Microbleeds have been associated with Alzheimer’s disease (AD), although it is unclear whether they occur in atypical presentations of AD, such as the logopenic variant of primary progressive aphasia (lvPPA). We aimed to assess the presence and clinical correlates of microbleeds in lvPPA.
Thirteen lvPPA subjects underwent 3T T2*-weighted and fluid-attenuated inversion recovery MRI and Pittsburgh Compound B (PiB) PET imaging. Microbleeds were identified on manual review and assigned a regional location. Total and regional white matter hyperintensity (WMH) burden was measured.
Microbleeds were observed in four lvPPA subjects (31%); most common in frontal lobe. Subjects with microbleeds were older, more likely female, and had a greater burden of WMH than those without microbleeds. The regional distribution of microbleeds did not match the regional distribution of WMH. All cases were PiB-positive.
Microbleeds occur in approximately 1/3 subjects with lvPPA, with older women at the highest risk.
Logopenic variant of primary progressive aphasia; Alzheimer’s disease; microbleeds; white matter hyperintensities
To determine structural MRI and digital microscopic characteristics of REM sleep behavior disorder in individuals with low-, intermediate-, and high-likelihood dementia with Lewy bodies (DLB) at autopsy.
Patients with autopsy-confirmed low-, intermediate-, and high-likelihood DLB, according to the probability statement recommended by the third report of the DLB Consortium, and antemortem MRI, were identified (n = 75). The clinical history was assessed for presence (n = 35) and absence (n = 40) of probable REM sleep behavior disorder (pRBD), and patients' antemortem MRIs were compared using voxel-based morphometry. Pathologic burdens of phospho-tau, β-amyloid, and α-synuclein were measured in regions associated with early neuropathologic involvement, the hippocampus and amygdala.
pRBD was present in 21 patients (60%) with high-likelihood, 12 patients (34%) with intermediate-likelihood, and 2 patients (6%) with low-likelihood DLB. Patients with pRBD were younger, more likely to be male (p ≤ 0.001), and had a more frequent neuropathologic diagnosis of diffuse (neocortical) Lewy body disease. In the hippocampus and amygdala, phospho-tau and β-amyloid burden were lower in patients with pRBD compared with those without pRBD (p < 0.01). α-Synuclein burden did not differ in the hippocampus, but trended in the amygdala. Patients without pRBD had greater atrophy of temporoparietal cortices, hippocampus, and amygdala (p < 0.001) than those with pRBD; atrophy of the hippocampus (p = 0.005) and amygdala (p = 0.02) were associated with greater phospho-tau burdens in these regions.
Presence of pRBD is associated with a higher likelihood of DLB and less severe Alzheimer-related pathology in the medial temporal lobes, whereas absence of pRBD is characterized by Alzheimer-like atrophy patterns on MRI and increased phospho-tau burden.
Prevalence and risk factors for focal hemosiderin deposits are important considerations when planning amyloid–modifying trials for treatment and prevention of Alzheimer’s disease (AD).
Subjects were cognitively normal (n=171), early-mild cognitive impairment (MCI) (n=240), late-MCI (n=111) and AD (n=40) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Microhemorrhages and superficial siderosis were assessed at baseline and on all available MRIs at 3, 6 and 12 months. β-amyloid load was assessed with 18F-florbetapir PET.
Prevalence of superficial siderosis was 1% and prevalence of microhemorrhages was 25% increasing with age (p<0.001) and β-amyloid load (p<0.001). Topographic densities of microhemorrhages were highest in the occipital lobes and lowest in the deep/infratentorial regions. A greater number of microhemorrhages at baseline was associated with a greater annualized rate of additional microhemorrhages by last follow-up (rank correlation=0.49;P<0.001).
Focal hemosiderin deposits are relatively common in the ADNI cohort and are associated with β-amyloid load.
ADNI; microhemorrhage; superficial siderosis; MRI; Amyloid; PET; Florbetapir; Alzheimer’s disease; mild cognitive impairment; early mild cognitive impairment
Midbrain atrophy is a characteristic feature of progressive supranuclear palsy (PSP), although it is unclear whether it is associated with the PSP syndrome (PSPS) or PSP pathology. We aimed to determine whether midbrain atrophy is a useful biomarker of PSP pathology, or whether it is only associated with typical PSPS.
