Whether longitudinal diffusion tensor MRI imaging (DTI) can capture disease progression in patients with amyotrophic lateral sclerosis (ALS) is unclear. The primary goal of this study was to determine if DTI detects progression of the corticospinal tracts (CST) degeneration in ALS. Seventeen ALS patients and 19 age- and gender-matched healthy controls were scanned with DTI at baseline for cross-sectional analyses. For longitudinal analyses, the ALS patients had repeat DTI scans after eight months. Tractography of the CST was used to guide regions-of-interest (ROI) analysis and complemented by a voxelwise analysis. Cross-sectional study found that baseline FA of the right superior CST was markedly reduced in ALS patients compared to controls. The FA reductions in this region correlated with the disease severity in ALS patients. Longitudinal study found that FA change rate of the right superior CST significantly declined over time. In conclusion, longitudinal DTI study captures progression of upper motor fiber degeneration in ALS. DTI can be useful for monitoring ALS progression and efficacy of treatment interventions.
Amyotrophic lateral sclerosis; diffusion tensor imaging; longitudinal study; corticospinal tracts; brain MRI
The Dominantly Inherited Alzheimer Network (DIAN) is a collaborative effort of international Alzheimer disease (AD) centers that are conducting a multifaceted prospective biomarker study in individuals at-risk for autosomal dominant AD (ADAD). DIAN collects comprehensive information and tissue in accordance with standard protocols from asymptomatic and symptomatic ADAD mutation carriers and their non-carrier family members to determine the pathochronology of clinical, cognitive, neuroimaging, and fluid biomarkers of AD. This article describes the structure, implementation, and underlying principles of DIAN, as well as the demographic features of the initial DIAN cohort.
Alzheimer disease; autosomal dominant; biomarkers of Alzheimer disease; PSEN1; PSEN2; APP; amyloid-beta; preclinical Alzheimer disease
Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) population, we examined (1) cross-sectional relationships between amyloid deposition, hypometabolism, and cognition, and (2) associations between amyloid and hypometabolism measurements and longitudinal cognitive measurements.
We examined associations between mean cortical florbetapir uptake, mean 18F-fluorodeoxyglucose–positron emission tomography (FDG-PET) within a set of predefined regions, and Alzhiemer’s Disease Assessment Scale (ADAS-cog) performance in 426 ADNI participants (126 normal, 162 early mild cognitive impairment [EMCI], 85 late MCI [LMCI], 53 Alzheimer disease [AD] patients). For a subset of these (76 normal, 81 LMCI) we determined whether florbetapir and FDG-PET were associated with retrospective decline in longitudinal ADAS-cog measurements.
Twenty-nine percent of normal subjects, 43% of EMCI patients, 62% of LMCI patients, and 77% of AD patients were categorized as florbetapir positive. Florbetapir was negatively associated with concurrent FDG and ADAS-cog in both MCI groups. In longitudinal analyses, florbetapir-positive subjects in both normal and LMCI groups had greater ongoing ADAS-cog decline than those who were florbetapir negative. However, in normal subjects, florbetapir positivity was associated with greater ADAS-cog decline than FDG, whereas in LMCI, FDG positivity was associated with greater decline than florbetapir.
Although both hypometabolism and β-amyloid (Aβ) deposition are detectable in normal subjects and all diagnostic groups, Aβ showed greater associations with cognitive decline in normal participants. In view of the minimal cognitive deterioration overall in this group, this suggests that amyloid deposition has an early and subclinical impact on cognition that precedes metabolic changes. At moderate and later stages of disease (LMCI/AD), hypometabolism becomes more pronounced and more closely linked to ongoing cognitive decline.
