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 model the temporal trajectory of β-amyloid accumulation using serial amyloid PET imaging.
Participants, aged 70–92 years, were enrolled in either the Mayo Clinic Study of Aging (n = 246) or the Mayo Alzheimer's Disease Research Center (n = 14). All underwent 2 or more serial amyloid PET examinations. There were 205 participants classified as cognitively normal and 55 as cognitively impaired (47 mild cognitive impairment and 8 Alzheimer dementia). We measured baseline amyloid PET-relative standardized uptake values (SUVR) and, for each participant, estimated a slope representing their annual amyloid accumulation rate. We then fit regression models to predict the rate of amyloid accumulation given baseline amyloid SUVR, and evaluated age, sex, clinical group, and APOE as covariates. Finally, we integrated the amyloid accumulation rate vs baseline amyloid PET SUVR association to an amyloid PET SUVR vs time association.
Rates of amyloid accumulation were low at low baseline SUVR. Rates increased to a maximum at baseline SUVR around 2.0, above which rates declined—reaching zero at baseline SUVR above 2.7. The rate of amyloid accumulation as a function of baseline SUVR had an inverted U shape. Integration produced a sigmoid curve relating amyloid PET SUVR to time. The average estimated time required to travel from an SUVR of 1.5–2.5 is approximately 15 years.
This roughly 15-year interval where the slope of the amyloid SUVR vs time curve is greatest and roughly linear represents a large therapeutic window for secondary preventive interventions.
We aimed to assess associations between clinical, imaging, pathological and genetic features and frontal lobe asymmetry in behavioral variant frontotemporal dementia (bvFTD). Volumes of the left and right dorsolateral, medial and orbital frontal lobes were measured in 80 bvFTD subjects and subjects were classified into three groups according to the degree of asymmetry (asymmetric left, asymmetric right, symmetric) using cluster analysis. The majority of subjects were symmetric (65%), with 20% asymmetric left and 15% asymmetric right. There were no clinical differences across groups, although there was a trend for greater behavioral dyscontrol in right asymmetric compared to left asymmetric subjects. More widespread atrophy involving the parietal lobe was observed in the symmetric group. Genetic features differed across groups with symmetric frontal lobes associated with C9ORF72 and tau mutations, while asymmetric frontal lobes were associated with progranulin mutations. These findings therefore suggest that neuroanatomical patterns of frontal lobe atrophy in bvFTD are influenced by specific gene mutations.
Frontotemporal dementia; frontal lobes; MRI; asymmetry; microtubule associated protein tau; progranulin; C9ORF72; pathology
Four subtypes of frontotemporal lobar degeneration with TDP-43 immunoreactive inclusions have been described (types A–D). Of these four subtypes, motor neuron disease is more commonly associated with type B pathology, but has also been reported with type A pathology. We have noted, however, the unusual occurrence of cases of type C pathology having corticospinal tract degeneration. We aimed to assess the severity of corticospinal tract degeneration in a large cohort of cases with type C (n = 31). Pathological analysis included semi-quantitation of myelin loss of fibres of the corticospinal tract and associated macrophage burden, as well as axonal loss, at the level of the medullary pyramids. We also assessed for motor cortex degeneration and fibre loss of the medial lemniscus/olivocerebellar tract. All cases were subdivided into three groups based on the degree of corticospinal tract degeneration: (i) no corticospinal tract degeneration; (ii) equivocal corticospinal tract degeneration; and (iii) moderate to very severe corticospinal tract degeneration. Clinical, genetic, pathological and imaging comparisons were performed across groups. Eight cases had no corticospinal tract degeneration, and 14 cases had equivocal to mild corticospinal tract degeneration. Nine cases, however, had moderate to very severe corticospinal tract degeneration with myelin and axonal loss. In these nine cases, there was degeneration of the motor cortex without lower motor neuron degeneration or involvement of other brainstem tracts. These cases most commonly presented as semantic dementia, and they had longer disease duration (mean: 15.3 years) compared with the other two groups (10.8 and 9.9 years; P = 0.03). After adjusting for disease duration, severity of corticospinal tract degeneration remained significantly different across groups. Only one case, without corticospinal tract degeneration, was found to have a hexanucleotide repeat expansion in the C9ORF72 gene. All three groups were associated with anterior temporal lobe atrophy on MRI; however, the cases with moderate to severe corticospinal tract degeneration showed right-sided temporal lobe asymmetry and greater involvement of the right temporal lobe and superior motor cortices than the other groups. In contrast, the cases with no or equivocal corticospinal tract degeneration were more likely to show left-sided temporal lobe asymmetry. For comparison, the corticospinal tract was assessed in 86 type A and B cases, and only two cases showed evidence of corticospinal tract degeneration without lower motor neuron degeneration. These findings confirm that there exists a unique association between frontotemporal lobar degeneration with type C pathology and corticospinal tract degeneration, with this entity showing a predilection to involve the right temporal lobe.