We identified all autopsy-confirmed subjects with the PSP clinical phenotype (i.e. PSPS) or PSP pathology and a volumetric MRI. Of 24 subjects with PSP pathology, 11 had a clinical diagnosis of PSPS (PSP-PSPS), and 13 had a non-PSPS clinical diagnosis (PSP-other). Three subjects had PSPS and corticobasal degeneration pathology (CBD-PSPS). Healthy control and disease control groups (i.e. a group without PSPS or PSP pathology) and a group with CBD pathology and corticobasal syndrome (CBD-CBS) were selected. Midbrain area was measured in all subjects.
Midbrain area was reduced in each group with clinical PSPS (with and without PSP pathology). The group with PSP pathology and non-PSPS clinical syndromes did not show reduced midbrain area. Midbrain area was smaller in the subjects with PSPS compared to those without PSPS (p<0.0001), with an area under the receiver-operator-curve of 0.99 (0.88,0.99). A midbrain area cut-point of 92 mm2 provided optimum sensitivity (93%) and specificity (89%) for differentiation.
Midbrain atrophy is associated with the clinical presentation of PSPS, but not with the pathological diagnosis of PSP in the absence of the PSPS clinical syndrome. This finding has important implications for the utility of midbrain measurements as diagnostic biomarkers for PSP pathology.
Progressive supranuclear palsy; tau; neuropathology; MRI; midbrain
Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter “skeleton” is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology.
DTI; Fractional Anisotropy; Voxel-based analysis; VBM; TBSS; Registration
To investigate MRI and proton magnetic resonance spectroscopy (MRS) predictors of mild cognitive impairment (MCI) in cognitively normal older adults.
Subjects were cognitively normal older adults (n = 1,156) who participated in the population-based Mayo Clinic Study of Aging MRI/MRS study from August 2005 to December 2010 and had at least one annual clinical follow-up. Single-voxel MRS was performed from the posterior cingulate gyri, and hippocampal volumes and white matter hyperintensity volumes were quantified using automated methods. Brain infarcts were assessed on MRI. Cox proportional hazards regression, with age as the time scale, was used to assess the effect of MRI and MRS markers on the risk of progression from cognitively normal to MCI. Linear mixed-effects models were used to assess the effect of MRI and MRS markers on cognitive decline.
After a median follow-up of 2.8 years, 214 participants had progressed to MCI or dementia (estimated incidence rate = 6.1% per year; 95% confidence interval = 5.3%–7.0%). In univariable modeling, hippocampal volume, white matter hyperintensity volume, and N-acetylaspartate/myo-inositol were significant predictors of MCI in cognitively normal older adults. In multivariable modeling, only decreased hippocampal volume and N-acetylaspartate/myo-inositol were independent predictors of MCI. These MRI/MRS predictors of MCI as well as infarcts were associated with cognitive decline (p < 0.05).
Quantitative MRI and MRS markers predict progression to MCI and cognitive decline in cognitively normal older adults. MRS may contribute to the assessment of preclinical dementia pathologies by capturing neurodegenerative changes that are not detected by hippocampal volumetry.
The ADNI 3D T1-weighted MRI acquisitions provide a rich dataset for developing and testing analysis techniques for extracting structural endpoints. To promote greater rigor in analysis and meaningful comparison of different algorithms, the ADNI MRI Core has created standardized analysis sets of data comprising scans that met minimum quality control requirements. We encourage researchers to test and report their techniques against these data. Standard analysis sets of volumetric scans from ADNI-1 have been created, comprising: screening visits, 1 year completers (subjects who all have screening, 6 and 12 month scans), two year annual completers (screening, 1, and 2 year scans), two year completers (screening, 6 months, 1 year, 18 months (MCI only) and 2 years) and complete visits (screening, 6 months, 1 year, 18 months (MCI only), 2, and 3 year (normal and MCI only) scans). As the ADNI-GO/ADNI-2 data becomes available, updated standard analysis sets will be posted regularly.
Primary progressive apraxia of speech, a motor speech disorder of planning and programming is a tauopathy that has overlapping histological features with progressive supranuclear palsy. We aimed to compare, for the first time, atrophy patterns, as well as white matter tract degeneration, between these two syndromes.
Sixteen primary progressive apraxia of speech subjects were age and gender-matched to 16 progressive supranuclear palsy subjects and 20 controls. All subjects were prospectively recruited, underwent neurological and speech evaluations, and 3.0 Tesla magnetic resonance imaging. Grey and white matter atrophy was assessed using voxel-based morphometry and atlas-based parcellation, and white matter tract degeneration was assessed using diffusion tensor imaging.