Beta-amyloid (Aβ) is a histopathological hallmark of Alzheimer’s disease dementia, but high levels of Aβ in the brain can also be found in a substantial proportion of nondemented subjects. Here we investigated which 2-year rate of brain and cognitive changes are present in nondemented subjects with high and low Aβ levels, as assessed with cerebrospinal fluid and molecular positron emission tomography (PET)–based biomarkers of Aβ. In subjects with mild cognitive impairment, increased brain Aβ levels were associated with significantly faster cognitive decline, progression of gray matter atrophy within temporal and parietal brain regions, and a trend for a faster decline in parietal Fludeoxyglucose (FDG)-PET metabolism. Changes in gray matter and FDG-PET mediated the association between Aβ and cognitive decline. In contrast, elderly cognitively healthy controls (HC) with high Aβ levels showed only a faster medial temporal lobe and precuneus volume decline compared with HC with low Aβ. In conclusion, the current results suggest not only that both functional and volumetric brain changes are associated with high Aβ years before the onset of dementia but also that HC with substantial Aβ levels show higher Aβ pathology resistance, lack other pathologies that condition neurotoxic effects of Aβ, or accumulated Aβ for a shorter time period.
Aβ; FDG-PET; MCI; PIB-PET
Brain magnetic resonance imaging (MRI) studies have demonstrated regional patterns of brain macrostructural atrophy and white matter microstructural alterations separately in the three major subtypes of frontotemporal lobar degeneration (FTLD), which includes behavioral variant frontotemporal dementia (bvFTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). This study was to investigate to what extent the pattern of white matter microstructural alterations in FTLD subtypes mirrors the pattern of brain atrophy, and to compare the ability of various diffusion tensor imaging (DTI) indices in characterizing FTLD patients, as well as to determine whether DTI measures provide greater classification power for FTLD than measuring brain atrophy. Twenty-five patients with FTLD (13 with bvFTD, 6 with SD, and 6 with PNFA) and 19 healthy age-matched control subjects underwent both structural MRI and DTI scans. Measurements of regional brain atrophy were based on T1-weighted MRI data and voxel-based morphometry. Measurements of regional white matter degradation were based on voxelwise as well as regions-of-interest tests of DTI variations, expressed as fractional anisotropy, axial diffusivity, and radial diffusivity. Compared to controls, bvFTD, SD, and PNFA patients each exhibited characteristic regional patterns of brain atrophy and white matter damage. DTI overall provided significantly greater accuracy for FTLD classification than brain atrophy. Moreover, radial diffusivity was more sensitive in assessing white matter damage in FTLD than other DTI indices. The findings suggest that DTI in general and radial diffusivity in particular are more powerful measures for the classification of FTLD patients from controls than brain atrophy.
Behavioral variant frontotemporal dementia; diffusion tensor imaging; frontotemporal lobar degeneration; multimodality MRI; progressive nonfluent aphasia; semantic dementia
To evaluate the degree to which longitudinal stability of subsyndromal symptoms of depression (SSD) is associated with conversion to dementia in patients with Mild Cognitive Impairment (MCI).
Data from 405 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Participants were evaluated at baseline and 12 month intervals over three years. Participants were designated as MCI Converters if dementia was diagnosed within 3 years or as Cognitively Stable MCI if dementia was not diagnosed during this interval. SSD were evaluated utilizing the 15-item Geriatric Depression Scale (GDS). Endorsement of specific SSD at baseline and the stability of SSD over 36 months were compared between the two MCI groups.
Baseline symptom endorsement and stability of total GDS scores did not differentiate MCI groups. Worsening of 4 individual items from the GDS over time (memory problems, feelings of helplessness, loss of interest, and preference for staying at home) differentiated MCI converters from cognitively stable MCI (p <0.05 for all). However, only increased endorsement of memory symptoms over time was associated with progression to dementia after controlling for other clinical variables (p=0.05).
