The definitive Alzheimer’s disease diagnosis requires post-mortem confirmation of neuropathological hallmarks – amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs). The advent of radiotracers for amyloid imaging presents an opportunity to investigate amyloid deposition in vivo. The 11C-Pittsburgh Compound-B (PiB) PET ligand remains the most widely studied to date; however, regional variations in 11C-PiB binding and the extent of agreement with neuropathological assessment have not been thoroughly investigated. We examined the correspondence among quantitative immunohistological assessments of Aβ and NFTs, regional 11C-PiB load, and brain atrophy (MRI) in six older Baltimore Longitudinal Study of Aging participants who came to autopsy (imaging-autopsy interval range 0.2–2.4 years). The total number of Aβ plaques (6E10) and NFTs (PHF1) in paraffin sections from hippocampus, orbito-frontal cortex, anterior and posterior cingulate gyrus, precuneus and cerebellum were quantified using a technique guided by unbiased stereological principles. We report a general agreement between the regional measures of amyloid obtained via stereological assessment and imaging, with significant relationships evident for the anterior (r=0.87; p=0.02) and posterior (r=0.93; p=0.007) cingulate gyri, and the precuneus (r=0.98; p=0.001). Moreover, higher Aβ count in the hippocampus was associated with lower hippocampal volume (r= −0.86; p=0.03). No associations were observed between 11C-PiB load and NFT count for any of the regions examined (p>0.2 in all regions) or between regional NFT count and corresponding brain volumes. The strong associations of PiB retention with region-matched, quantitative analyses of Aβ in post-mortem tissue offer support for the validity of 11C-PiB-PET imaging as a method for evaluation of plaque burden in vivo.
plaques; tangles; stereology; PiB; Alzheimer; neuroimaging
The goal of this work is to introduce new metrics to assess risk of Alzheimer's disease (AD) which we call AD Pattern Similarity (AD-PS) scores. These metrics are the conditional probabilities modeled by large-scale regularized logistic regression. The AD-PS scores derived from structural MRI and cognitive test data were tested across different situations using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The scores were computed across groups of participants stratified by cognitive status, age and functional status. Cox proportional hazards regression was used to evaluate associations with the distribution of conversion times from mild cognitive impairment to AD. The performances of classifiers developed using data from different types of brain tissue were systematically characterized across cognitive status groups. We also explored the performance of anatomical and cognitive-anatomical composite scores generated by combining the outputs of classifiers developed using different types of data. In addition, we provide the AD-PS scores performance relative to other metrics used in the field including the Spatial Pattern of Abnormalities for Recognition of Early AD (SPARE-AD) index and total hippocampal volume for the variables examined.
Although MRI detected white matter disease has been correlated with cognitive decline in the elderly, it is unclear whether white matter disease is primarily responsible for the cognitive deterioration or whether another process is common to white matter disease and dementia.
We examined the relationship between Alzheimer type brain pathology at autopsy and MRI detected cerebral white matter disease in 50 participants from the Baltimore Longitudinal Study of Aging (BLSA) Autopsy Program, a prospective study of aging which includes detailed cognitive assessments.
White matter disease was quantitated in pre- and postmortem MRI scans using the Cardiovascular Health Study (CHS) criteria in a blinded fashion. We found that several measures of Alzheimer disease (AD) pathology including CERAD score, Braak score and a composite AD pathology score, along with hypertension, were significantly associated with CHS white matter score using univariate and multivariate ordinal regression. In contrast, amyloid angiopathy was not independently related to with CHS score. While a clinical diagnosis of dementia was associated with CHS score in univariate analysis, the association disappeared after accounting for AD pathology.
Alzheimer’s pathology at autopsy is associated with MRI detected cerebral white matter disease. This relationship may explain, in part, the association between cerebral white matter disease and cognitive decline in the elderly.
Alzheimer’s; Dementia; MRI; White Matter Disease; Hypertension; Atherosclerosis
Massively univariate regression and inference in the form of statistical parametric mapping have transformed the way in which multi-dimensional imaging data are studied. In functional and structural neuroimaging, the de facto standard “design matrix”-based general linear regression model and its multi-level cousins have enabled investigation of the biological basis of the human brain. With modern study designs, it is possible to acquire multi-modal three-dimensional assessments of the same individuals — e.g., structural, functional and quantitative magnetic resonance imaging, alongside functional and ligand binding maps with positron emission tomography. Largely, current statistical methods in the imaging community assume that the regressors are non-random. For more realistic multi-parametric assessment (e.g., voxel-wise modeling), distributional consideration of all observations is appropriate. Herein, we discuss two unified regression and inference approaches, model II regression and regression calibration, for use in massively univariate inference with imaging data. These methods use the design matrix paradigm and account for both random and non-random imaging regressors. We characterize these methods in simulation and illustrate their use on an empirical dataset. Both methods have been made readily available as a toolbox plug-in for the SPM software.