TDP-43 type C; corticospinal tract; MRI; semantic dementia; right temporal lobe
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
Secondary prevention trials in subjects with preclinical Alzheimer disease may require documentation of brain amyloidosis. The identification of inexpensive and noninvasive screening variables that can identify individuals who have significant amyloid accumulation would reduce screening costs.
A total of 483 cognitively normal (CN) individuals, aged 70–92 years, from the population-based Mayo Clinic Study of Aging, underwent Pittsburgh compound B (PiB)–PET imaging. Logistic regression determined whether age, sex, APOE genotype, family history, or cognitive performance was associated with odds of a PiB retention ratio >1.4 and >1.5. Area under the receiver operating characteristic curve (AUROC) evaluated the discrimination between PiB-positive and -negative subjects. For each characteristic, we determined the number needed to screen in each age group (70–79 and 80–89) to identify 100 participants with PiB >1.4 or >1.5.
A total of 211 (44%) individuals had PiB >1.4 and 151 (31%) >1.5. In univariate and multivariate models, discrimination was modest (AUROC ∼0.6–0.7). Multivariately, age and APOE best predicted odds of PiB >1.4 and >1.5. Subjective memory complaints were similar to cognitive test performance in predicting PiB >1.5. Indicators of PiB positivity varied with age. Screening APOE ε4 carriers alone reduced the number needed to screen to enroll 100 subjects with PIB >1.5 by 48% in persons aged 70–79 and 33% in those aged 80–89.
Age and APOE genotype are useful predictors of the likelihood of significant amyloid accumulation, but discrimination is modest. Nonetheless, these results suggest that inexpensive and noninvasive measures could significantly reduce the number of CN individuals needed to screen to enroll a given number of amyloid-positive subjects.
Atypical variants of Alzheimer’s disease (AD) have been pathologically defined based on the distribution of neurofibrillary tangles; hippocampal sparing (HpSp) AD shows minimal involvement of the hippocampus and limbic predominant (LP) AD shows neurofibrillary tangles restricted to the medial temporal lobe. We aimed to determine whether MRI patterns of atrophy differ across HpSp AD, LP AD and typical AD, and whether imaging could be a useful predictor of pathological subtype during life.
In this case-control study, we identified 177 patients who had been prospectively followed in the Mayo Clinic Alzheimer’s Disease Research Center, were demented during life, had AD pathology at autopsy (Braak stage ≥ IV, intermediate-high probability AD) and an antemortem MRI. Cases were assigned to one of three pathological subtypes (HpSp n=19, typical n=125, or LP AD n=33) based on neurofibrillary tangle counts and their ratio in association cortices to hippocampus, without reference to neuronal loss. Voxel-based morphometry and atlas-based parcellation were used to compare patterns of grey matter loss across groups, and to controls.
The severity of medial temporal and cortical grey matter atrophy differed across subtypes. The most severe medial temporal atrophy was observed in LP AD, followed by typical AD, and then HpSp AD. Conversely, the most severe cortical atrophy was observed in HpSp AD, followed by typical AD, and then LP AD. A ratio of hippocampal-to-cortical volume provided the best discrimination across all three AD subtypes. The majority of typical AD (98/125;78%) and LP AD (31/33;94%) subjects, but only 8/19 (42%) of the HpSp AD subjects, presented with a dominant amnestic syndrome.