SSD in MCI participants largely consist of cognitive symptoms and activity limitations and the stability of SSD over time differentiated the MCI groups better than baseline endorsement of symptoms. However, the only significant predictor of conversion to dementia was increased endorsement of memory problems, which likely represents insight into cognitive problems more than depressive symptomatology in MCI individuals.
subsyndromal depression; longitudinal stability; mild cognitive impairment; insight; dementia
There is epidemiological evidence that cardiovascular risk factors (CVRF) also are risk factors for Alzheimer’s disease, but there is limited information on this from neuro-pathological studies, and even less from in vivo studies. Therefore, we examined the relationship between CVRF and amyloid-β (Aβ) brain burden measured by Pittsburgh Compound B-positron emission tomography (PiB-PET) studies in the Alzheimer’s Disease Neuroimaging Initiative.
Ninety-nine subjects from the Alzheimer’s Disease Neuroimaging Initiative cohort who had a PiB-PET study measure, apolipoprotein E genotyping data, and information available on CVRF (body mass index [BMI], systolic blood pressure, diastolic blood pressure [DBP1 and cholesterol and fasting glucose test results) were included. Eighty-one subjects also had plasma cortisol C-reactive protein, and superoxide dismutase 1 measurements. Stepwise regression models were used to assess the relation between the CVRF and the composite PiB-PET score.
The first model included the following as baseline variables: age, clinical diagnosis, number of apolipoprotein ε4 alleles, BMI (P = .023), and DBP (P = .012). BMI showed an inverse relation with PiB-PET score, and DBP had a positive relation with PiB-PET score. In the second adjusted model, cortisol plasma levels were also associated with PiB-PET score (P = .004). Systolic blood pressure, cholesterol, or impaired fasting glucose were not found to be associated with PiB-PET values.
In this cross-sectional study, we found an association between Aβ brain burden measured in vivo and DBP and cortisol, indicating a possible link between these CVRF and Aβ burden measured by PiB-PET. These findings highlight the utility of biomarkers to explore potential pathways linking diverse Alzheimer’s disease risk factors.
Alzheimer disease; Vascular risk factors; PiB; Amyloid-β; Cortisol; Blood pressure; Body mass index
The hippocampal formation (HF) is a brain structure of great interest because of its central role in learning and memory, and its associated vulnerability to several neurological disorders. In vivo oblique coronal T2-weighted MRI with high in-plane resolution (~0.5 mm×0.5 mm), thick slices (~2.0 mm), and a field of view tailored to imaging the hippocampal formation (denoted HF-MRI in this paper) has been advanced as a useful imaging modality for detailed hippocampal morphometry. Cross-sectional analysis of volume measurements derived from HF-MRI has shown the modality’s promise to yield sensitive imaging-based biomarker for neurological disorders such as Alzheimer’s disease. However, the utility of this modality for making measurements of longitudinal change has not yet been demonstrated. In this paper, using an unbiased deformation-based morphometry (DBM) pipeline, we examine the suitability of HF-MRI for estimating longitudinal change by comparing atrophy rates measured in the whole hippocampus from this modality with those measured from more common isotropic (~1 mm3) T1-weighted MRI in the same set of individuals, in a cohort of healthy controls and patients with cognitive impairment. While measurements obtained from HF-MRI were largely consistent with those obtained from T1-MRI, HF-MRI yielded slightly larger group effect of greater atrophy rates in patients than in controls. The estimated minimum sample size required for detecting a 25% change in patients’ atrophy rate in the hippocampus compared to the control group with a statistical power β=0.8 was N=269. For T1-MRI, the equivalent sample size was N=325. Using a dataset of test–retest scans, we show that the measurements were free of additive bias. We also demonstrate that these results were not a confound of certain methodological choices made in the DBM pipeline to address the challenges of making longitudinal measurements from HF-MRI, using a region of interest (ROI) around the HF to globally align serial images, followed by slice-by-slice deformable registration to measure local volume change. Additionally, we present a preliminary study of atrophy rate measurements within hippocampal subfields using HF-MRI. Cross-sectional differences in atrophy rates were detected in several subfields.
