Tensor-based morphometry is a powerful tool for automatically computing longitudinal change in brain structure. Because of bias in images and in the algorithm itself, however, a penalty term and inverse consistency are needed to control the over-reporting of nonbiological change. These may force a tradeoff between the intrinsic sensitivity and specificity, potentially leading to an under-reporting of authentic biological change with time. We propose a new method incorporating prior information about tissue boundaries (where biological change is likely to exist) that aims to keep the robustness and specificity contributed by the penalty term and inverse consistency while maintaining localization and sensitivity. Results indicate that this method has improved sensitivity without increased noise. Thus it will have enhanced power to detect differences within normal aging and along the spectrum of cognitive impairment.
Biomedical imaging; brain boundary shift; image matching; image registration; Kullback–Liebler; tensor-based morphometry (TBM)
Many brain aging studies use total intracranial volume (TIV) as a proxy measure of premorbid brain size that is unaffected by neurodegeneration. T1-weighted Magnetic Resonance Imaging (MRI) sequences are commonly used to measure TIV, but T2-weighted MRI sequences provide superior contrast between the cerebrospinal fluid (CSF) bounding the premorbid brain space and surrounding dura mater. In this study, we compared T1-based and T2-based TIV measurements to assess the practical impact of this superior contrast on studies of brain aging. 810 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, including healthy elders and those with mild cognitive impairment (MCI) and Alzheimer’s Disease (AD), received T1-weighted and T2-weighted MRI at their baseline evaluation. TIV was automatically estimated from T1-weighted images using FreeSurfer version 4.3 (T1TIV), and an automated active contour method was used to estimate TIV from T2-weighted images (T2TIV). The correlation between T1TIV and T2TIV was high (.93), and disagreement was greater on larger heads. However, correcting a FreeSurfer-based measure of total parenchymal volume by dividing it by T2TIV led to stronger expected associations with a standardized measure of cognitive dysfunction (MMSE) in Poisson regression models among individuals with AD (z=1.73 vs. 1.09) and MCI (z=3.15 vs. 2.79) than a corresponding parenchymal volume measure divided by T1TIV. This effect was enhanced when the analysis was restricted to the cases where T1TIV and T2TIV disagreed the most. These findings suggest that T2-based TIV measurements may be higher fidelity than T1-based TIV measurements, thus leading to greater sensitivity to detect biologically plausible brain-behavior associations.
total intracranial volume; segmentation; FreeSurfer; MRI; image processing
Age related memory decline is the consequence of multiple biological factors that lead to brain structural and functional change, including gray matter atrophy, white matter injury, and loss of functional coordination between regions. However, the independent roles that each of these brain changes play in mediating memory decline is not clear. Therefore, we used magnetic resonance imaging (MRI) to measure gray matter volume (GM), white matter hyperintensities (WMH) volumes, and BOLD fMRI based functional connectivity among default mode network nodes in 76 cognitive normal older adults. We found that GM, WMH and connectivity between left inferior parietal and medial prefrontal cortex (MPF_LIP) were independently associated with episodic memory performance. Within the group with GM volumes below the median, greater MPF_LIP connectivity was associated with better memory performance, whereas this association was not present for individuals with GM volume above the median. These findings confirm the heterogeneous nature of brain-behavior relationships in cognitive aging. In addition, the relationship between resting state functional connectivity and memory performance, particularly amongst those individuals with more brain atrophy, strongly suggests compensation against the effects of neuronal injury.
MRI measures; Gray matter; white matter hyperintensity; resting-state MRI; Functional connectivity; Episodic memory performance
Background and Purpose
To investigate whether the Framingham Cardiovascular Risk Profile (FCRP) and carotid artery intima-media thickness (CIMT) are associated with cortical volume and thickness.