Structure-Function Relationships; Random Regressors; Regression Calibration; Model II Regression; General Linear Model
Anemia has been associated with elevated cerebral blood flow (CBF) in animal models and
certain clinical conditions (eg, renal disease), but whether hemoglobin level variations
across a relatively normal range are associated with local or diffuse CBF changes is
unclear. We investigated whether lower hemoglobin is associated with regional increases
in relative CBF in older individuals, and if these increases occur in watershed
Seventy-four older nondemented adults underwent serial 15O water positron
emission tomography scans. Voxel-based analysis was used to investigate regional
relative CBF patterns in association with hemoglobin level and in individuals with and
without anemia. Analyses of cross-sectional relations between regional CBF and anemia
were performed separately at two time points, 2 years apart, to identify replicable
patterns of associations.
Restricting results to associations replicated across two cross-sectional analyses,
lower hemoglobin was associated with higher relative CBF within the middle/inferior
frontal, occipital, precuneus, and cerebellar regions. In addition, individuals with
anemia (n = 15) showed higher relative CBF in superior frontal,
middle temporal, hippocampal, and gyrus rectus regions than those without anemia. In
some regions (right superior temporal gyrus, left inferior frontal gyrus, midline
cuneus, and right precuneus); however, lower hemoglobin was associated with lower
In nondemented individuals, lower hemoglobin is associated with elevated relative CBF
in specific cortical areas but reduced CBF in other areas. Whether this association
between anemia and CBF in the absence of chronic diseases and in a normal physiologic
range is related to clinical endpoints warrants further study.
Cerebral blood flow; Anemia; PET; Aging
While the gold standard method of cognitive assessment is a face-to-face administration, telephone-based assessments offer several advantages if they demonstrate reliability and validity.
Observational study; 110 participants randomly assigned to receive two administrations of the same cognitive test battery 6 months apart in one of four combinations (1st administration/2nd administration): telephone/telephone; telephone/face-to-face; face-to-face/telephone; or face-to-face/face-to-face.
Academic medical center
110 non-demented women between the ages of 65 and 90 years.
The battery included tests of attention, verbal learning and memory, verbal fluency, executive function, working memory and global cognitive functioning plus self-report measures of perceived memory problems, depressive symptoms, sleep disturbance and health-related quality of life. Test-retest reliability, concurrent validity, relative bias associated with telephone administration, and change scores were evaluated.
There were no statistically significant differences in scores on any of the cognitive tests or questionnaires between randomly assigned modes of administration at baseline indicating equivalence across modes. There was no significant bias for tests or questionnaires administered by telephone (ps>0.01). Nor was there a difference in mean change scores between administration modes except for the Category Fluency (p = 0.01) and the California Verbal Learning Test long delay-free recall (p < 0.01). Mean test-retest coefficients for the battery were not significantly different across groups though individual test-retest correlation coefficients were generally higher within mode than across mode.
Telephone administration of cognitive tests and questionnaires to older women is both reliable and valid. Use of telephone batteries can substantially reduce the economic cost and burden of cognitive assessments and increase enrollment, retention and data completeness thereby improving study validity.
cognition; assessment; telephone; validation; tests
There is increasing evidence from basic science and human epidemiological studies that
inflammation, oxidative stress, and metabolic abnormalities are associated with
age-related cognitive decline and impairment. This article summarizes selected research on
these topics presented at the Cognitive Aging Summit II. Speakers in this session
presented evidence highlighting the roles of these processes and pathways on age-related
cognitive decline, pointing to possible targets for intervention in nondemented older
adults. Specific areas discussed included age differences in the production of cytokines
following injury or infection, mechanisms underlying oxidative stress-induced changes in
memory consolidation, insulin effects on brain signaling and memory, and the association
between metabolic syndrome and cognitive decline in older adults. These presentations
emphasize advances in our understanding of mechanisms and modifiers of age-related
cognitive decline and provide insights into potential targets to promote cognitive health
in older adults.