Hippocampus; Subfields; T1-weighted; T2-weighted; MRI; Longitudinal; Atrophy; MCI; Evaluation; Medial temporal lobe; Deformation-based morphometry; DBM sample size
The goal was to elucidate the time course of regional brain atrophy rates relative to age in cognitively normal (CN) aging, mild cognitively impairment (MCI) and Alzheimer’s disease (AD), without a-priori models for atrophy progression. Regional brain volumes from 147 CN subjects, 164 stable MCI, 93 MCI-to-AD converters and 111 AD patients, between 51 to 91 years old and who had repeated 1.5T magnetic resonance imaging (MRI) scans over 30 months, were analyzed. Relations between regional brain volume change and age were determined using generalized additive models, an established non-parametric concept for approximating nonlinear relations. Brain atrophy rates varied nonlinearly with age, predominantly in regions of the temporal lobe. Moreover, the atrophy rates of some regions leveled off with increasing age in control and stable MCI subjects whereas those rates progressed further in MCI-to-AD converters and AD patients. The approach has potential uses for early detection of AD and differentiation between stable and progressing MCI.
Alzheimer’s disease; mild cognitive impairment; aging; brain atrophy; hippocampus; magnetic resonance imaging; generalized additive models
The present study evaluated cerebrovascular disease (CVD), β-amyloid (Aβ), and cognition in clinically normal elderly adults. Fifty-four participants underwent MRI, PIB-PET imaging, and neuropsychological evaluation. High white matter hyperintensity burden and/or presence of infarct defined CVD status (CVD−: N = 27; CVD+: N = 27). PIB-PET ratios of Aβ deposition were extracted using Logan plotting (cerebellar reference). Presence of high levels of Aβ in prespecified regions determined PIB status (PIB−: N = 33; PIB+: N = 21). Executive functioning and episodic memory were measured using composite scales. CVD and Aβ, defined as dichotomous or continuous variables, were unrelated to one another. CVD+ participants showed lower executive functioning (P = 0.001) when compared to CVD− individuals. Neither PIB status nor amount of Aβ affected cognition (Ps ≥ .45), and there was no statistical interaction between CVD and PIB on either cognitive measure. Within this spectrum of normal aging CVD and Aβ aggregation appear to be independent processes with CVD primarily affecting cognition.
PIB; cerebrovascular disease; episodic memory; executive functioning; cognition
White matter hyperintensities (WMH) and silent brain infarcts (SBI) have been associated with both vascular factors and cognitive decline. We examined among cognitively normal elderly, whether vascular factors predict cognitive decline and whether these associations are mediated by MRI measures of subclinical vascular brain injury.
Prospective multi-site longitudinal study of subcortical ischemic vascular diseases
Memory and aging centers in California
We studied 74 participants who were cognitively normal at entry and received at least 2 neuropsychological evaluations and 2 MRI exams over an average follow-up of 6.9 years.
Item response theory was used to create composite scores of global, verbal memory, and executive functioning. Volumetric MRI measures included WMH, SBI, hippocampus, and cortical gray matter (CGM). We used linear mixed effects models to examine the associations between vascular factors, MRI measures, and cognitive scores.
History of coronary artery disease (CAD) was associated with greater declines in global, verbal memory, and executive cognition. The CAD associations remained after controlling for changes in WMH, SBI, hippocampal and CGM volumes.
History of CAD may be a surrogate marker for clinically significant atherosclerosis which also affects the brain. Structural MRI measures of WMH and SBI do not fully capture the potential adverse effects of atherosclerosis on the brain. Future longitudinal studies of cognition should incorporate direct measures of atherosclerosis in cerebral arteries, as well as more sensitive neuroimaging measures.
