Objective

To characterize the shape of the trajectories of Alzheimer’s Disease (AD) biomarkers as a function of MMSE.

Design

Longitudinal registries from the Mayo Clinic and the Alzheimer’s Disease Neuroimaging Initiative (ADNI).

Patients

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).

Results

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.

Conclusions

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.

Objective

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.

Methods

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.

Results

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.

Interpretation

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.

Pathology underlying behavioral variant frontotemporal dementia (bvFTD) is heterogeneous, with the most common pathologies being Pick’s disease (PiD), corticobasal degeneration (CBD), and FTLD-TDP type 1. Clinical features are unhelpful in differentiating these pathologies. We aimed to determine whether imaging atrophy patterns differ across these pathologies in bvFTD subjects. We identified 15 bvFTD subjects that had volumetric MRI during life and autopsy: five with PiD, five CBD and five FTLD-TDP type 1. Voxel-based morphometry was used to assess atrophy patterns in each bvFTD group compared to 20 age and gender-matched controls. All three pathological groups showed grey matter loss in frontal lobes, although specific patterns of atrophy differed across groups: PiD showed widespread loss in frontal lobes with additional involvement of anterior temporal lobes; CBD showed subtle patterns of loss involving posterior lateral and medial superior frontal lobe; FTLD-TDP type 1 showed widespread loss in frontal, temporal and parietal lobes. Greater parietal loss was observed in FTLD-TDP type 1 compared to both other groups, and greater anterior temporal and medial frontal loss was observed in PiD compared to CBD. Imaging patterns of atrophy in bvFTD vary according to pathological diagnosis and may therefore be helpful in predicting these pathologies in bvFTD.

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.

Objective

To report the clinical, electroencephalographic, and neuroradiologic findings in a kindred with a novel insertion in the prion protein gene (PRNP).

Design

Clinical description of a kindred.

Setting

Mayo Clinic Alzheimer’s Disease Research Center (Rochester).

Subjects

Two pathologically-confirmed cases and their relatives.

Main outcome measures

Clinical features, electroencephalographic patterns, magnetic resonance imaging abnormalities, genetic analyses and neuropathological features.

Results

The proband presented with clinical and neuroimaging features of atypical frontotemporal dementia (FTD) and ataxia. Generalized tonic-clonic seizures developed later in her course, and electroencephalography revealed spike and wave discharges but no periodic sharp wave complexes. Her affected sister and father also exhibited FTD-like features, and both experienced generalized tonic-clonic seizures and gait ataxia late in their course. Genetic analyses in the proband identified a novel defect in PRNP with one mutated allele carrying a 288 base pair insertion (BPI) consisting of 12 octapeptide repeats. Neuropathologic examination of the sister and proband revealed PrP-positive plaques and widespread tau-positive tangles.

Conclusion

This kindred has a unique combination of clinical and neuropathologic features associated with the largest BPI identified to date in PRNP, and underscores the need to consider familial prion disease in the differential diagnosis of a familial FTD-like syndrome.

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.

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.