Aging; Cognition; Inflammation; Oxidative stress; Metabolism
We examined longitudinal associations between ApoE4+ status and several cognitive outcomes and tested effect modification by sex. Data on 644 Non-Hispanic White adults, from the Baltimore Longitudinal Study of Aging (BLSA) were used. Dementia onset, cognitive impairment and decline were assessed longitudinally. After 27.5 years median follow-up, 113 participants developed dementia. ApoE4+ predicted dementia significantly (HR=2.89; 95% CI: 1.93–4.33), with non-significant sex differences. Taking all time points for predicting cognition, women had significantly stronger positive associations than men between ApoE4+ status and impairment or decline on the California Verbal Learning Test (CVLT-delayed recall and List A total recall) and on Verbal Fluency Test-Categories. This ApoE4×sex interaction remained significant with bonferroni correction only for CVLT-delayed recall. Taking time points prior to dementia for cognitive predictions, the positive association between impairment in CVLT-delayed recall and ApoE4+ status remained stronger among women, though only before bonferroni correction. While ApoE4+ status appears to be a sex neutral risk factor for dementia, its association with verbal memory and learning decline and impairment was stronger among women.
Apolipoprotein E genotype; dementia; cognitive decline; cognitive impairment; aging
Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVR) in ligand-receptor dynamic PET studies. The objective of this study is to use a recently developed relative equilibrium-based graphical plot (RE plot) method to improve and simplify the two commonly used methods for quantification of [11C]PiB PET.
The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight [11C]PiB dynamic PET scans (66 from controls and 12 from mildly cognitively impaired participants (MCI) from the Baltimore Longitudinal Study of Aging (BLSA)) were acquired over 90 minutes. Regions of interest (ROIs) were defined on coregistered MRIs. Both the ROI and pixelwise time activity curves (TACs) were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI TACs were used as a reference for comparison of DVR estimates.
Results from the theoretical analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI TACs. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, cingulate regions, and the striatum were underestimated by the Logan plot (controls 4 – 12%; MCI 9 – 16%) and overestimated by the SUVR (controls 8 – 16%; MCI 16 – 24%). This bias was higher in the MCI group than in controls (p < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR.
The RE plot improves pixel-wise quantification of [11C]PiB dynamic PET compared to the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates compared to SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of [11C]PiB studies.
RE plot; [11C]PiB; PET; SUVR; Bias
PET imaging agents such as Pittsburgh compound B (PiB) allow detection of fibrillar β-amyloid (Aβ) in vivo. In addition to quantification of Aβ deposition in mild cognitive impairment and Alzheimer’s disease, PiB has also increased our understanding of Aβ deposition in older adults without cognitive impairment. in vivo Aβ deposition has been studied in relation to genotype, structural and functional brain changes, as well as alterations in biomarker levels. To date, several studies have reported changes in Aβ burden over time. This, together with investigation of the relationship between Aβ deposition and cognition, sets the stage for elucidation of the temporal sequence of the neurobiological events leading to cognitive decline. Furthermore, correlation of Aβ levels detected by PiB PET and those obtained from biopsy or postmortem specimens will allow more rigorous quantitative interpretation of PiB PET data in relation to neuropathological evaluation. Since the first human study in 2004, in vivo amyloid imaging has led to advances in our understanding of the role of Aβ deposition in human aging and cognitive decline, as well as provided new tools for patient selection and therapeutic monitoring in clinical trials.
PiB; amyloid; aging; MCI; AD; cognition; MRI; FDG; pathology; human; brain
High levels of amyloid-β (Aβ) characterize Alzheimer’s disease.
To investigate whether longitudinal changes in Aβ deposition can be detected in vivo in older adults without dementia (hereafter referred to as nondemented).
Community-dwelling older adults.
Twenty-four nondemented participants (4 with a baseline Clinical Dementia Rating Scale score of 0.5; mean [SD] age 79.2 [8.1] years) in the Baltimore Longitudinal Study of Aging underwent serial carbon 11-labeled Pittsburgh Compound B- positron emission tomography ([11C]PiB-PET) (follow-up at a mean [SD] of 1.5 [0.5] years), with 5 participants undergoing a third [11C]PiB-PET examination.
Main Outcome Measures
Annual changes in distribution volume ratio (DVR) were evaluated using a global index of cortical DVR (cDVR) and region-of-interest analyses. Given the variability of cDVR at initial PiB-PET, annual changes in cDVR in those with minimal vs those with elevated initial cDVR were compared.