cognitively normal elderly; coronary artery disease; cognitive decline; MRI
Magnetic Resonance Imaging (MRI) provides various imaging modes to study the brain. We tested the benefits of a joint analysis of multimodality MRI data in combination with a large-scale analysis that involved simultaneously all image voxels using joint independent components analysis (jICA) and compared the outcome to results using conventional voxel-by-voxel unimodality tests. Specifically, we designed a jICA to decompose multimodality MRI data into independent components that explain joint variations between the image modalities as well as variations across brain regions. We tested the jICA design on structural and perfusion-weighted MRI data from 12 patients diagnosed with behavioral variant frontotemporal dementia (bvFTD) and 12 cognitively normal elderly individuals. While unimodality analyses showed widespread brain atrophy and hypoperfusion in the patients, jICA further revealed two significant joint components of variations between atrophy and hypoperfusion across brain regions. The 1st joint component revealed associated brain atrophy and hypoperfusion predominantly in the right brain hemisphere in behavioral variant frontotemporal dementia, and the 2nd joint component revealed greater atrophy relative to hypoperfusion affecting predominantly the left hemisphere in behavioral variant frontotemporal dementia. The patterns are consistent with the clinical symptoms of behavioral variant frontotemporal dementia that relate to asymmetric compromises of the left and right brain hemispheres. The joint components also revealed that that structural alterations can be associated with physiological alterations in spatially separated but potentially connected brain regions. Finally, jICA outperformed voxel-by-voxel unimodal tests significantly in terms of an effect size, separating the behavioral variant frontotemporal dementia patients from the controls. Taken together, the results demonstrate the benefit of multimodality MRI in conjunction with jICA for mapping neurodegeneration, which may lead ultimately to an improved diagnosis of behavioral variant frontotemporal dementia and other forms of neurodegenerative diseases.
Brain atrophy; Brain hypoperfusion; Dementia; Neurodegenerative diseases; Joint ICA; Multimodality MRI
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD and 200 normal controls and $67 million funding was provided by both the public and private sectors including the National Institutes on Aging, thirteen pharmaceutical companies and two Foundations that provided support through the Foundation for NIH (FNIH). This article reviews all papers published since the inception of the initiative and summarizes the results as of February, 2011. The major accomplishments of ADNI have been 1) the development of standardized methods for clinical, magnetic resonance imaging (MRI) and positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a multi-center setting; 2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control, MCI and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β amyloid (Aβ) cascade  and tau mediated neurodegeneration hypotheses for AD while brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; 3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities including MRI, FDG-PET, CSF biomarkers and clinical tests; 4) the development of methods for the early detection of AD. CSF biomarkers, Aβ42 and tau as well as amyloid PET may reflect the earliest steps in AD pathology in mildly or even non-symptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; 5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities whereas MRI measures of change were shown to be the most efficient outcome measures; 6) the confirmation of the AD risk loci CLU, CR1 and PICALM and the identification of novel candidate risk loci; 7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia and Australia; 8) understanding the biology and pathobiology of normal aging, MCI and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD thereby advancing efforts to find disease modifying drugs for AD; and 9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a two year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI2) in October, 2010 through to 2016, with enrollment of an additional 550 participants.
Penalized or sparse regression methods are gaining increasing attention in imaging genomics, as they can select optimal regressors from a large set of predictors whose individual effects are small or mostly zero. We applied a multivariate approach, based on L1-L2-regularized regression (elastic net) to predict a magnetic resonance imaging (MRI) tensor-based morphometry-derived measure of temporal lobe volume from a genome-wide scan in 740 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects. We tuned the elastic net model’s parameters using internal crossvalidation and evaluated the model on independent test sets. Compared to 100,000 permutations performed with randomized imaging measures, the predictions were found to be statistically significant (p ~ 0.001). The rs9933137 variant in the RBFOX1 gene was a highly contributory genotype, along with rs10845840 in GRIN2B and rs2456930, discovered previously in a univariate genomewide search.