Numerous kindreds with familial frontotemporal dementia and/or amyotrophic lateral sclerosis have been linked to chromosome 9, and an expansion of the GGGGCC hexanucleotide repeat in the non-coding region of chromosome 9 open reading frame 72 has recently been identified as the pathogenic mechanism. We describe the key characteristics in the probands and their affected relatives who have been evaluated at Mayo Clinic Rochester or Mayo Clinic Florida in whom the hexanucleotide repeat expansion were found. Forty-three probands and 10 of their affected relatives with DNA available (total 53 subjects) were shown to carry the hexanucleotide repeat expansion. Thirty-six (84%) of the 43 probands had a familial disorder, whereas seven (16%) appeared to be sporadic. Among examined subjects from the 43 families (n = 63), the age of onset ranged from 33 to 72 years (median 52 years) and survival ranged from 1 to 17 years, with the age of onset <40 years in six (10%) and >60 in 19 (30%). Clinical diagnoses among examined subjects included behavioural variant frontotemporal dementia with or without parkinsonism (n = 30), amyotrophic lateral sclerosis (n = 18), frontotemporal dementia/amyotrophic lateral sclerosis with or without parkinsonism (n = 12), and other various syndromes (n = 3). Parkinsonism was present in 35% of examined subjects, all of whom had behavioural variant frontotemporal dementia or frontotemporal dementia/amyotrophic lateral sclerosis as the dominant clinical phenotype. No subject with a diagnosis of primary progressive aphasia was identified with this mutation. Incomplete penetrance was suggested in two kindreds, and the youngest generation had significantly earlier age of onset (>10 years) compared with the next oldest generation in 11 kindreds. Neuropsychological testing showed a profile of slowed processing speed, complex attention/executive dysfunction, and impairment in rapid word retrieval. Neuroimaging studies showed bilateral frontal abnormalities most consistently, with more variable degrees of parietal with or without temporal changes; no case had strikingly focal or asymmetric findings. Neuropathological examination of 14 patients revealed a range of transactive response DNA binding protein molecular weight 43 pathology (10 type A and four type B), as well as ubiquitin-positive cerebellar granular neuron inclusions in all but one case. Motor neuron degeneration was detected in nine patients, including five patients without ante-mortem signs of motor neuron disease. While variability exists, most cases with this mutation have a characteristic spectrum of demographic, clinical, neuropsychological, neuroimaging and especially neuropathological findings.

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.

Objective

When using imaging to predict time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD), time-to-event statistical methods account for varying lengths of follow-up times among subjects whereas two-sample t-tests in voxel-based morphometry (VBM) do not. Our objectives were to apply a time-to-event voxel-based analytic method to identify regions on MRI where atrophy is associated with significantly increased risk of future progression to AD in subjects with MCI and to compare it to traditional voxel-level patterns obtained by applying two-sample methods. We also compared the power required to detect an association using time-to-event methods versus two-sample approaches.

Methods

Subjects with MCI at baseline were followed prospectively. The event of interest was clinical diagnosis of AD. Cox proportional hazards models adjusted for age, sex, and education were used to estimate the relative hazard of progression from MCI to AD based on rank-transformed voxel-level gray matter density (GMD) estimates.

Results

The greatest risk of progression to AD was associated with atrophy of the medial temporal lobes. Patients ranked at the 25th percentile of GMD in these regions had more than a doubling of risk of progression to AD at a given time-point compared to patients at the 75th percentile. Power calculations showed the time-to-event approach to be more efficient than the traditional two-sample approach.

Conclusions

We present a new voxel-based analytic method that incorporates time-to-event statistical methods. In the context of a progressive disease like AD, time-to-event VBM seems more appropriate and powerful than traditional two-sample methods.

Mutations in progranulin (PGRN) are associated with frontotemporal dementia with or without parkinsonism. We describe the prominent phenotypic variability within and among eight kindreds evaluated at Mayo Clinic Rochester and/or Mayo Clinic Jacksonville in whom mutations in PGRN were found. All available clinical, genetic, neuroimaging and neuropathologic data was reviewed. Age of onset ranged from 49 to 88 years and disease duration ranged from 1 to 14 years. Clinical diagnoses included frontotemporal dementia (FTD), primary progressive aphasia, FTD with parkinsonism, parkinsonism, corticobasal syndrome, Alzheimer’s disease, amnestic mild cognitive impairment, and others. One kindred exhibited maximal right cerebral hemispheric atrophy in all four affected individuals, while another had maximal left hemisphere involvement in all three of the affected. Neuropathologic examination of 13 subjects revealed frontotemporal lobar degeneration with ubiquitin-positive inclusions plus neuronal intranuclear inclusions in all cases. Age of onset, clinical phenotypes and MRI findings associated with most PGRN mutations varied significantly both within and among kindreds. Some kindreds with PGRN mutations exhibited lateralized topography of degeneration across all affected individuals.