In nondemented older adults, annual increase in [11C]PiB retention is 0.011 DVR per year (0.9%; P=0.01) which localizes to prefrontal, parietal, lateral temporal, and occipital cortices as well as anterior and posterior cingulate cortices. Annual change in cDVR is greater in older adults with elevated cDVR than in those with minimal initial cDVR (p=0.006).
Fibrillar Aβ detected by [11C]PiB-PET increases over time even in nondemented older adults. Individuals with higher initial [11C]PiB retention have greater rates of Aβ deposition, providing evidence for differential rates of Aβ deposition. Moreover, regional vulnerabilities to Aβ deposition allow for more targeted investigation of early Aβ changes.
Identifying interactions among brain regions from structural magnetic-resonance images presents one of the major challenges in computational neuroanatomy. We propose a Bayesian data-mining approach to the detection of longitudinal morphological changes in the human brain. Our method uses a dynamic Bayesian network to represent evolving inter-regional dependencies. The major advantage of dynamic Bayesian network modeling is that it can represent complicated interactions among temporal processes. We validated our approach by analyzing a simulated atrophy study, and found that this approach requires only a small number of samples to detect the ground-truth temporal model. We further applied dynamic Bayesian network modeling to a longitudinal study of normal aging and mild cognitive impairment — the Baltimore Longitudinal Study of Aging. We found that interactions among regional volume-change rates for the mild cognitive impairment group are different from those for the normal-aging group.
Dynamic Bayesian network; longitudinal morphometry
Mapping brain structure in relation to neurological development, function, plasticity, and disease is widely considered to be one of the most essential challenges for opening new lines of neuro-scientific inquiry. Recent developments with MRI analysis of structural connectivity, anatomical brain segmentation, cortical surface parcellation, and functional imaging have yielded fantastic advances in our ability to probe the neurological structure-function relationship in vivo. To date, the image analysis efforts in each of these areas have typically focused on a single modality. Here, we extend the cortical reconstruction using implicit surface evolution (CRUISE) methodology to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner. This effort combines and extends state-of-the-art techniques to simultaneously consider and analyze structural and diffusion information alongside quantitative and functional imaging data. Robust and consistent estimates of the cortical surface extraction, cortical labeling, diffusion-inferred contrasts, diffusion tractography, and subcortical parcellation are demonstrated in a scan-rescan paradigm. Accompanying this demonstration, we present a fully automated software system complete with validation data.
brain; MRI; cortical surface; white matter parcellation; fiber tracking; sub-cortical segmentation
Amyloid-β plaques (Aβ) are a hallmark of Alzheimer's disease (AD), begin deposition decades before the incipient disease, and are thought to be associated with neuronal loss, brain atrophy and cognitive impairment. We examine associations between 11C-PiB-PET measurement of Aβ burden and brain volume changes in the preceding years in 57 non-demented individuals (age 64-86; M = 78.7). Participants were prospectively followed through the Baltimore Longitudinal Study of Aging, with up to 10 consecutive MRI scans (M = 8.1) and an 11C-PiB scan approximately 10 years after the initial MRI. Linear mixed effects models were used to determine whether mean cortical 11C-PiB distribution volume ratios, estimated by fitting a reference tissue model to the measured time activity curves, were associated with longitudinal regional brain volume changes of the whole brain, ventricular CSF, frontal, temporal, parietal, and occipital white and gray matter, the hippocampus, orbito-frontal cortex, and the precuneus. Despite significant longitudinal declines in the volumes of all investigated regions (p < 0.05), no associations were detected between current Aβ burden and regional brain volume decline trajectories in the preceding years, nor did the regional volume trajectories differ between those with highest and lowest Aβ burden. Consistent with a threshold model of disease, our findings suggest that Aβ load does not seem to affect brain volume changes in individuals without dementia.
Alzheimer's Disease; BLSA; Volumetric MRI; Normal Aging: PET; 11C-PiB
Statin use and serum cholesterol reduction have been proposed as preventions for dementia and mild cognitive impairment (MCI).
1,604 and 1,345 eligible participants from the Baltimore Longitudinal Study of Aging (BLSA) were followed after age 50 for a median time of around 25 years, to examine incidence of dementia (n=259) and MCI (n=138), respectively. Statin use (ever-use and time-dependent use), total cholesterol levels (TC; first-visit and time-dependent), TC change trajectory from first-visit, and high-density lipoprotein (HDL-C):TC ratio (first-visit and time-dependent) were main exposures of interest. Cox proportional hazards models were used.