Neuroimaging; MRI; Prediction; Elastic net; Imaging Genetics
Alzheimer’s Disease (AD) has long been considered a cortical degenerative disease, but impaired brain connectivity, due to white matter injury, may exacerbate cognitive problems. Predicting brain changes is critically important for early treatment. In a longitudinal diffusion tensor imaging study, we investigated white matter fiber integrity in 19 patients (mean age: 74.7 +/− 8.4 yrs at baseline) displaying early signs of mild cognitive impairment (eMCI). We first examined whether baseline average fractional anisotropy (FA) measures in the corpus callosum (CC) predicted changes in white matter integrity over the following 6 months. We then examined whether “small world” architecture measures - calculated from baseline connectivity maps - predicted white matter changes over the next 6 months. While average CC FA measures at baseline were not associated with future changes in FA, network measures were a sensitive biomarker for predicting white matter changes during this critical time before AD strikes.
diffusion imaging; graph theory; connectivity; predictive models; Alzheimer’s disease
Objective: Our goal was to evaluate the association of APOE with amyloid deposition, cerebrospinal fluid levels (CSF) of Aβ, tau, and p-tau, brain atrophy, cognition and cognitive complaints in E-MCI patients and cognitively healthy older adults (HC) in the ADNI-2 cohort.
Methods: Two-hundred and nine E-MCI and 123 HC participants from the ADNI-2 cohort were included. We evaluated the impact of diagnostic status (E-MCI vs. HC) and APOE ε4 status (ε4 positive vs. ε4 negative) on cortical amyloid deposition (AV-45/Florbetapir SUVR PET scans), brain atrophy (structural MRI scans processed using voxel-based morphometry and Freesurfer version 5.1), CSF levels of Aβ, tau, and p-tau, and cognitive performance and complaints.
Results: E-MCI participants showed significantly impaired cognition, higher levels of cognitive complaints, greater levels of tau and p-tau, and subcortical and cortical atrophy relative to HC participants (p < 0.05). Cortical amyloid deposition and CSF levels of Aβ were significantly associated with APOE ε4 status but not E-MCI diagnosis, with ε4 positive participants showing more amyloid deposition and lower levels of CSF Aβ than ε4 negative participants. Other effects of APOE ε4 status on cognition and CSF tau levels were also observed.
APOE ε4 status is associated with amyloid accumulation and lower CSF Aβ, as well as increased CSF tau levels in early prodromal stages of AD (E-MCI) and HC. Alternatively, neurodegeneration, cognitive impairment, and increased complaints are primarily associated with a diagnosis of E-MCI. These findings underscore the importance of considering APOE genotype when evaluating biomarkers in early stages of disease.
apolipoprotein E (APOE); early mild cognitive impairment (E-MCI); Florbetapir/AV-45/Amyvid; positron emission tomography (PET); magnetic resonance imaging (MRI); cerebrospinal fluid (CSF); Alzheimer's disease neuroimaging initiative (ADNI)
Patients with corticobasal degeneration (CBD) pathology present with diverse clinical syndromes also associated with other neuropathologies, including corticobasal syndrome, progressive nonfluent aphasia, and an Alzheimer’s-type dementia. Some present with behavioral variant frontotemporal dementia (bvFTD), though this subtype still requires more detailed phenotypic characterization. All patients with CBD pathology and clinical assessment were reviewed (N=17) and selected if they initially met criteria for bvFTD [bvFTD(CBD): N=5]. Available bvFTD patients with Pick’s [bvFTD(Pick’s): N=5] were selected as controls. Patients were also compared to healthy older controls [N=53] on neuropsychological and neuroimaging measures. At initial presentation, bvFTD(CBD) showed few neuropsychological or motor differences from bvFTD(Pick’s). Neuropsychiatrically, they were predominantly apathetic with less florid social disinhibition and eating disturbances, and were more anxious than bvFTD(Pick’s) patients. Voxel-based morphometry revealed similar patterns of predominantly frontal atrophy between bvFTD groups, though overall degree of atrophy was less severe in bvFTD(CBD), who also showed comparative preservation of the frontoinsular rim, with dorsal > ventral frontal atrophy, and sparing of temporal and parietal structures relative to bvFTD(Pick’s) patients. Despite remarkable overlap between the two patient types, bvFTD patients with underlying CBD pathology show subtle clinical features that may distinguish them from patients with Pick’s disease neuropathology.