Patterns of atrophy on MRI differ across the pathological subtypes of AD, suggesting that MR regional volumetrics reliably track the distribution of neurofibrillary tangle pathology and can predict pathological subtype during life.
US National Institutes of Health (National Institute on Aging)
Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Our objective was to determine whether the 11C–Pittsburgh Compound-B (PiB) retention and regional hypometabolism on PET and regional cortical atrophy on MRI are complementary in characterizing patients with DLB and differentiating them from AD. We studied age, gender and education matched patients with a clinical diagnosis of DLB (n=21), AD (n=21), and cognitively normal subjects (n=42). Hippocampal atrophy, global cortical PiB retention and occipital lobe metabolism in combination distinguished DLB from AD better than any of the measurements alone (area under the receiver operating characteristic=0.98).Five of the DLB and AD patients who underwent autopsy were distinguished through multimodality imaging. These data demonstrate that MRI and PiB PET contribute to characterizing the distinct pathological mechanisms in patients with AD compared to DLB. Occipital and posterior parietotemporal lobe hypometabolism is a distinguishing feature of DLB and this regional hypometabolic pattern is independent of the amyloid pathology.
Dementia with Lewy bodies; MRI; PET; FDG; PiB; Alzheimer's disease
To determine the association between the focal atrophy measures on antemortem MRI and postmortem neuropathologic classification of dementia with Lewy bodies (DLB) using the Third Report of the DLB Consortium criteria.
We retrospectively identified 56 subjects who underwent antemortem MRI and had Lewy body (LB) pathology at autopsy. Subjects were pathologically classified as high (n = 25), intermediate (n = 22), and low likelihood DLB (n = 9) according to the Third Report of the DLB Consortium criteria. We included 2 additional pathologic comparison groups without LBs: one with low likelihood Alzheimer disease (AD) (control; n = 27) and one with high likelihood AD (n = 33). The associations between MRI-based volumetric measurements and the pathologic classification of DLB were tested with analysis of covariance by adjusting for age, sex, and MRI-to-death interval.
Antemortem hippocampal and amygdalar volumes increased from low to intermediate to high likelihood DLB (p < 0.001, trend test). Smaller hippocampal and amygdalar volumes were associated with higher Braak neurofibrillary tangle stage (p < 0.001). Antemortem dorsal mesopontine gray matter (GM) atrophy was found in those with high likelihood DLB compared with normal control subjects (p = 0.004) and those with AD (p = 0.01). Dorsal mesopontine GM volume decreased from low to intermediate to high likelihood DLB (p = 0.01, trend test).
Antemortem hippocampal and amygdalar volumes increase and dorsal mesopontine GM volumes decrease in patients with low to high likelihood DLB according to the Third Report of the DLB Consortium criteria. Patients with high likelihood DLB typically have normal hippocampal volumes but have atrophy in the dorsal mesopontine GM nuclei.