Consecutive subjects participating in a prospective cohort study of aging and mild cognitive impairment enriched for vascular risk factors for atherosclerosis underwent structural MRI scans at 3T and 4T MRI at three sites. Freesurfer (v5.1) was used to obtain regional measures of neocortical volumes (mm3) and thickness (mm). Multiple linear regression was used to determine the association of FCRP and CIMT with cortical volume and thickness
152 subjects (82 men) were aged 78 (±7) years old, 94 had a CDR of 0, 58 had a clinical dementia rating (CDR) of 0.5 and the mean mini-mental status examination (MMSE) was 28 ± 2. FCRP score was inversely associated with total gray matter (GM) volume, parietal and temporal GM volume (adjusted p<0.04). FCRP was inversely associated with parietal and total cerebral GM thickness (adjusted p<0.03). CIMT was inversely associated with thickness of parietal GM only (adjusted p=0.04). Including history of myocardial infarction or stroke and radiologic evidence of brain infarction, or apoE genotype did not alter relationships with FCRP or CIMT.
Increased cardiovascular risk was associated with reduced GM volume and thickness in regions also affected by Alzheimer’s disease (AD), independent of infarcts and apoE genotype. These results suggest a “double hit” toward developing dementia when someone with incipient AD also has high cardiovascular risk.
Framingham cardiovascular risk profile; carotid intima media thickness; gray matter; cortical volume; cortical thickness; atrophy
Automatically segmenting brain magnetic resonance images into grey matter, white matter, and cerebrospinal fluid compartments is a fundamentally important neuroimaging problem whose difficulty is heightened in the presence of aging and neurodegenerative disease. Current methods overlap greatly in terms of identifiable algorithmic components, and the impact of specific components on performance is generally unclear in important real-world scenarios involving serial scanning, multiple scanners, and neurodegenerative disease. Therefore we evaluated the impact that one such component, the Markov Random Field (MRF) optimizer that encourages spatially-smooth tissue labelings, has on brain tissue segmentation performance. Two challenging elderly sets were used to test segmentation consistency across scanners and biological plausibility of tissue change estimates; and a simulated young brain data set was used to test accuracy against ground truth. Comparisons among Graph Cuts (GC), Belief Propagation (BP), and Iterative Conditional Modes (ICM) suggested that in the elderly brain, BP and GC provide the highest segmentation performance, with a slight advantage to BP, and that performance is often superior to that provided by popular methods SPM and FAST. Conversely, SPM and FAST excelled in the young brain, thus emphasizing the unique challenges involved in imaging the aging brain.
Objectives and Methods:
The purpose of this study was to examine the incidence of mild cognitive impairment (MCI) and patterns of progression from incident MCI to dementia in 285 cognitively normal subjects (mean age, 78.9 years) in the Cardiovascular Health Study–Cognition Study from 1998–1999 to 2010–2011.
Two hundred (70%) of the participants progressed to MCI; the age-adjusted incidence of MCI was 111.09 (95% confidence interval, 88.13–142.95) per 1,000 person-years. A total of 107 (53.5%) of the incident MCI subjects progressed to dementia. The mean time from MCI to dementia was 2.8 ± 1.8 years. Forty (20%) of the incident MCI cases had an “unstable” course: 19 (9.5%) converted to MCI and later returned to normal; 10 (5%) converted to MCI, to normal, and later back to MCI; 7 (3.5%) converted to MCI, to normal, to MCI, and later to dementia; and 4 (2%) converted to MCI, to normal, and later to dementia. There was an increased mortality rate among the cognitively normal group (110.10 per 1,000 person-years) compared to those with incident MCI who converted to dementia (41.32 per 1,000 person-years).
The majority of the subjects aged >80 years developed an MCI syndrome, and half of them progressed to dementia. Once the MCI syndrome was present, the symptoms of dementia appeared within 2 to 3 years. Progression from normal to MCI or from normal to MCI to dementia is not always linear; subjects who developed MCI and later returned to normal can subsequently progress to dementia. Competing mortality and morbidity influence the study of incident MCI and dementia in population cohorts.