We compare patterns of grey matter loss on MRI in subjects presenting as corticobasal syndrome (CBS) with Alzheimer disease pathology (CBS-AD) to those presenting as CBS with corticobasal degeneration pathology (CBS-CBD). Voxel-based morphometry was used to compare patterns of grey matter loss in pathologically confirmed CBS-AD subjects (n=5) and CBS-CBD subjects (n=6) to a group of normal controls (n=20), and to each other. Atlas based parcellation using the automated anatomic labeling atlas was also utilized in a region-of-interest analysis to account for laterality. The CBS-AD subjects were younger at the time of scan compared to CBS-CBD subjects (median: 60 years vs 69; P=0.04). After adjusting for age at time of MRI scan, the CBS-AD subjects showed loss in posterior frontal, temporal, and superior and inferior parietal lobes, while CBS-CBD showed more focal loss predominantly in the posterior frontal lobes, compared to controls. In both CBS-AD and CBS-CBD groups there was basal ganglia volume loss, yet relative sparing of hippocampi. On direct comparisons between the two subject groups, CBS-AD showed greater loss in both temporal and inferior parietal cortices than CBS-CBD. No regions showed greater loss in the CBS-CBD group compared to the CBS-AD group. These findings persisted when laterality was taken into account. In subjects presenting with CBS, prominent temporoparietal, especially posterior temporal and inferior parietal, atrophy may be a clue to the presence of underlying AD pathology.

Background and Purpose

Frontotemporal lobar degeneration (FTLD) can be subdivided into those in which the abnormal protein is tau (FTLD-TAU), the TAR DNA binding protein 43 (FTLD-TDP) and the fused in sarcoma protein (FTLD-FUS). We have observed severe caudate atrophy at autopsy in FTLD-FUS, and hence we aimed to determine whether caudate atrophy on MRI is a feature that can distinguish FTLD-FUS from FTLD-TDP and FTLD-TAU.

Methods

From a cohort of 207 cases of FTLD we identified all cases of FTLD-FUS that had a volumetric antemortem head MRI (n=3). Caudate and frontal lobe volumes were measured in all three cases using atlas based parcellation and SPM5, and were compared to 10 randomly selected cases of FTLD-TDP and 10 randomly selected cases of FTLD-TAU. Total grey matter volumes were also calculated for all cases.

Results

The FTLD-FUS cases had significantly smaller caudate volumes (p=0.02) yet similar frontal lobe grey matter volumes (p=0.12) compared to FTLD-TDP and FTLD-TAU. Caudate volumes when corrected for total grey matter volume (p=0.01) or frontal lobe grey matter volume (p=0.01) were significantly smaller in FTLD-FUS than FTLD-TDP and FTLD-TAU, and showed no overlap with the other two groups.

Conclusions

Caudate atrophy on MRI appears to be significantly greater in FTLD-FUS compared with FTLD-TDP and FTLD-TAU suggesting that severe caudate atrophy may be a useful clinical feature to predict FTLD-FUS pathology.

The clinical diagnosis of Alzheimer Disease (AD) does not exactly match the pathological findings at autopsy in every subject. Therefore, in-vivo imaging measures, such as Magnetic Resonance Imaging (MRI) that measure anatomical variations in each brain due to atrophy, would be clinically useful independent supplementary measures of pathology. We have developed an algorithm that extracts atrophy information from individual patient’s 3D MRI scans and assigns a STructural Abnormality iNDex (STAND)-score to the scan based on the degree of atrophy in comparison to patterns extracted from a large library of clinically well characterized AD and CN (cognitively normal) subject’s MRI scans. STAND-scores can be adjusted for demographics to give adjusted-STAND (aSTAND)-scores which are typically > 0 for subjects with abnormal brains. Since histopathological findings are considered to represent the “ground truth”, our objective was to assess the sensitivity of aSTAND-scores to pathological AD staging. This was done by comparing antemortem MRI based aSTAND-scores with post mortem grading of disease severity in 101 subjects who had both antemortem MRI and postmortem Braak neurofibrillary tangle (NFT) staging. We found a rank correlation of 0.62 (p<0.0001) between Braak NFT stage and aSTAND-scores. The results show that optimally extracted information from MRI scans such as STAND-scores accurately capture disease severity and can be used as an independent approximate surrogate marker for in-vivo pathological staging as well as for early identification of AD in individual subjects.