Acetylcholinesterase inhibitors are commonly used to treat patients with dementia with Lewy bodies. Hippocampal atrophy on magnetic resonance imaging and amyloid-β load on positron emission tomography are associated with the Alzheimer’s disease-related pathology in patients with dementia with Lewy bodies. To date, few studies have investigated imaging markers that predict treatment response in patients with dementia with Lewy bodies. Our objective was to determine whether imaging markers of Alzheimer’s disease-related pathology such as hippocampal volume, brain amyloid-β load on 11C Pittsburgh compound B positron emission tomography predict treatment response to acetylcholinesterase inhibitors in patients with dementia with Lewy bodies. We performed a retrospective analysis on consecutive treatment-naive patients with dementia with Lewy bodies (n = 54) from the Mayo Clinic Alzheimer’s Disease Research Centre who subsequently received acetylcholinesterase inhibitors and underwent magnetic resonance imaging with hippocampal volumetry. Baseline and follow-up assessments were obtained with the Mattis Dementia Rating Scale. Subjects were divided into three groups (reliable improvement, stable or reliable decline) using Dementia Rating Scale reliable change indices determined previously. Associations between hippocampal volumes and treatment response were tested with analysis of covariance adjusting for baseline Dementia Rating Scale, age, gender, magnetic resonance field strength and Dementia Rating Scale interval. Seven subjects underwent 11C Pittsburgh compound B imaging within 12 weeks of magnetic resonance imaging. Global cortical 11C Pittsburgh compound B retention (scaled to cerebellar retention) was calculated in these patients. Using a conservative psychometric method of assessing treatment response, there were 12 patients with reliable decline, 29 stable cases and 13 patients with reliable improvement. The improvers had significantly larger hippocampi than those that declined (P = 0.02) and the stable (P = 0.04) group. An exploratory analysis demonstrated larger grey matter volumes in the temporal and parietal lobes in improvers compared with those who declined (P < 0.05). The two patients who had a positive 11C Pittsburgh compound B positron emission tomography scan declined and those who had a negative 11C Pittsburgh compound B positron emission tomography scan improved or were stable after treatment. Patients with dementia with Lewy bodies who do not have the imaging features of coexistent Alzheimer’s disease-related pathology are more likely to cognitively improve with acetylcholinesterase inhibitor treatment.
dementia with Lewy bodies; acetylcholinesterase inhibitors; MRI; PiB; PET; amyloid
The association between antemortem [11C]-Pittsburgh Compound B (PiB) retention and β-amyloid (Aβ) load, Lewy body (LB) and neurofibrillary tangle (NFT) densities were investigated in a pathologically confirmed case of dementia with LB (DLB). 76-year-old man presenting with a clinical diagnosis of DLB had undergone PiB–positron emission tomography (PET), 18F FDG-PET and MRI 18 months before death. The pathologic diagnosis was DLB neocortical-type with low-likelihood of Alzheimer's disease by NIA-Reagan criteria. Sections from regions of interest (ROI) on post-mortem examination were studied. A significant correlation was found between cortical Aβ density and PiB retention in the 17 corresponding ROIs (r=0.899; p<0.0001). Bielschowsky silver stain revealed mostly sparse neocortical neuritic plaques; whereas diffuse plaques were frequent. There was no correlation between LB density and PiB retention (r=0.13; p=0.66); nor between NFT density and PiB retention (r=−0.36; p=0.17). The ROI-based analysis of imaging and histopathological data confirms that PiB uptake on PET is a specific marker for Aβ density, but cannot differentiate neuritic from diffuse amyloid plaques in this case with DLB.
Dementia with Lewy bodies; amyloid imaging; PET; pathology; amyloid
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
Alzheimer's disease (AD) can present with non-amnestic clinical syndromes. We investigated whether there is an imaging signature of AD pathology in these atypical subjects. We identified 14 subjects that had pathological AD, a non-amnestic presentation (i.e. atypical AD), and MRI. These subjects were matched to 14 with clinical and pathological AD (i.e. typical AD), 14 with the same non-amnestic presentations with frontotemporal lobar degeneration (FTLD) pathology, and 20 controls. Voxel-based morphometry and region-of-interest (ROI) analysis were used to assess patterns of grey matter loss. Loss was observed in the temporoparietal cortex in both typical and atypical AD, and showed significantly greater loss than FTLD. However, the medial temporal lobes were more severely affected in typical AD and FTLD compared to atypical AD. A ratio of hippocampal and temporoparietal volumes provided excellent discrimination of atypical AD from FTLD subjects. Temporoparietal atrophy may therefore provide a useful marker of the presence of AD pathology even in subjects with atypical clinical presentations, especially in the context of relative sparing of the hippocampus.