Diffusion tensor magnetic resonance imaging (DTI), a method for measuring the integrity of axon fiber tracts in the brain, plays an important role in clarifying brain changes that accompany aging and aging-associated neurodegenerative disease. While DTI smoothing methods theoretically have the potential to enhance such studies by reducing noise, it is unclear whether DTI smoothing has any practical impact on computed associations between fiber tract integrity and scientific variables of interest. Therefore we smoothed DTI images from 154 older adults using three kernel smoothing methods hypothesized to have differing strengths (the affine and log-Euclidean smoothers were hypothesized to enhance highly organized tracts better than the Euclidean smoother). Smoothing increased the strengths of expected associations between DTI and age, cognitive function, and the diagnosis of dementia. However, no particular smoothing method was uniformly superior in strengthening these associations. This data suggests that DTI smoothing enhances the sensitivity of studies of brain aging, but further research is needed to determine which smoothing technique is optimal.
We present a method that significantly improves magnetic resonance imaging (MRI) based brain tissue segmentation by modeling the topography of boundaries between tissue compartments. Edge operators are used to identify tissue interfaces and thereby more realistically model tissue label dependencies between adjacent voxels on opposite sides of an interface. When applied to a synthetic MRI template corrupted by additive noise, it provided more consistent tissue labeling across noise levels than two commonly used methods (FAST and SPM5). When applied to longitudinal MRI series it provided lesser variability in individual trajectories of tissue change, suggesting superior ability to discriminate real tissue change from noise. These results suggest that this method may be useful for robust longitudinal brain tissue change estimation.
The time and space complexities of Markov random field (MRF) algorithms for image segmentation increase with the number of edges that represent statistical dependencies between adjacent pixels. This has made MRFs too computationally complex for cutting-edge applications such as joint segmentation of longitudinal sequences of many high-resolution magnetic resonance images (MRIs). Here, we show that simply removing edges from full MRFs can reduce the computational complexity of MRF parameter estimation and inference with no notable decrease in segmentation performance. In particular, we show that for segmentation of white matter hyperintensities in 88 brain MRI scans of elderly individuals, as many as 66% of MRF edges can be removed without substantially degrading segmentation accuracy. We then show that removing edges from MRFs makes MRF parameter estimation and inference computationally tractable enough to enable modeling statistical dependencies within and across a larger number of brain MRI scans in a longitudinal series; this improves segmentation performance compared to separate segmentations of each individual scan in the series.
Identifying associations between the shape properties of brain regions, measured from magnetic resonance imaging (MRI), and numerical measures of neurodegenerative disease burden can clarify whether disease processes lead to distinctive spatial patterns of brain atrophy. However, prior methods for identifying such associations between shape and clinical variables either failed to summarize shape patterns into a concise set of summary measurements, or risked failing to discover such associations by extracting summary shape features blinded to the clinical variables. We present a method that overcomes these limitations by directly searching for a small set of linear shape features–shape regression components–that simultaneously account for a large amount of population shape variability and are highly correlated with a numerical clinical variable of interest. When applied to hippocampi of 299 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants, the method identified correlations between hippocampal atrophy and markers of AD pathology and cogniton that were stronger than, and covered a more extended spatial region than, those identified by competing approaches.
This study assessed relationships among white matter hyperintensities (WMH), cerebrospinal fluid (CSF), Alzheimer's disease (AD) pathology markers, and brain volume loss. Subjects included 197 controls, 331 individuals with mild cognitive impairment (MCI), and 146 individuals with AD with serial volumetric 1.5-T MRI. CSF Aβ1-42 (n = 351) and tau (n = 346) were measured. Brain volume change was quantified using the boundary shift integral (BSI). We assessed the association between baseline WMH volume and annualized BSI, adjusting for intracranial volume. We also performed multiple regression analyses in the CSF subset, assessing the relationships of WMH and Aβ1-42 and/or tau with BSI. WMH burden was positively associated with BSI in controls (p = 0.02) but not MCI or AD. In multivariable models, WMH (p = 0.003) and Aβ1-42 (p = 0.001) were independently associated with BSI in controls; in MCI Aβ1-42 (p < 0.001) and tau (p = 0.04) were associated with BSI. There was no evidence of independent effects of WMH or CSF measures on BSI in AD. These data support findings that vascular damage is associated with increased brain atrophy in the context of AD pathology in pre-dementia stages.
Alzheimer's disease; Vascular disease; Mild cognitive impairment (MCI); Volumetric MRI; Normal aging
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.