All progressive supranuclear palsy subjects had typical occulomotor/gait impairments but none had speech apraxia. Both syndromes showed grey matter loss in supplementary motor area, white matter loss in posterior frontal lobes and degeneration of the body of the corpus callosum. While lateral grey matter loss was focal, involving superior premotor cortex, in primary progressive apraxia of speech, loss was less focal extending into prefrontal cortex in progressive supranuclear palsy. Caudate volume loss and tract degeneration of superior cerebellar peduncles was also observed in progressive supranuclear palsy. Interestingly, area of the midbrain was reduced in both syndromes compared to controls, although this was greater in progressive supranuclear palsy.
Although neuroanatomical differences were identified between these distinctive clinical syndromes, substantial overlap was also observed, including midbrain atrophy, suggesting these two syndromes may have common pathophysiological underpinnings.
Progressive supranuclear palsy; apraxia of speech; voxel-based morphometry; diffusion tensor imaging; midbrain
The new criteria for preclinical Alzheimer’s Disease (AD) proposed 3 stages: abnormal levels of β-amyloid (stage 1); stage 1 plus evidence of brain injury (stage 2); and stage 2 plus subtle cognitive changes (stage 3). However, a large group of subjects with normal β-amyloid biomarkers have evidence of brain injury; we labeled them as “suspected non-Alzheimer pathway” (sNAP) group. The characteristics of the sNAP group are poorly understood.
Using the preclinical AD classification, 430 cognitively normal subjects from the Mayo Clinic Study of Aging who underwent brain MR, 18fluorodeoxyglucose (FDG) and Pittsburgh compound B (PiB) positron emission tomography (PET) were evaluated with FDG PET regional volumetrics, MR regional brain volumetrics, white matter hyperintensity (WMH) volume and number of infarcts. We examined cross-sectional associations across AD preclinical stages, those with all biomarkers normal, and the sNAP group.
The sNAP group had a lower proportion (14%) with APOE ε4 genotype than the preclinical AD stages 2 + 3. The sNAP group did not show any group differences compared to stages 2 + 3 of the preclinical AD group on measures of FDG PET regional hypometabolism, MR regional brain volume loss, cerebrovascular imaging lesions, vascular risk factors, imaging changes associated with α-synucleinopathy or physical findings of parkinsonism.
Cognitively normal persons with brain injury biomarker abnormalities, with or without abnormal levels of β-amyloid, were indistinguishable on a variety of imaging markers, clinical features and risk factors. The initial appearance of brain injury biomarkers that occurs in cognitively normal persons with preclinical AD may not depend on β-amyloidosis.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology
To determine the association of conventional cardiovascular risk factors, markers of platelet activation, and thrombogenic blood-borne microvesicles with white matter hyperintensity (WMH) load and progression in recently menopausal women.
Women (n = 95) enrolled in the Mayo Clinic Kronos Early Estrogen Prevention Study underwent MRI at baseline and at 18, 36, and 48 months after randomization to hormone treatments. Conventional cardiovascular risk factors, carotid intima-medial thickness, coronary arterial calcification, plasma lipids, markers of platelet activation, and thrombogenic microvesicles were measured at baseline. WMH volumes were calculated using a semiautomated segmentation algorithm based on fluid-attenuated inversion recovery MRI. Correlations of those parameters with baseline WMH and longitudinal change in WMH were adjusted for age, months past menopause, and APOE ε4 status in linear regression analysis.
At baseline, WMH were present in all women. The WMH to white matter volume fraction at baseline was 0.88% (0.69%, 1.16%). WMH volume increased by 122.1 mm3 (95% confidence interval: −164.3, 539.5) at 36 months (p = 0.003) and 155.4 mm3 (95% confidence interval: −92.13, 599.4) at 48 months (p < 0.001). These increases correlated with numbers of platelet-derived and total thrombogenic microvesicles at baseline (p = 0.03).
Associations of platelet-derived, thrombogenic microvesicles at baseline and increases in WMH suggest that in vivo platelet activation may contribute to a cascade of events leading to development of WMH in recently menopausal women.
Most subjects with logopenic primary progressive aphasia (lvPPA) have beta-amyloid (Aβ) deposition on Pittsburgh Compound B PET (PiB-PET), usually affecting prefrontal and temporoparietal cortices, with less occipital involvement.
To assess clinical and imaging features in lvPPA subjects with unusual topographic patterns of Aβ deposition with highest uptake in occipital lobe.
Thirty-three lvPPA subjects with Aβ deposition on PiB-PET were included in this case-control study. Line-plots of regional PiB uptake were created, including frontal, temporal, parietal and occipital regions, for each subject. Subjects in which the line sloped downwards in occipital lobe (lvPPA-low), representing low uptake, were separated from those where the line sloped upwards in occipital lobe (lvPPA-high), representing unusually high occipital uptake compared to other regions. Clinical variables, atrophy on MRI, hypometabolism on F18-fluorodeoxyglucose PET, and presence and distribution of microbleeds and white matter hyperintensities (WMH) were assessed.