Alzheimer's disease; pathology; voxel-based morphometry; atypical presentation; frontotemporal lobar degeneration; temporoparietal cortex; hippocampus
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
Behavioural variant frontotemporal dementia is characterized by a change in comportment. It is associated with considerable functional decline over the course of the illness albeit with sometimes dramatic variability among patients. It is unknown whether any baseline features, or combination of features, could predict rate of functional decline in behavioural variant frontotemporal dementia. The aim of this study was to investigate the effects of different baseline clinical, neuropsychological, neuropsychiatric, genetic and anatomic predictors on the rate of functional decline as measured by the Clinical Dementia Rating Sum of Boxes scale. We identified 86 subjects with behavioural variant frontotemporal dementia that had multiple serial Clinical Dementia Rating Sum of Boxes assessments (mean 4, range 2–18). Atlas-based parcellation was used to generate volumes for specific regions of interest at baseline. Volumes were utilized to classify subjects into different anatomical subtypes using the advanced statistical technique of cluster analysis and were assessed as predictor variables. Composite scores were generated for the neuropsychological domains of executive, language, memory and visuospatial function. Behaviours from the brief questionnaire form of the Neuropsychiatric Inventory were assessed. Linear mixed-effects regression modelling was used to determine which baseline features predict rate of future functional decline. Rates of functional decline differed across the anatomical subtypes of behavioural variant frontotemporal dementia, with faster rates observed in the frontal dominant and frontotemporal subtypes. In addition, subjects with poorer performance on neuropsychological tests of executive, language and visuospatial function, less disinhibition, agitation/aggression and night-time behaviours at presentation, and smaller medial, lateral and orbital frontal lobe volumes showed faster rates of decline. In many instances, the effect of the predictor variables observed across all subjects was also preserved within anatomical subtypes. Furthermore, some of the predictor variables improved our prediction of rate of functional decline after anatomical subtype was taken into account. In particular, age at onset was a highly significant predictor but only after adjusting for subtype. We also found that although some predictor variables, for example gender, Mini-Mental State Examination score, and apathy/indifference, did not affect the rate of functional decline; these variables were associated with the actual Clinical Dementia Rating Sum of Boxes score estimated for any given time-point. These findings suggest that in behavioural variant frontotemporal dementia, rate of functional decline is driven by the combination of anatomical pattern of atrophy, age at onset, and neuropsychiatric characteristics of the subject at baseline.
frontotemporal dementia; behaviour; functional decline; brain volumes; mixed effects models
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
Frontotemporal lobar degeneration (FTLD) can be classified based on the presence of the microtubule associated protein tau and the TAR DNA binding protein-43 (TDP-43). Future treatments will likely target these proteins; therefore it is important to identify biomarkers to help predict protein biochemistry.
To determine whether there is an MRI signature pattern of tau or TDP-43 using a large cohort of FTLD subjects and to investigate how patterns of atrophy change according to disease severity using a large autopsy-confirmed cohort of FTLD subjects.
Patterns of grey matter loss were assessed using voxel-based morphometry in 37 tau-positive and 44 TDP-43 positive subjects compared to 35 age and gender-matched controls, and compared to each other. Comparisons were also repeated in behavioral variant frontotemporal dementia (bvFTD) subjects (n=15 tau-positive and n=30 TDP-43 positive). Patterns of atrophy were also assessed according to performance on the clinical dementia rating (CDR) scale and mini-mental state examination (MMSE).
The tau-positive and TDP-43 positive groups showed patterns of frontotemporal grey matter loss compared to controls with no differences observed between the groups, for all subjects and for bvFTD subjects. Patterns of grey matter loss increased in a graded manner by CDR and MMSE with loss in the frontal lobes, insula and hippocampus in mild subjects, spreading to the temporal and parietal cortices and striatum in more advanced disease.