Participants with incident dementia had higher first-visit TC compared to participants who remained free of dementia and MCI, while first-visit TC was higher among statin ever-users compared to never-users (age-unadjusted associations). Statin users had two to three-fold lower risk of developing dementia (HR=0.41; 95% CI: 0.18–0.92), but not MCI, when considering time-dependent “statin use” with propensity score model adjustment. This association remained significant independently of serum cholesterol exposures. An elevated first-visit TC was associated with reduced MCI risk (Upper quartile (Q4) vs. Q1: HR=0.51; 95% CI=0.29–0.90). Compared to the lowest quartile (Q1: 0.00–0.19), HDL-C:TC (time-dependent) in (Q2: 0.19–0.24) was associated with reduced MCI risk (HR=0.53; 95%CI: 0.30–0.94). Among men only, TC decline from first-visit was significantly associated with increased dementia risk (HR=4.21; 95% CI: 1.28–13.85).
Statins may have multifactorial effects on dementia but not MCI risk. Future interventions may be warranted and research should focus on optimal serum TC, HDL-C:TC ratio and TC change trajectories.
Statins; serum cholesterol; dementia; mild cognitive impairment; aging
A number of conditions are characterized by pathologies that form continuous or nearly-continuous spectra spanning from the absence of pathology to very pronounced pathological changes (e.g., normal aging, Mild Cognitive Impairment, Alzheimer's). Moreover, diseases are often highly heterogeneous with a number of diagnostic subcategories or subconditions lying within the spectra (e.g., Autism Spectrum Disorder, schizophrenia). Discovering coherent subpopulations of subjects within the spectrum of pathological changes may further our understanding of diseases, and potentially identify subconditions that require alternative or modified treatment options. In this paper, we propose an approach that aims at identifying coherent subpopulations with respect to the underlying MRI in the scenario where the condition is heterogeneous and pathological changes form a continuous spectrum. We describe a Joint Maximum-Margin Classification and Clustering (JointMMCC) approach that jointly detects the pathologic population via semi-supervised classification, as well as disentangles heterogeneity of the pathological cohort by solving a clustering subproblem. We propose an efficient solution to the non-convex optimization problem associated with JointMMCC. We apply our proposed approach to an MRI study of aging, and identify coherent subpopulations (i.e., clusters) of cognitively less stable adults.
Semi-supervised classification; clustering; MRI; aging
Subjective cognitive complaints are often used in the diagnosis of dementia, yet few studies have looked at factors that predict differences in complaints.
This study examined whether concurrent depressive symptoms and self and informant-reported cognitive impairments are related to cognitive complaints.
Longitudinal aging study of the relationship between depressive symptoms, reported cognitive impairments, and cognitive complaints. Mixed effects regression models were used to determine whether scores on the Center for Epidemiological Studies Depression (CESD) scale and Clinical Dementia Rating (CDR) scale predicted cognitive complaints. The Cognitive Failures Questionnaire (CFQ) assessed cognitive complaints.
A community dwelling sample in Baltimore, MD.
105 cognitively normal older individuals with a mean baseline age of 75 years, followed for an average of 4 years.
The Center for Epidemiological Studies Depression (CESD) scale measured depressive symptoms. The Clinical Dementia Rating Sum of Boxes (CDR-SB) scale measured self and informant reported impairment, and the CFQ measured cognitive complaints.
We found that increases in depressive symptoms and reported impairments are associated with increased CFQ scores. In addition, there was a significant interaction between depressive symptoms and reported impairment in relation to cognitive complaints. Those individuals without reported cognitive impairment show the strongest association between depressive symptoms and cognitive complaints. Finally, reported impairments interact with baseline age, suggesting that the relationship between reported impairments and cognitive complaints is strongest in individuals younger than 80 years old.