Seventeen subjects (52%) were classified as lvPPA-high. Mean occipital PiB uptake in lvPPA-high was higher than all other regions, and higher than all regions in lvPPA-low. The lvPPA-high subjects performed more poorly on cognitive testing, including executive and visuospatial testing, but the two groups did not differ in aphasia severity. Proportion of microbleeds and WMH was higher in lvPPA-high than lvPPA-low. Parietal hypometabolism was greater in lvPPA-high than lvPPA-low.
Unusually high occipital Aβ deposition is associated with widespread cognitive impairment and different imaging findings in lvPPA. These findings help explain clinical heterogeneity in lvPPA, and suggest that Aβ influences severity of overall cognitive impairment but not aphasia.
The appearance of β-amyloidosis and brain injury biomarkers in cognitively normal (CN) persons is thought to define risk for the future development of cognitive impairment due to Alzheimer’s disease (AD), but their interaction is poorly understood.
To test the hypothesis that the joint presence of β-amyloidosis and brain injury biomarkers would lead to more rapid neurodegeneration.
Longitudinal Cohort Study
Population-based Mayo Clinic Study of Aging.
191 CN persons (median age 77, range 71–93) in the Mayo Clinic Study of Aging who underwent MR, FDG PET and PiB PET imaging at least twice 15 months apart. Subjects were grouped according to the recommendations of the NIA-AA Preclinical AD criteria, based on the presence of β-amyloidosis, defined as a PiB PET SUVr >1.5, alone (Stage 1) or with brain injury (stage 2+3), defined as hippocampal atrophy or FDG hypometabolism. We also studied a group of MCI (n=17) and dementia (n=9) patients from the Mayo Clinic Study of Aging or the Mayo Alzheimer Center with similar follow-up times who had had comparable imaging and who all had PiB PET SUVr >1.5.
Main Outcome Measures
Rate of change of cortical volume on volumetric MR scans and rate of change of glucose metabolism on FDG PET scans.
There were 25 CN subjects with both high PiB retention and low hippocampal volume or FDG hypometabolism at baseline (Preclinical AD stages 2+3). On follow-up scans, the Preclinical AD stages 2+3 subjects had greater loss of medial temporal lobe volume and greater glucose hypometabolism in the medial temporal lobe compared to other CN groups. The changes were similar to the cognitively impaired participants. Extra-temporal regions did not show similar changes.
Higher rates of medial temporal neurodegeneration occurred in CN individuals who, on their initial scans, had abnormal levels of both β-amyloid and brain injury biomarkers.
Alzheimer’s disease; PET imaging; MR imaging; Epidemiology
To evaluate the effects of recent advances in MRI RF coil and parallel imaging technology on brain volume measurement consistency.
Materials and Methods
103 whole-brain MRI volumes were acquired at a clinical 3T MRI, equipped with a 12- and 32-channel head coil, using the T1-weighted protocol as employed in the Alzheimer’s Disease Neuroimaging Initiative study with parallel imaging accelerations ranging from 1 to 5. An experienced reader performed qualitative ratings of the images. For quantitative analysis, differences in composite width (CW, a measure of image similarity) and boundary shift integral (BSI, a measure of whole-brain atrophy) were calculated.
Intra- and inter-session comparisons of CW and BSI measures from scans with equal acceleration demonstrated excellent scan-rescan accuracy, even at the highest acceleration applied. Pairs-of-scans acquired with different accelerations exhibited poor scan-rescan consistency only when differences in the acceleration factor were maximized. A change in the coil hardware between compared scans was found to bias the BSI measure.
The most important findings are that the accelerated acquisitions appear to be compatible with the assessment of high-quality quantitative information and that for highest scan-rescan accuracy in serial scans the acquisition protocol should be kept as consistent as possible over time.
Magnetic resonance imaging (MRI); brain; measurement consistency
To investigate the effect of intellectual and physical activity on biomarkers of Alzheimer’s disease (AD) pathophysiology and cognition in a non-demented elderly population. The biomarkers evaluated were brain Aβ-amyloid load via PIB-PET, neuronal dysfunction via FDG-PET and neurodegeneration via Structural-MRI.