Hippocampal injury in the Alzheimer's Disease (AD) pathological process is region specific and MRI-based measures of localized hippocampus (HP) atrophy are known to detect region specific changes associated with clinical AD, but it is unclear whether these measures provide information that is independent of that already provided by measures of total HP volume. Therefore, this study assessed the strength of association between localized HP atrophy measures and AD-related measures including CSF amyloid beta and tau concentrations, and cognitive performance, in statistical models that also included total HP volume as a covariate. A computational technique termed localized components analysis (LoCA) was used to identify 7 independent patterns of HP atrophy among 390 semi-automatically delineated HP from baseline MRI of participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Among cognitively-normal participants, multiple measures of localized HP atrophy were significantly associated with CSF amyloid concentration, while total HP volume was not. In addition, among all ADNI participants, localized HP atrophy measures and total HP volume were both independently and additively associated with CSF tau concentration, performance on numerous neuropsychological tests, and discrimination between normal, MCI, and AD clinical diagnostic groups. Together, these results suggest that regional measures of hippocampal atrophy provided by LoCA may be more sensitive than total HP volume to the effects of AD pathology burden among cognitively normal individuals and may provide information about HP regions whose deficits may have especially profound cognitive consequences throughout the AD clinical course.
Hippocampus; Alzheimer's Disease; morphometry; biomarkers; shape analysis
Cerebral white matter lesions (WMLs) reflect small vessel disease, are common in elderly individuals and are associated with cognitive impairment. We sought to determine the relationships between WMLs, age, gray matter (GM) volume, and cognition in the Cardiovascular Health Study (CHS).
From the CHS we selected 740 cognitively normal controls with a 1.5 T MRI scan of the brain and a detailed diagnostic evaluation. WML severity was determined using a standardized visual rating system. GM volumes were analyzed using voxel-based morphometry implemented in the Statistical Parametric Mapping software.
WMLs were inversely correlated with GM volume, with the greatest volume loss in the frontal cortex. Age related atrophy was observed in the hippocampus and posterior cingulate cortex. Regression analyses revealed links among age, APOE*4 allele, hypertension, WMLs, GM volume, and digit symbol substitution test scores.
Both advancing age and hypertension predict higher WML load, which is itself associated with GM atrophy. Longitudinal data are needed to confirm the temporal sequence of events leading to a decline in cognitive function.
White matter lesions; age; gray matter volume; cognition
Trajectories of cognitive decline among elderly individuals are heterogeneous, and markers that have high reliability for predicting cognitive trajectories across a broad spectrum of the elderly population have yet to be identified.
This study examined the utility of a variety of MRI-based brain measures, obtained at baseline, as predictors of subsequent declines in domain-specific measures of cognitive function in a cohort of 307 community-dwelling elderly individuals with varying degrees of cognitive impairment who were diverse across a number of relevant demographic variables and were evaluated yearly. Psychometrically matched measures of cognition were used to assess episodic memory, semantic memory, and executive function. Relationships between baseline MRI measures, including the volumes of the brain, hippocampus, and white matter hyperintensities (WMH), and cognitive trajectories were assessed in mixed effects regression models that modeled MRI effects on cognitive performance at baseline and rate of change as well as inter-individual variability in cognitive baseline and rate of change.
Greater baseline brain volume predicted slower subsequent rate of decline in episodic memory and smaller WMH volume predicted slower subsequent rate of decline in executive function and semantic memory. Baseline hippocampal volume, while strongly related to baseline cognitive function, was not predictive of subsequent change in any of the cognitive domains.
Baseline measures of brain structure and tissue pathology predicted rate of cognitive decline in a diverse and carefully-characterized cohort, suggesting that they may provide summary measures of pre-existing neuropathological damage or the capacity of the brain to compensate for the impact of subsequent neuropathology on cognition. Conventional MRI measures may have utility for predicting cognitive outcomes in highly heterogeneous elderly populations.
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.
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.
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.
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.
National Institutes of Health and National Heart, Lung, and Blood Institute; National Institute on Aging; and National Institute of Neurological Disorders and Stroke.
Background and Purpose
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. DTI 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 neighbourhood.