There is no signature pattern of atrophy for tau or TDP-43; however patterns of atrophy in FTLD progress with measures of clinical disease severity.
frontotemporal lobar degeneration; autopsy; tau; TAR DNA binding protein-43; voxel-based morphometry; Clinical Dementia Rating Scale; Mini-Mental State Examination
Twenty cognitively normal (CN), 17 amnestic mild cognitive impairment (aMCI), and 8 subjects with probable Alzheimer's disease (AD) were imaged with both magnetic resonance imaging (MRI) and the amyloid labeling ligand 11C Pittsburgh Compound B (PiB). PiB retention was quantified as the ratio of uptake in cortical regions of interest (ROIs) to the uptake in the cerebellar ROI in images acquired 40-60 minute post injection. A global cortical PiB retention summary measure was derived from six cortical ROIs. Statistical parametric mapping (SPM) and voxel-based morphometry (VBM) were used to evaluate PiB retention and grey matter loss on a 3D voxel-wise basis.
AD subjects had high global cortical PiB retention and low hippocampal volume; most CN subjects had low PiB retention and high hippocampal volume; and on average aMCI subjects were intermediate on both PiB and hippocampal volume. A target-to-cerebellar ratio of 1.5 was used to designate subjects as high vs. low PiB cortical retention. All AD subjects fell above this ratio as did 6/20 CN subjects and 9/17 MCI subjects, indicating bi-modal PiB retention in CN and aMCI. Interestingly, we found no consistent differences in learning and memory performance between high vs. low PiB CN subjects or high vs. low aMCI subjects.
The SPM/VBM voxel-wise comparisons of AD vs. CN subjects provided complementary information in that clear and meaningful similarities and differences in topographic distribution of amyloid deposition and grey matter loss were shown. The frontal lobes had high PiB retention with little grey matter loss. Anteromedial temporal areas had low PiB retention with significant grey matter loss. Lateral temporoparietal association cortex displayed both significant PiB retention and grey matter loss.
A voxel-wise SPM conjunction analysis of PiB uptake revealed that subjects with high PiB retention (high CN, high aMCI, and AD) shared a common PiB retention topographic pattern regardless of clinical category, and this PiB topographic pattern matched that of amyloid plaque distribution that has been established in autopsy studies of AD.
Both global cortical PiB retention and hippocampal volumes demonstrated significant correlation in the expected direction with cognitive testing performance; however, correlations were stronger with MRI than PiB. Pair-wise inter-group diagnostic separation was significant for all group-wise pairs for both PiB and hippocampal volume with the exception of CN vs. aMCI which was not significant for PiB. PiB and MRI provided complementary information such that clinical diagnostic classification with both, in combination, was superior to either alone.
Alzheimer's disease; Mild Cognitive Impairment; Pittsburgh Compound B; amyloid imaging; Magnetic Resonance Imaging; hippocampus
The purpose of this study was to use serial imaging to gain insight into the sequence of pathologic events in Alzheimer's disease, and the clinical features associated with this sequence. We measured change in amyloid deposition over time using serial 11C Pittsburgh compound B (PIB) positron emission tomography and progression of neurodegeneration using serial structural magnetic resonance imaging. We studied 21 healthy cognitively normal subjects, 32 with amnestic mild cognitive impairment and 8 with Alzheimer's disease. Subjects were drawn from two sources—ongoing longitudinal registries at Mayo Clinic, and the Alzheimer's disease Neuroimaging Initiative (ADNI). All subjects underwent clinical assessments, MRI and PIB studies at two time points, approximately one year apart. PIB retention was quantified in global cortical to cerebellar ratio units and brain atrophy in units of cm3 by measuring ventricular expansion. The annual change in global PIB retention did not differ by clinical group (P = 0.90), and although small (median 0.042 ratio units/year overall) was greater than zero among all subjects (P < 0.001). Ventricular expansion rates differed by clinical group (P < 0.001) and increased in the following order: cognitively normal (1.3 cm3/year) < amnestic mild cognitive impairment (2.5 cm3/year) < Alzheimer's disease (7.7 cm3/year). Among all subjects there was no correlation between PIB change and concurrent change on CDR-SB (r = −0.01, P = 0.97) but some evidence of a weak correlation with MMSE (r =−0.22, P = 0.09). In contrast, greater rates of ventricular expansion were clearly correlated with worsening concurrent change on CDR-SB (r = 0.42, P < 0.01) and MMSE (r =−0.52, P < 0.01). Our data are consistent with a model of typical late onset Alzheimer's disease that has two main features: (i) dissociation between the rate of amyloid deposition and the rate of neurodegeneration late in life, with amyloid deposition proceeding at a constant slow rate while neurodegeneration accelerates and (ii) clinical symptoms are coupled to neurodegeneration not amyloid deposition. Significant plaque deposition occurs prior to clinical decline. The presence of brain amyloidosis alone is not sufficient to produce cognitive decline, rather, the neurodegenerative component of Alzheimer's disease pathology is the direct substrate of cognitive impairment and the rate of cognitive decline is driven by the rate of neurodegeneration. Neurodegeneration (atrophy on MRI) both precedes and parallels cognitive decline. This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration.