We studied 515 non-demented (428 cognitively normal and 87 MCI) participants in the population based Mayo Clinic Study of Aging who completed a 3T MRI, PET scans, APOE genotype, had lifestyle activity measures and cognition data available. The imaging measures computed were global PiB-PET uptake; global FDG-PET and MRI based hippocampal volume. We consolidated activity variables into lifetime intellectual, current intellectual and current physical activities. We used a global cognitive Z-score as a measure of cognition. We applied two independent methods – partial correlation analysis adjusted for age and gender and path analysis using structural equations to evaluate the associations between lifestyle activities, imaging biomarkers and global cognition.
None of the lifestyle variables correlated with the biomarkers and the path associations between lifestyle variables and biomarkers were not significant (p>0.05). On the other hand, all the biomarkers were correlated with global cognitive Z-score (p<0.05) and the path associations between (lifetime and current) intellectual activities and global Z-score were significant (p<0.01).
Intellectual and physical activity lifestyle factors were not associated with AD biomarkers but intellectual lifestyle factors explained variability in the cognitive performance in this non-demented population. This study provides evidence that lifestyle activities may delay the onset of dementia but do not significantly influence the expression of AD pathophysiology.
Alzheimer’s disease; Imaging biomarkers; Lifestyle Activities
To systematically compare two techniques for measuring brain atrophy rates from serial magnetic resonance imaging (MRI) studies.
Materials and Methods
Using the separation in atrophy rate between cohorts of cognitively normal elderly subjects and patients with Alzheimer's disease (AD) as the gold standard, we evaluated 1) different methods of computing volume change; 2) different methods for steps in image preprocessing - intensity normalization, alignment mask used, and bias field correction; 3) the effect of MRI acquisition hardware changes; and 4) the sensitivity of the method to variations in initial manual volume editing. For each of the preceding evaluations, measurements of whole-brain and ventricular atrophy rates were calculated.
In general, greater separation between the clinical groups was seen with ventricular rather than whole-brain measures. Surprisingly, neither the use of bias field correction nor a major hardware change between the scan pairs affected group separation.
Atrophy rate measurements from serial MRI are candidates for use as surrogate markers of disease progression in AD and other dementing neurodegenerative disorders. The final method has excellent precision and accurately captures the expected biology of AD - arguably the two most important features if this technique is to be used as a biomarker of disease progression.
serial MRI; Alzheimer's Disease; Brain Atrophy
The logopenic variant of primary progressive aphasia is an atypical clinical variant of Alzheimer’s disease which is typically characterized by left temporoparietal atrophy on magnetic resonance imaging and hypometabolism on F-18 fluorodeoxyglucose positron emission tomography. We aimed to characterize and compare patterns of atrophy and hypometabolism in logopenic primary progressive aphasia, and determine which brain regions and imaging modality best differentiates logopenic primary progressive aphasia from typical dementia of the Alzheimer’s type.
A total of 27 logopenic primary progressive aphasia subjects underwent fluorodeoxyglucose positron emission tomography and volumetric magnetic resonance imaging. These subjects were matched to 27 controls and 27 subjects with dementia of the Alzheimer’s type. Patterns of atrophy and hypometabolism were assessed at the voxel and region-level using Statistical Parametric Mapping. Penalized logistic regression analysis was used to determine what combinations of regions best discriminate between groups.
Atrophy and hypometabolism was observed in lateral temporoparietal and medial parietal lobes, left greater than right, and left frontal lobe in the logopenic group. The logopenic group showed greater left inferior, middle and superior lateral temporal atrophy (inferior p = 0.02; middle p = 0.007, superior p = 0.002) and hypometabolism (inferior p = 0.006, middle p = 0.002, superior p = 0.001), and less right medial temporal atrophy (p = 0.02) and hypometabolism (p<0.001), and right posterior cingulate hypometabolism (p<0.001) than dementia of the Alzheimer’s type. An age-adjusted penalized logistic model incorporating atrophy and hypometabolism achieved excellent discrimination (area under the receiver operator characteristic curve = 0.89) between logopenic and dementia of the Alzheimer’s type subjects, with optimal discrimination achieved using right medial temporal and posterior cingulate hypometabolism, left inferior, middle and superior temporal hypometabolism, and left superior temporal volume.
Patterns of atrophy and hypometabolism both differ between logopenic primary progressive aphasia and dementia of the Alzheimer’s type and both modalities provide excellent discrimination between groups.
To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.
Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).
Two different samples (n=343 and n=598) were created that spanned the cognitive spectrum from normal to AD dementia. Subgroup analyses were performed in members of both cohorts (n=243 and n=328) who were amyloid positive at baseline.