These findings confirm a relationship between reported cognitive impairment and cognitive complaints in older individuals, and also highlight the extent to which age and depressive symptoms account for variation in complaints. These factors should be considered when interpreting cognitive complaints in a clinical setting.
cognitive complainst; depression; aging
Several studies have demonstrated age-related declines in general executive function and memory. In this study, we examined cross-sectional and longitudinal age effects in more specific cognitive processes that constitute executive function and memory. We postulated that, whereas some components of executive and memory functions would show age differences and longitudinal declines, other specific abilities would be maintained or even improve with repeated testing. In a sample of individuals ≥55 years old from the Baltimore Longitudinal Study of Aging, we found longitudinal declines in inhibition, manipulation, semantic retrieval, phonological retrieval, switching, and long-term memory over a maximum of 14 years follow-up. In contrast, abstraction, capacity, chunking, discrimination, and short-term memory were maintained or even improved longitudinally, probably due in part to repeated testing. Moreover, whereas several different abilities were correlated across participants’ cross-sectional performance, longitudinal changes in performance showed more heterogeneous trajectories. Finally, compared with cross-sectional performance, longitudinal trajectories showed better distinction between participants with and those without later cognitive impairment. These results show that longitudinal cognitive aging of executive and memory functions is not a uniform process but a heterogeneous one and suggest that certain executive and memory functions remain stable despite age-related declines in other component processes.
aging; executive function; memory; longitudinal; cross-sectional
Although studies exploring relationships between obesity and cognitive impairment in the elderly are conflicting, literature suggests that overweight and obesity may be protective against cognitive impairment and dementia in older women. We examine the associations between changes in weight and waist circumference with global and domain-specific cognitive function in a large, well-defined cohort of 2283 older, post-menopausal women (age 65-79) prospectively followed through the Women's Health Initiative (WHI) Study of Cognitive Aging (WHISCA). We assessed the associations between changes in weight and waist circumference collected up to 5 years prior to WHISCA enrollment and mean levels of global and domain-specific cognitive performance across an average of 5.4 years of subsequent follow-up. There was a lack of associations between weight and cognition in women who remained stable or gained weight. The only significant relationships observed were in association with weight loss (p≤0.05), most likely signaling incipient disease. Moreover, cognition was not related to changes in waist circumference. Relationships were largely independent of initial BMI, self-reported caloric intake or dieting. The lack of associations between weight gain and cognition in women is consistent with the existent literature.
Populations of healthy older individuals are often highly heterogeneous, as prevalence of various underlying pathologies increases with age. Finding coherent groups of normal older adults may allow to identify subpopulations that are at risk of developing Alzheimer’s disease (AD). In this paper, we propose an approach that utilizes longitudinal magnetic resonance imaging (MRI) data to obtain natural groupings of older adult subjects via an unsupervised (i.e., clustering) technique. We develop a k-medoids-like clustering algorithm that simultaneously finds clusters of longitudinal images, as well as weights brain regions in such a way that the obtained clusters are maximally coherent. We propose a cluster-based measure that reflects the individual subject’s cognitive decline. The proposed method is unsupervised and is suitable for analyzing AD at its very early stages.
Alzheimer’s; MRI; Mild Cognitive Impairment; Cluster Analysis; Longitudinal Image Analysis
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, regions of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrices. Recently, biological parametric mapping has extended the widely popular statistical parametric mapping approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and non-parametric regression in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provide a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.
Structure-Function Relationships; Statistical Parametric Mapping; Biological Parametric Mapping; Robust Regression; Non-Parametric Regression
Extraction of the brain — i.e. cerebrum, cerebellum, and brain stem — from T1-weighted structural magnetic resonance images is an important initial step in neuroimage analysis. Although automatic algorithms are available, their inconsistent handling of the cortical mantle often requires manual interaction, thereby reducing their effectiveness. This paper presents a fully automated brain extraction algorithm that incorporates elastic registration, tissue segmentation, and morphological techniques which are combined by a watershed principle, while paying special attention to the preservation of the boundary between the gray matter and the cerebrospinal fluid. The approach was evaluated by comparison to a manual rater, and compared to several other leading algorithms on a publically available data set of brain images using the Dice coefficient and containment index as performance metrics. The qualitative and quantitative impact of this initial step on subsequent cortical surface generation is also presented. Our experiments demonstrate that our approach is quantitatively better than six other leading algorithms (with statistical significance on modern T1-weighted MR data). We also validated the robustness of the algorithm on a very large data set of over one thousand subjects, and showed that it can replace an experienced manual rater as preprocessing for a cortical surface extraction algorithm with statistically insignificant differences in cortical surface position.