208 participants from the University of California, Davis Alzheimer's Disease Center received a comprehensive clinical evaluation and brain MRI including FLAIR and DTI sequences. Voxel-wise maps of WMHs were produced from FLAIR using a standardized WMH detection protocol. Fractional anisotropy (FA) maps were calculated from DTI. All WMH and FA maps were coregistered to a standardized space. For each normal-appearing white matter voxel in each subject FLAIR scan, a neighbourhood WM injury (NWI) score was calculated that increased with increasing number and proximity of WMH in the vicinity of the voxel. FA was related to NWI using a nonlinear mixed effect model controlling for relevant confounding factors.
FA was found to decrease as NWI increased (β=-0.0017/%, p<0.0001) with an accelerated rate (p<0.0001). An increase of 1% in NWI score was associated with a decrease in mean FA of 0.012 (p<0.001).
WMH may represent foci of more widespread and subtle white matter changes rather than distinct, sharply-delineated anatomical abnormalities. We use the term white matter hyperintensities penumbra to explain this phenomenon.
Aging; Diffusion Tensor Imaging; Cerebrovascular Disease; White Matter Hyperintensity; Alzheimer Disease; Magnetic Resonance Imaging
The purpose of this study was to determine the pattern and extent of caudate nucleus and putamen atrophy in HIV-infected men with well-controlled immune status and viral replication. 155 men underwent structural brain magnetic resonance imaging; 84 were HIV-infected and 71 were uninfected controls. MRI data were processed using the Fully Deformable Segmentation routine, producing volumes for the right and left caudate nucleus and putamen, and 3-D maps of spatial patterns of thickness. There was significant atrophy in the HIV-infected men in both the caudate and putamen, principally in the anterior regions. The volume of the basal ganglia was inversely associated with the time since first seropositivity, suggesting that either there is a chronic, subclinical process that continues in spite of therapy, or that the extent of the initial insult caused the extent of atrophy.
HIV; MRI; Gray matter; Basal ganglia
Previous neuroimaging research indicates that white matter injury and integrity, measured respectively by white matter hyperintensities (WMH) and fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI), differ with aging and cerebrovascular disease (CVD) and are associated with episodic memory deficits in cognitively normal older adults. However, knowledge about tract-specific relationships between WMH, FA, and episodic memory in aging remains limited. We hypothesized that white matter connections between frontal cortex and subcortical structures as well as connections between frontal and temporo-parietal cortex would be most affected. In the current study, we examined relationships between WMH, FA and episodic memory in 15 young adults, 13 elders with minimal WMH and 15 elders with extensive WMH, using an episodic recognition memory test for object-color associations. Voxel-based statistics were used to identify voxel clusters where white matter measures were specifically associated with variations in episodic memory performance, and white matter tracts intersecting these clusters were analyzed to examine white matter-memory relationships. White matter injury and integrity measures were significantly associated with episodic memory in extensive regions of white matter, located predominantly in frontal, parietal, and subcortical regions. Template based tractography indicated that white matter injury, as measured by WMH, in the uncinate and inferior longitudinal fasciculi were significantly negatively associated with episodic memory performance. Other tracts such as thalamo-frontal projections, superior longitudinal fasciculus, and dorsal cingulum bundle demonstrated strong negative associations as well. The results suggest that white matter injury to multiple pathways, including connections of frontal and temporal cortex and frontal-subcortical white matter tracts, plays a critical role in memory differences seen in older individuals.