Main Outcome Measures
The shape of biomarker trajectories as a function of MMSE, adjusted for age, was modeled and described as baseline (cross-sectional) and within-subject longitudinal effects. Biomarkers evaluated were cerebro spinal fluid (CSF) Aβ42 and tau; amyloid and fluoro deoxyglucose position emission tomography (PET) imaging, and structural magnetic resonance imaging (MRI).
Baseline biomarker values generally worsened (i.e., non-zero slope) with lower baseline MMSE. Baseline hippocampal volume, amyloid PET and FDG PET values plateaued (i.e., non-linear slope) with lower MMSE in one or more analyses. Longitudinally, within-subject rates of biomarker change were associated with worsening MMSE. Non-constant within-subject rates (deceleration) of biomarker change were found in only one model.
Biomarker trajectory shapes by MMSE were complex and were affected by interactions with age and APOE status. Non-linearity was found in several baseline effects models. Non-constant within-subject rates of biomarker change were found in only one model, likely due to limited within-subject longitudinal follow up. Creating reliable models that describe the full trajectories of AD biomarkers will require significant additional longitudinal data in individual participants.
Alzheimer’s disease biomarkers; Magnetic Resonance Imaging; cerebro spinal fluid; amyloid PET imaging; FDG PET imaging
A workgroup commissioned by the Alzheimer’s Association (AA) and the National Institute on Aging (NIA) recently published research criteria for preclinical Alzheimer’s disease (AD). We performed a preliminary assessment of these guidelines.
We employed Pittsburgh compound B positron emission tomography (PET) imaging as our biomarker of cerebral amyloidosis and 18fluorodeoxyglucose PET imaging and hippocampal volume as biomarkers of neurodegeneration. A group of 42 clinically diagnosed AD subjects was used to create imaging biomarker cut-points. A group of 450 cognitively normal (CN) subjects from a population based sample was used to develop cognitive cut-points and to assess population frequencies of the different preclinical AD stages using different cut-point criteria.
The new criteria subdivide the preclinical phase of AD into stages 1–3. To classify our CN subjects, two additional categories were needed. Stage 0 denotes subjects with normal AD biomarkers and no evidence of subtle cognitive impairment. Suspected Non-AD Pathophysiology (SNAP) denotes subjects with normal amyloid PET imaging, but abnormal neurodegeneration biomarker studies. At fixed cut-points corresponding to 90% sensitivity for diagnosing AD and the 10th percentile of CN cognitive scores, 43% of our sample was classified as stage 0; 16% stage 1; 12 % stage 2; 3% stage 3; and 23% SNAP.
This cross-sectional evaluation of the NIA-AA criteria for preclinical AD indicates that the 1–3 staging criteria coupled with stage 0 and SNAP categories classify 97% of CN subjects from a population-based sample, leaving just 3% unclassified. Future longitudinal validation of the criteria will be important.
The objective of our study was to evaluate whether cognitively normal (CN) elderly participants showing elevated cortical beta-amyloid (Aβ) deposition have a consistent neuroanatomical signature of brain atrophy that may characterize preclinical Alzheimer's disease (AD). 115 CN participants who were Aβ-positive (CN +) by amyloid PET imaging; 115 CN participants who were Aβ-negative (CN −); and 88 Aβ-positive mild cognitive impairment or AD participants (MCI/AD +) were identified. Cortical thickness (FreeSurfer) and gray matter volume (SPM5) were measured for 28 regions-of-interest (ROIs) across the brain and compared across groups. ROIs that best discriminated CN − from CN + differed for FreeSurfer cortical thickness and SPM5 gray matter volume. Group-wise discrimination was poor with a high degree of uncertainty in terms of the rank ordering of ROIs. In contrast, both techniques showed strong and consistent findings comparing MCI/AD + to both CN − and CN + groups, with entorhinal cortex, middle and inferior temporal lobe, inferior parietal lobe, and hippocampus providing the best discrimination for both techniques. Concordance across techniques was higher for the CN − and CN + versus MCI/AD + comparisons, compared to the CN − versus CN + comparison. The weak and inconsistent nature of the findings across technique in this study cast doubt on the existence of a reliable neuroanatomical signature of preclinical AD in elderly PiB-positive CN participants.
► We measured atrophy in cognitively normal subjects with amyloid deposition (CN +). ► Findings in CN + subjects were weak and disconcordant across Freesurfer and SPM5. ► Concordance across techniques was higher when assessing Alzheimer disease subjects. ► Evidence for a neuroanatomical signature of preclinical AD in CN + subjects is weak.