Corticobasal degeneration; frontotemporal dementia; behavior; neuropsychiatry; neuropsychology; neuropathology
Histopathological studies and animal models suggest that hippocampal subfields may be differently affected by aging, Alzheimer’s disease (AD), and other diseases. High-resolution images at 4 Tesla depict details of the internal structure of the hippocampus allowing for in vivo volumetry of different subfields. The aims of this study were as follows: (1) to determine patterns of volume loss in hippocampal subfields in normal aging, AD, and amnestic mild cognitive impairment (MCI). (2) To determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for differentiation between groups.
Ninety-one subjects (53 controls (mean age: 69.3 ± 7.3), 20 MCI (mean age: 73.6 ± 7.1), and 18 AD (mean age: 69.1 ± 9.5) were studied with a high-resolution T2 weighted imaging sequence aimed at the hippocampus. Entorhinal cortex (ERC), subiculum, CA1, CA1–CA2 transition zone (CA1-2), CA3 & dentate gyrus (CA3&DG) were manually marked in the anterior third of the hippocampal body. Hippocampal volume was obtained from the Freesurfer and manually edited.
Compared to controls, AD had smaller volumes of ERC, subiculum, CA1, CA1-2, and total hippocampal volumes. MCI had smaller CA1-2 volumes. Discriminant analysis and power analysis showed that CA1-2 was superior to total hippocampal volume for distinction between controls and MCI.
The patterns of subfield atrophy in AD and MCI were consistent with patterns of neuronal cell loss/reduced synaptic density described by histopathology. These preliminary findings suggest that hippocampal subfield volumetry might be a better measure for diagnosis of early AD and for detection of other disease effects than measurement of total hippocampus.
hippocampal subfields; Alzheimer’s disease; manual parcellation; MRI
The goal of this study was to determine whether PTSD was associated with an increase in time-related decline in macrostructural brain volume and whether these changes were associated with accelerated cognitive decline. To quantify brain structure, 3 dimensional T1-weighted MRI scans were performed at baseline and again after a minimum of 24 months in 25 patients with PTSD and 22 controls. Longitudinal changes in brain volume were measured using deformation morphometry. For the group as a whole PTSD+ patients did not show significant ongoing brain atrophy compared to PTSD-. PTSD+ patients were then subgrouped into those with decreasing or increasing symptoms. We found little evidence for brain markers of accelerated atrophy in PTSD+ veterans whose symptoms improved over time, with only a small left parietal region showing greater ongoing tissue loss than PTSD-. PTSD patients whose symptoms increased over time showed accelerated atrophy throughout the brain, particularly brainstem and frontal and temporal lobes. Lastly, for the sample as a whole greater rates of brain atrophy were associated with greater rates of decline in verbal memory and delayed facial recognition.
deformation morphometry; longitudinal; MRI; neuropsychological testing; PTSD; Vietnam veterans
Alzheimer’s disease (AD) is a progressive age-related neurodegenerative disease. At the time of clinical manifestation of dementia, significant irreversible brain damage is already present, rendering the diagnosis of AD at early stages of the disease an urgent prerequisite for therapeutic treatment to halt, or at least slow, disease progression. In this Review, we discuss various neuroimaging measures that are proving to have potential value as biomarkers of AD pathology for the detection and prediction of AD before the onset of dementia. Recent studies that have identified AD-like structural and functional brain changes in elderly people who are cognitively within the normal range or who have mild cognitive impairment (MCI) are discussed. A dynamic sequence model of changes that occur in neuroimaging markers during the different disease stages is presented and the predictive value of multimodal neuroimaging for AD dementia is considered.
The Functional Activities Questionnaire (FAQ) and Alzheimer’s Disease Assessment Scale – cognitive subscale (ADAS-cog) are frequently-used indices of cognitive decline in Alzheimer’s disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Additionally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.