aging; cerebrovascular disease; magnetic resonance imaging; white matter hyperintensity; fractional anisotropy; structural connectivity; episodic memory; source memory
We examined in vivo evidence of axonal degeneration in association with neuronal pathology in Alzheimer’s disease (AD) through analysis of fornix microstructural integrity and measures of hippocampal subfield atrophy. Based on known anatomical topography, we hypothesized that the local thickness of subiculum and CA1 hippocampus fields would be associated with fornix integrity, reflecting an association between AD-related injury to hippocampal neurons and degeneration of associated axon fibers. To test this hypothesis, multi-modal imaging, combining measures of local hippocampal radii with diffusion tensor imaging (DTI), was applied to 44 individuals clinically diagnosed with AD, 44 individuals clinically diagnosed with mild cognitive impairment (MCI), and 96 cognitively normal individuals. Fornix microstructural degradation, as measured by reduced DTI-based fractional anisotropy (FA), was prominent in both MCI and AD, and was associated with reduced hippocampal volumes. Further, reduced fornix FA was associated with reduced anterior CA1 and antero-medial subiculum thickness. Finally, while both lesser fornix FA and lesser hippocampal volume were associated with lesser episodic memory, only the hippocampal measures were significant predictors of episodic memory in models including both hippocampal and fornix predictors. The region-specific association between fornix integrity and hippocampal neuronal death may provide in vivo evidence for degenerative white matter injury in AD: axonal pathology that is closely linked to neuronal injury.
hippocampus; fornix; fractional anisotropy; Alzheimer’s disease; mild cognitive impairment
To investigate associations between MRI brain morphology, cerebrovascular risk (VR), clinical diagnosis and cognition among elders living in urban Shanghai.
Memory Disorders Clinic and community normal control (NC) subject recruitment.
Ninety-six older subjects, 32 with normal cognition, 30 with amnestic MCI (aMCI) and 34 with dementia.
Main outcome measures
Each subject received medical history, neurological/physical exams, neuropsychological evaluations, brain MRI and apolipoprotein E-ε4 (APOE -ε4) genotype test. MRI volumes were assessed using a semi-automatic method.
Brain volume (BV) was significantly smaller in the demented compared with NC (p < 0.001) or aMCI (p = 0.043). Hippocampal volume (HV) was lower, and white matter hyperintensity volume (WMH) was higher, in aMCI (HV: p = 0.028; WMH: p = 0.041) and dementia (HV: p < 0.001; WMH: p = 0.002) compared with NC. APOE -ε4 presence was significantly associated with reduced HV (p = 0.02). Systolic blood pressure was positively associated with VR score (p = 0.037); diastolic blood pressure (p = 0.021) and VR score (p = 0.036) were both positively associated with WMH. WMH (p = 0.029) and VR (p = 0.031) were both higher among the demented than NC.
MRI brain morphology changes were significantly associated clinical diagnosis, in addition, blood pressure was highly associated with VR score and WMH. These results suggest that MRI is a valuable measure of brain injury in a Chinese cohort and can serve to assess the effects of various degenerative and cerebrovascular pathologies.
Dementia; Mild Cognitive Impairment; Magnetic Resonance Imaging; white matter hyperintensities; hippocampal volume; cerebrovascular risk; apolipoprotein E genotype; cognition
This study examined trajectories of cognitive change in psychometrically matched measures of episodic memory, semantic memory, and executive function in an ethnically, demographically, and cognitively diverse sample of older persons. Individual rates of change showed considerable heterogeneity in each domain. Baseline clinical diagnosis predicted differential change in semantic memory and executive function (dementia > mild cognitive impairment (MCI) > normal), but average decline in verbal episodic memory was similar across all three diagnostic groups. There was substantial overlap of distributions of cognitive change across baseline diagnostic groups for all three measures. Cognitive change was strongly related to change in clinical diagnosis. Rapid and similar change was present for all three cognitive measures in demented cases and in normals and cases with MCI who progressed clinically. In cognitively normal cases, verbal episodic memory change was greater than change in the other two domains. Global status, measured by the Clinical Dementia Rating scale, predicted change in semantic memory and executive function, while ApoE genotype predicted change in verbal episodic memory, and age had no effect on rates of change in any domain independent of global status and ApoE. Results show important limitations in using cross sectional diagnosis to predict prognosis, and suggest that research to identify robust predictors of cognitive change across the full spectrum from normal to dementia is needed for better early identification of diseases causing progressive decline.
Cognitive change; diagnosis; dementia; mild cognitive impairment; normal cognition; aging
Cerebrospinal fluid (CSF) and structural magnetic resonance imaging (MRI) show patterns of change in Alzheimer’s disease (AD) that precede dementia. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) studied normal controls (NC), subjects with mild cognitive impairment (MCI) and AD to identify patterns of biomarkers to aid in early diagnosis and effective treatment of AD.