Amyloid; Preclinical; Alzheimer's disease; Freesurfer; Voxel-based morphometry; Cognitively normal
Imaging biomarkers are useful outcome measures in treatment trials. We compared sample size estimates for future treatment trials performed over 6 or 12-months in progressive supranuclear palsy using both imaging and clinical measures. We recruited 16 probable progressive supranuclear palsy patients that underwent baseline, 6 and 12 month brain scans, and 16 age-matched controls with serial scans. Disease severity was measured at each time-point using the progressive supranuclear palsy rating scale. Rates of ventricular expansion and rates of atrophy of the whole brain, superior frontal lobe, thalamus, caudate and midbrain were calculated. Rates of atrophy and clinical decline were used to calculate sample sizes required to power placebo-controlled treatment trials over 6 and 12-months. Rates of whole brain, thalamus and midbrain atrophy, and ventricular expansion, were increased over 6 and 12-months in progressive supranuclear palsy compared to controls. The progressive supranuclear palsy rating scale increased by 9 points over 6-months, and 18 points over 12-months. The smallest sample size estimates for treatment trials over 6-months were achieved using rate of midbrain atrophy, followed by rate of whole brain atrophy and ventricular expansion. Sample size estimates were further reduced over 12-month intervals. Sample size estimates for the progressive supranuclear palsy rating scale were worse than imaging measures over 6-months, but comparable over 12-months. Atrophy and clinical decline can be detected over 6-months in progressive supranuclear palsy. Sample size estimates suggest that treatment trials could be performed over this interval, with rate of midbrain atrophy providing the best outcome measure.
Progressive supranuclear palsy; atrophy; midbrain; power calculations; short interval
Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain’s modular organization and assign each region to a “meta-modular” group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer’s dementia and 56 cognitively normal elderly subjects matched 1∶2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer’s disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer’s dementia.
The common neurodegenerative pathologies underlying dementia are Alzheimer’s disease (AD), Lewy body disease (LBD) and Frontotemporal lobar degeneration (FTLD). Our aim was to identify patterns of atrophy unique to each of these diseases using antemortem structural-MRI scans of pathologically-confirmed dementia cases and build an MRI-based differential diagnosis system. Our approach of creating atrophy maps using structural-MRI and applying them for classification of new incoming patients is labeled Differential-STAND (Differential-diagnosis based on STructural Abnormality in NeuroDegeneration). Pathologically-confirmed subjects with a single dementing pathologic diagnosis who had an MRI at the time of clinical diagnosis of dementia were identified: 48 AD, 20 LBD, 47 FTLD-TDP (pathology-confirmed FTLD with TDP-43). Gray matter density in 91 regions-of-interest was measured in each subject and adjusted for head-size and age using a database of 120 cognitively normal elderly. The atrophy patterns in each dementia type when compared to pathologically-confirmed controls mirrored known disease-specific anatomic patterns: AD-temporoparietal association cortices and medial temporal lobe; FTLD-TDP-frontal and temporal lobes and LBD-bilateral amygdalae, dorsal midbrain and inferior temporal lobes. Differential-STAND based classification of each case was done based on a mixture model generated using bisecting k-means clustering of the information from the MRI scans. Leave-one-out classification showed reasonable performance compared to the autopsy gold-standard and clinical diagnosis: AD (sensitivity:90.7%; specificity:84 %), LBD (sensitivity:78.6%; specificity:98.8%) and FTLD-TDP (sensitivity:84.4%; specificity:93.8%). The proposed approach establishes a direct a priori relationship between specific topographic patterns on MRI and “gold standard” of pathology which can then be used to predict underlying dementia pathology in new incoming patients.
