foods were correlated with activation in several brain regions, including the OFC.
Change in weight was modest between the groups in this study. Daily consumption of a SSB over 28 days led to mixed responses to LF/HS foods in areas of the brain associated with reward. Ratings of wanting are correlated with fMRI activation inside an MRI scanner.
White matter hyperintensities (WMHs) are associated with progressive age-related cognitive decline and cardiovascular risk factors, but their biological relevance as indicators of generalized white ...matter injury is unclear. Diffusion tensor imaging provides more sensitive indications of subtle white matter disruption and can therefore clarify whether WMHs represent foci of generalized white matter damage that extends over a broader neighborhood.
Two hundred eight participants from the University of California, Davis Alzheimer's Disease Center received a comprehensive clinical evaluation and brain MRI including fluid-attenuated inversion recovery and diffusion tensor imaging sequences. Voxelwise maps of WMHs were produced from fluid-attenuated inversion recovery using a standardized WMH detection protocol. Fractional anisotropy maps were calculated from diffusion tensor imaging. All WMH and fractional anisotropy maps were coregistered to a standardized space. For each normal-appearing white matter voxel in each subject fluid-attenuated inversion recovery scan, a neighborhood white matter injury score was calculated that increased with increasing number and proximity of WMH in the vicinity of the normal-appearing white matter voxel. Fractional anisotropy was related to neighborhood white matter injury using a nonlinear mixed effect model controlling for relevant confounding factors.
Fractional anisotropy was found to decrease as neighborhood white matter injury increased (β = -0.0017/%, P < 0.0001) with an accelerated rate (P < 0.0001) for neighborhood white matter injury >0.4. An increase of 1% in neighborhood white matter injury score was associated with a decrease in mean fractional anisotropy of 0.012 (P < 0.001).
WMH may represent foci of more widespread and subtle white matter changes rather than distinct, sharply delineated anatomic abnormalities. We use the term white matter hyperintensities penumbra to explain this phenomenon.
To investigate the effects of baseline white matter hyperintensity (WMH) and rates of WMH extension and emergence on rate of change in cognition (episodic memory and executive function).
A total of ...150 individuals including cognitively normal elderly individuals and those with Alzheimer disease and mild cognitive impairment completed serial episodic memory and executive function evaluations and serial MRI scans sufficient for longitudinal measurement of WMH (mean delay 4.0 years). Incident WMH voxels were categorized as extended (baseline WMH that grew larger) or emergent (newly formed WMH). We used a stepwise regression approach to investigate the effects of baseline WMH and rates of WMH extension and emergence on rate of change in cognition (episodic memory and executive function).
WMH burden significantly increased over time, and approximately 80% of incident WMH voxels represented extensions of existing lesions. Each 1 mL/y increase in WMH extension was associated with an additional 0.70 SD/y of subsequent episodic memory decrease (p = 0.0053) and an additional 0.55 SD/y of subsequent executive function decrease (p = 0.022). Emergent WMHs were not found to be associated with a change in cognitive measures.
Aging-associated WMHs evolve significantly over a 4-year period. Most of this evolution represents worsening injury to the already compromised surround of existing lesions. Increasing WMH was also significantly associated with declining episodic memory and executive function. This finding supports the view that white matter disease is an insidious and continuously evolving process whose progression has clinically relevant cognitive consequences.
Abstract Introduction It is unclear whether white matter hyperintensities (WMHs), magnetic resonance imaging markers of small-vessel cerebrovascular disease, promote neurodegeneration and associated ...clinical decline in Alzheimer's disease (AD), or simply co-occur with recognized pathogenic processes. Methods In 169 patients with mild cognitive impairment, followed for 3 years, we examined the association of (1) baseline regional WMH and cerebral spinal fluid–derived t-tau (total tau) with entorhinal cortex atrophy rates, as a marker of AD-related neurodegeneration, and conversion to AD; and (2) baseline regional WMH with change in t-tau level. Results In participants with low baseline t-tau, higher regional WMH volumes were associated with faster entorhinal cortex atrophy. Higher parietal WMH volume predicted conversion to AD in those with high t-tau. Higher parietal and occipital WMH volumes predicted increasing t-tau. Discussion WMHs affect AD clinical and pathologic processes both directly and interacting with tau.
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