Brain extraction; skull stripping; watershed principle; segmentation; medical image processing
Asymptomatic Alzheimer disease (ASYMAD) is characterized by normal cognition despite substantial AD pathology. To identify factors contributing to cognitive resilience, we compared early changes in regional cerebral blood flow (rCBF) in individuals subsequently diagnosed as ASYMAD with changes in cognitively impaired (CI) and normal older participants from the Baltimore Longitudinal Study of Aging. Participants underwent annual positron emission tomography (PET) rCBF measurements beginning 10.0 (SD 3.6) years before death and while cognitively intact. Based on clinical and autopsy information, subjects were grouped as cognitively normal (CN = 7), ASYMAD (n= 6), and CI (=6). Autopsy material was analyzed using CERAD and Braak scores and quantitative stereologic measures of tau and amyloid. ASYMAD and CI groups had similar CERAD and Braak scores, similar amounts of β-amyloid and tau in middle frontal (MFG), middle temporal (MTG), and inferior parietal (IP) regions, and more β-amyloid than CN in precuneus, MFG, and IP areas. Voxel-based PET analysis identified similarities and differences in longitudinal rCBF change among groups across a 7.2-year interval. Both ASYMAD and CI groups showed similar longitudinal rCBF declines in precuneus, lingual, and MTG regions relative to CN. The CI also showed greater rCBF decreases in anterior and posterior cingulate, cuneus, and brainstem regions relative to ASYMAD and CN, whereas ASYMAD showed greater relative rCBF increases over time in medial temporal and thalamic regions relative to CI and CN. Our findings provide evidence of early functional alterations that may contribute to cognitive resilience in those who accumulate AD pathology but maintain normal cognition.
Amyloid; dementia; fMRI; neuropathology; PET; resting state; tau
Brain derived neurotrophic factor (BDNF) seems to be involved in regulation of synaptic plasticity and neurogenesis. BDNF plasma and serum levels have been associated with depression, Alzheimer's disease, and other psychiatric and neurodegenerative disorders. In a community sample, drawn from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether BDNF plasma concentration was associated with rates of age-related change in cognitive performance (n = 429) and regional brain volume (n = 59). Plasma BDNF levels, which were significantly higher in females (p<0.05), were not associated with either concurrent cognitive performance or rates of age-related change in performance across cognitive domains (p's>0.05). Sex differences in the relationship between BDNF and the trajectories of regional brain volume changes were observed for the whole brain and frontal white matter volumes (p<0.05), whereby lower plasma BDNF was associated with steeper volume decline in females but not males. Together, our findings contribute to furthering the understanding of the relationships between plasma BDNF, structural brain integrity and cognition. Potential mechanisms mediating these relationships merit further investigation.
Earlier studies have suggested that hearing loss, which is prevalent in more than 30% of adults >60 years, may be a risk factor for dementia, but this hypothesis has never been investigated prospectively.
To determine if hearing loss is associated with incident all-cause dementia and Alzheimer’s disease (AD).
Design, Setting, and Participants
Prospective study of 639 participants (age 36 – 90 y) of the Baltimore Longitudinal Study of Aging who had audiometric testing and who were dementia-free in 1990-1994. Hearing loss was defined by a pure-tone average of hearing thresholds at 0.5, 1, 2, and 4 kHz in the better-hearing ear (normal <25 dB [n = 455], mild loss 25-40 dB [n = 125], moderate loss 41-70 dB [n = 53], severe loss >70 dB [n = 6]). Diagnosis of incident dementia was made by consensus diagnostic conference. Cox proportional hazard models were used to model time to incident dementia according to severity of hearing loss and were adjusted for age, sex, race, education, diabetes, smoking, and hypertension.
Main Outcome Measure
Incidence of all-cause dementia and AD until May 31, 2008.
During a median follow-up of 11.9 years, 58 cases of incident all-cause dementia were diagnosed of which 37 cases were AD. The risk of incident all-cause dementia increased log-linearly with the severity of baseline hearing loss (1.27 per 10 db loss, 95% CI: 1.06 – 1.50). Compared to normal hearing, the hazard ratio for incident all-cause dementia was 1.89 for mild hearing loss (95% CI: 1.00 – 3.58), 3.00 for moderate hearing loss (95% CI: 1.43 – 6.30), and 4.94 for severe hearing loss (95% CI: 1.09 – 22.4). The risk of incident AD also increased with baseline hearing loss but with a wider confidence interval (1.20 per 10 dB of hearing loss, 95% CI: 0.94 – 1.53).
Hearing loss is independently associated with incident all-cause dementia. Whether hearing loss is a marker for early stage dementia or is actually a modifiable risk factor for dementia deserves further study.