Alzheimer's disease; amyloid imaging; magnetic resonance imaging, longitudinal imaging; mild cognitive impairment; Pittsburgh compound B
Frontotemporal lobar degeneration (FTLD) can be classified based on the presence of the microtubule-associated protein tau and the TAR DNA binding protein-43 (TDP-43). Future treatments will likely target these proteins, therefore it is important to identify biomarkers to help predict protein biochemistry.
To determine whether there is an MRI signature pattern of tau or TDP-43 using a large cohort of FTLD subjects and to investigate how patterns of atrophy change according to disease severity using a large autopsy-confirmed cohort of FTLD subjects.
Patterns of gray matter loss were assessed using voxel-based morphometry in 37 tau-positive and 44 TDP-43-positive subjects compared to 35 age and gender-matched controls, and compared to each other. Comparisons were also repeated in behavioral variant frontotemporal dementia (bvFTD) subjects (n = 15 tau-positive and n = 30 TDP-43-positive). Patterns of atrophy were also assessed according to performance on the Clinical Dementia Rating (CDR) scale and Mini-Mental State Examination (MMSE).
The tau-positive and TDP-43-positive groups showed patterns of frontotemporal gray matter loss compared to controls with no differences observed between the groups, for all subjects and for bvFTD subjects. Patterns of gray matter loss increased in a graded manner by CDR and MMSE with loss in the frontal lobes, insula and hippocampus in mild subjects, spreading to the temporal and parietal cortices and striatum in more advanced disease.
There is no signature pattern of atrophy for tau or TDP-43; however, patterns of atrophy in FTLD progress with measures of clinical disease severity.
Frontotemporal lobar degeneration; Autopsy; Tau; TAR DNA binding protein-43; Voxel-based morphometry; Clinical Dementia Rating Scale; Mini-Mental State Examination
To develop and validate a tool for Alzheimer's disease (AD) diagnosis in individual subjects using support vector machine (SVM) based classification of structural MR (sMR) images.
Libraries of sMR scans of clinically well characterized subjects can be harnessed for the purpose of diagnosing new incoming subjects.
190 patients with probable AD were age- and gender-matched with 190 cognitively normal (CN) subjects. Three different classification models were implemented: Model I uses tissue densities obtained from sMR scans to give STructural Abnormality iNDex (STAND)-score; and Models II and III use tissue densities as well as covariates (demographics and Apolipoprotein E genotype) to give adjusted-STAND (aSTAND)-score. Data from 140 AD and 140 CN were used for training. The SVM parameter optimization and training was done by four-fold cross validation. The remaining independent sample of 50 AD and 50 CN were used to obtain a minimally biased estimate of the generalization error of the algorithm.
The CV accuracy of Model II and Model III aSTAND-scores was 88.5% and 89.3% respectively and the developed models generalized well on the independent test datasets. Anatomic patterns best differentiating the groups were consistent with the known distribution of neurofibrillary AD pathology.
This paper presents preliminary evidence that application of SVM-based classification of an individual sMR scan relative to a library of scans can provide useful information in individual subjects for diagnosis of AD. Including demographic and genetic information in the classification algorithm slightly improves diagnostic accuracy.
support vector machines; classification; diagnosis; Alzheimer's