222 NC underwent baseline MRI and clinical examination at baseline and at least one follow-up. 112 also provided CSF at baseline. Unsupervised clustering based on initial CSF and MRI measures was used to identify clusters of participants with similar profiles. Repeated measures regression modeling assessed the relationship of individual measures, and of cluster membership, to cognitive change over three years.
Most individuals showed little cognitive change. Individual biomarkers had limited predictive value for cognitive decline, but membership in the cluster with the most extreme profile was associated with more rapid decline in ADAS-COG.
Subtypes among NC based on multiple biomarkers may represent the earliest stages of subclinical cognitive decline and AD.
Alzheimer’s disease; Dementia; Early diagnosis; Cerebrospinal fluid; Tau protein; Amyloid beta-protein; Structural magnetic resonance imaging; Hippocampal volume; Cognition; Clustering; Normal controls
Background and Purpose
Despite the critical importance of the corpus callosum (CC) to the connection between brain hemispheres, little is known about the independent contribution of degenerative and vascular processes to regional changes in the microstructural integrity of the CC. Here, we examine these changes in subjects with mild cognitive impairment (MCI), Alzheimer's disease (AD), and in cognitively normal elderly adults.
We used three-dimensional brain MRI with diffusion tensor imaging in 47 AD, 77 MCI, and 107 cognitively normal subjects, and calculated mean fractional anisotropy (FA) values for four CC regions corresponding to four homologous regions of cortical gray matter (GM). To assess vascular and degenerative processes, we also measured cortical GM and white matter hyperintensity (WMH) volume in corresponding regions, along with evaluation of their vascular risk.
We found that GM volume in anterior and posterior regions was significantly related to FA findings in the corresponding regions of the CC for all three diagnostic groups. Independent of GM volume, frontal WMH volume was also associated with FA values in the corresponding CC regions, but posterior WMH volume was not. Vascular risk was associated with FA of most CC regions, while diagnosis for cognitive state was associated only with FA of the anterior and posterior CC regions.
We found differential region-specific associations between degenerative and vascular processes and the structural integrity of the CC across the spectrum of cognitive ability. Based on these results, we propose a model to explain regional disruption in the interhemispheric connection.
Alzheimer's disease; cerebrovascular disorders; mild cognitive impairment; corpus callosum; diffusion tensor imaging
To evaluate relationships between magnetic resonance imaging (MRI)–based measures of white matter hyperintensities (WMHs), measured at baseline and longitudinally, and 1-year cognitive decline using a large convenience sample in a clinical trial design with a relatively mild profile of cardiovascular risk factors.
Convenience sample in a clinical trial design.
A total of 804 participants in the Alzheimer Disease Neuroimaging Initiative who received MRI scans, cognitive testing, and clinical evaluations at baseline, 6-month follow-up, and 12-month follow-up visits. For each scan, WMHs were detected automatically on coregistered sets of T1, proton density, and T2 MRI images using a validated method. Mixed-effects regression models evaluated relationships between risk factors for WMHs, WMH volume, and change in outcome measures including Mini-Mental State Examination (MMSE), Alzheimer Disease Assessment Scale–Cognitive Subscale (ADAS-Cog), and Clinical Dementia Rating Scale sum of boxes scores. Covariates in these models included race, sex, years of education, age, apolipoprotein E genotype, baseline clinical diagnosis (cognitively normal, mild cognitive impairment, or Alzheimer disease), cardiovascular risk score, and MRI-based hippocampal and brain volumes.
Higher baseline WMH volume was associated with greater subsequent 1-year increase in ADAS-Cog and decrease in MMSE scores. Greater WMH volume at follow-up was associated with greater ADAS-Cog and lower MMSE scores at follow-up. Higher baseline age and cardiovascular risk score and more impaired baseline clinical diagnosis were associated with higher baseline WMH volume.
White matter hyperintensity volume predicts 1-year cognitive decline in a relatively healthy convenience sample that was similar to clinical trial samples, and therefore should be considered as a covariate of interest at baseline and longitudinally in future AD treatment trials.