MRI; Alzheimer’s disease; Lewy body disease; Frontotemporal lobar degeneration
A major recent discovery was the identification of an expansion of a non-coding GGGGCC hexanucleotide repeat in the C9ORF72 gene in patients with frontotemporal dementia and amyotrophic lateral sclerosis. Mutations in two other genes are known to account for familial frontotemporal dementia: microtubule-associated protein tau and progranulin. Although imaging features have been previously reported in subjects with mutations in tau and progranulin, no imaging features have been published in C9ORF72. Furthermore, it remains unknown whether there are differences in atrophy patterns across these mutations, and whether regional differences could help differentiate C9ORF72 from the other two mutations at the single-subject level. We aimed to determine the regional pattern of brain atrophy associated with the C9ORF72 gene mutation, and to determine which regions best differentiate C9ORF72 from subjects with mutations in tau and progranulin, and from sporadic frontotemporal dementia. A total of 76 subjects, including 56 with a clinical diagnosis of behavioural variant frontotemporal dementia and a mutation in one of these genes (19 with C9ORF72 mutations, 25 with tau mutations and 12 with progranulin mutations) and 20 sporadic subjects with behavioural variant frontotemporal dementia (including 50% with amyotrophic lateral sclerosis), with magnetic resonance imaging were included in this study. Voxel-based morphometry was used to assess and compare patterns of grey matter atrophy. Atlas-based parcellation was performed utilizing the automated anatomical labelling atlas and Statistical Parametric Mapping software to compute volumes of 37 regions of interest. Hemispheric asymmetry was calculated. Penalized multinomial logistic regression was utilized to create a prediction model to discriminate among groups using regional volumes and asymmetry score. Principal component analysis assessed for variance within groups. C9ORF72 was associated with symmetric atrophy predominantly involving dorsolateral, medial and orbitofrontal lobes, with additional loss in anterior temporal lobes, parietal lobes, occipital lobes and cerebellum. In contrast, striking anteromedial temporal atrophy was associated with tau mutations and temporoparietal atrophy was associated with progranulin mutations. The sporadic group was associated with frontal and anterior temporal atrophy. A conservative penalized multinomial logistic regression model identified 14 variables that could accurately classify subjects, including frontal, temporal, parietal, occipital and cerebellum volume. The principal component analysis revealed similar degrees of heterogeneity within all disease groups. Patterns of atrophy therefore differed across subjects with C9ORF72, tau and progranulin mutations and sporadic frontotemporal dementia. Our analysis suggested that imaging has the potential to be useful to help differentiate C9ORF72 from these other groups at the single-subject level.
frontotemporal dementia; magnetic resonance imaging; C9ORF72; tau; progranulin
Functions of the ADNI MRI core fall into three categories: (1) those of the central MRI core lab at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data, and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present (“ADNI-GO”) and future (“ADNI-2”, if funded) MRI protocol will be to maintain MRI methodological consistency in previously enrolled “ADNI-1” subjects who are followed longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor specific pilot sub-studies of arterial spin labeling perfusion, resting state functional connectivity and diffusion tensor imaging. One each of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multi-center (but single vendor) setting for these three emerging MRI applications.
The behavioural variant of frontotemporal dementia is a progressive neurodegenerative syndrome characterized by changes in personality and behaviour. It is typically associated with frontal lobe atrophy, although patterns of atrophy are heterogeneous. The objective of this study was to examine case-by-case variability in patterns of grey matter atrophy in subjects with the behavioural variant of frontotemporal dementia and to investigate whether behavioural variant of frontotemporal dementia can be divided into distinct anatomical subtypes. Sixty-six subjects that fulfilled clinical criteria for a diagnosis of the behavioural variant of frontotemporal dementia with a volumetric magnetic resonance imaging scan were identified. Grey matter volumes were obtained for 26 regions of interest, covering frontal, temporal and parietal lobes, striatum, insula and supplemental motor area, using the automated anatomical labelling atlas. Regional volumes were divided by total grey matter volume. A hierarchical agglomerative cluster analysis using Ward's clustering linkage method was performed to cluster the behavioural variant of frontotemporal dementia subjects into different anatomical clusters. Voxel-based morphometry was used to assess patterns of grey matter loss in each identified cluster of subjects compared to an age and gender-matched control group at P < 0.05 (family-wise error corrected). We identified four potentially useful clusters with distinct patterns of grey matter loss, which we posit represent anatomical subtypes of the behavioural variant of frontotemporal dementia. Two of these subtypes were associated with temporal lobe volume loss, with one subtype showing loss restricted to temporal lobe regions (temporal-dominant subtype) and the other showing grey matter loss in the temporal lobes as well as frontal and parietal lobes (temporofrontoparietal subtype). Another two subtypes were characterized by a large amount of frontal lobe volume loss, with one subtype showing grey matter loss in the frontal lobes as well as loss of the temporal lobes (frontotemporal subtype) and the other subtype showing loss relatively restricted to the frontal lobes (frontal-dominant subtype). These four subtypes differed on clinical measures of executive function, episodic memory and confrontation naming. There were also associations between the four subtypes and genetic or pathological diagnoses which were obtained in 48% of the cohort. The clusters did not differ in behavioural severity as measured by the Neuropsychiatric Inventory; supporting the original classification of the behavioural variant of frontotemporal dementia in these subjects. Our findings suggest behavioural variant of frontotemporal dementia can therefore be subdivided into four different anatomical subtypes.
behavioural variant frontotemporal dementia; atrophy; cluster analysis; voxel-based morphometry