FDG-PET; Alzheimer’s disease; Mild Cognitive Impairment
Hippocampal sclerosis (HS) is a common and often asymmetric neuropathological finding among elderly persons who experience progressive memory loss, but its cause is unknown and it is rarely diagnosed during life. In order to improve both understanding and diagnosis of late-life HS, bilateral hippocampi and cerebral hemispheres were reviewed in 130 consecutive autopsy cases drawn from a longitudinal study of subjects with subcortical ischemic vascular dementia (IVD), Alzheimer disease (AD) and normal aging. HS was found in 31 of 130 cases (24.5%). Of these, 45% were bilateral, 32% left-sided, and 23% right-sided. The majority of HS cases involved the entire rostral-caudal extent of the hippocampus. However, in 7 cases HS was focal in nature and was only found at or anterior to the lateral geniculate nucleus. In 77% of cases, HS was accompanied by other types of pathology (‘mixed’ HS), but in 23% of cases it was the sole neuropathologic finding (‘pure’ HS). TDP-43-positive cytoplasmic inclusions were found in dentate granule cells in 93% of all HS cases, 55% of AD cases with no HS, but 0% of IVD cases with no HS. MRI hippocampal volumes were significantly lower in bilateral HS compared to AD (p < 0.001) and in unilateral HS cases compared to cases with intact hippocampi (p < 0.001). Since HS may occur unilaterally in approximately a quarter of cases, its prevalence may be underestimated if only one cerebral hemisphere is examined. The presence of TDP-43 inclusions in HS cases, regardless of accompanying pathologies (e.g., AD, IVD, FTLD), is consistent with an underlying neurodegenerative pathogenetic mechanism. Further studies are warranted to determine whether greater severity of hippocampal atrophy on MRI may assist the clinical differentiation of HS from AD.
Hippocampal volume; MRI; neurology; neuroscience; TDP-43
Imaging traits provide a powerful and biologically relevant substrate to examine the influence of genetics on the brain. Interest in genome-wide, brain-wide search for influential genetic variants is growing, but has mainly focused on univariate, SNP-based association tests. Moving to gene-based multivariate statistics, we can test the combined effect of multiple genetic variants in a single test statistic. Multivariate models can reduce the number of statistical tests in gene-wide or genome-wide scans and may discover gene effects undetectable with SNP-based methods. Here we present a gene-based method for associating the joint effect of single nucleotide polymorphisms (SNPs) in 18,044 genes across 31,662 voxels of the whole brain in 731 elderly subjects (mean age: 75.56 ± 6.82SD years; 430 males) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. Using the voxel-level volume difference values as the phenotype, we selected the most significantly associated gene (out of 18,044) at each voxel across the brain. No genes identified were significant after correction for multiple comparisons, but several known candidates were re-identified, as were other genes highly relevant to brain function. GAB2, which has been previously associated with late-onset AD, was identified as the top gene in this study, suggesting the validity of the approach. This multivariate, gene-based voxelwise association study offers a novel framework to detect genetic influences on the brain.
principal components regression; voxelwise; multivariate; gene-based; GWAS; GAB2 (max. 6 keywords)
Elevated homocysteine levels are a known risk factor for Alzheimer’s disease and vascular disorders. Here we applied tensor-based morphometry to brain magnetic resonance imaging scans of 732 elderly individuals from the Alzheimer’s Disease Neuroimaging Initiative study, to determine associations between homocysteine and brain atrophy. Those with higher homocysteine levels showed greater frontal, parietal, and occipital white matter atrophy in the entire cohort, irrespective of diagnosis, age, or sex. This association was also found when considering mild cognitive impairment individuals separately. Vitamin B supplements, such as folate, may help prevent homocysteine-related atrophy in Alzheimer’s disease by possibly reducing homocysteine levels. These atrophy profiles may, in the future, offer a potential biomarker to gauge the efficacy of interventions using dietary folate supplementation.
Alzheimer’s disease; atrophy; brain structure; folate; homocysteine; magnetic resonance imaging; vitamin B