In the past 10 years, there has been a virtual explosion in the literature concerning the construct of mild cognitive impairment. The interest in this topic demonstrates the increasing emphasis on the identification of the earliest features of cognitive disorders such as Alzheimer’s disease and other dementias. Mild cognitive impairment represents the earliest clinical features of these conditions and, hence, has become a focus of clinical, epidemiological, neuroimaging, biomarker, neuropathological, disease mechanism and clinical trials research. This review summarizes the progress that has been made while also recognizing the challenges that remain.

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.

Background and Purpose

Decreased glucose metabolism in the temporal and parietal lobes on [18F]fluorodeoxyglucose (FDG) PET is recognized as an early imaging marker for the Alzheimer’s disease (AD) pathology. Our objective was to investigate the effects of age on FDG PET findings in aMCI.

Methods

25 patients with aMCI at 55–86 years of age (median = 73), and 25 age and gender matched cognitively normal (CN) subjects underwent FDG PET. SPM5 was used to compare the FDG uptake in aMCI-old (>73 years) and aMCI-young (>73 years) patients to CN subjects. The findings in the aMCI-old patients were independently validated in a separate cohort of 10 aMCI and 13 CN subjects older than 73 years of age.

Results

The pattern of decreased glucose metabolism and gray matter atrophy in the medial temporal, posterior cingulate, precuneus, lateral parietal and temporal lobes in aMCI-young subjects was consistent with the typical pattern observed in AD. The pattern of glucose metabolic changes in aMCI-old subjects was different, predominantly involving the frontal lobes and the left parietal lobe. Gray matter atrophy in aMCI-old subjects was less pronounced than the aMCI-young subjects involving the hippocampus and the basal forebrain in both hemispheres

Conclusion

Pathological heterogeneity may be underlying the absence of AD-like glucose metabolic changes in older compared to younger aMCI patients. This may be an important consideration for the clinical use of temporoparietal hypometabolism on FDG PET as a marker for early diagnosis of AD in aMCI.

Background

Semantic dementia (SD) is a syndrome within the spectrum of frontotemporal lobar degenerations (FTLD) characterized by fluent progressive aphasia (particularly anomia) and loss of word meaning.

Objective

To report a unique case of very early semantic dementia with slowly progressive course allowing insights into the early natural history of this disorder.

Design

Case report.

Setting

Tertiary care university hospital and academic center.

Patient

A 62-year-old female retired teacher presenting with “memory” complaints.

Main Outcome Measures

Clinical course, neuropsychological data, MRI.

Results

The patient was first evaluated when standard neuropsychological measures were normal, but subtle left anterior temporal lobe atrophy was present. Over the follow-up period of eight years, she developed profound anomia and loss of word meaning associated with progressive left anterior temporal lobe atrophy consistent with semantic dementia. In more recent years, anterograde memory impairment as well as mild prosopagnosia have evolved in association with left hippocampal atrophy and subtle atrophy in the homologous gyri of the right anterior temporal lobe. She remains functionally independent despite her current deficits.

Conclusions

Early identification of patients who will develop semantic dementia is difficult and might be missed with standard clinical, neuropsychological, and structural neuroimaging evaluations. Recognition of this relatively rare syndrome is important for early diagnosis and prognostication, and particularly for therapeutic interventions in the future.

The purpose of this study was to compare the diagnostic accuracy of glucose metabolism and amyloid deposition as demonstrated by 18F-FDG and Pittsburg Compound B (PiB) PET to evaluate subjects with cognitive impairment.

Methods

Subjects were selected from existing participants in the Mayo Alzheimer’s Disease Research Center or Alzheimer’s Disease Patient Registry programs. A total of 20 healthy controls and 17 amnestic mild cognitive impairment (aMCI), 6 nonamnestic mild cognitive impairment (naMCI), and 13 Alzheimer disease (AD) subjects were imaged with both PiB and 18F-FDG PET between March 2006 and August 2007. Global measures for PiB and 18F-FDG PET uptake, normalized to cerebellum for PiB and pons for 18F-FDG, were compared. Partial-volume correction, standardized uptake value (SUV), and cortical ratio methods of image analysis were also evaluated in an attempt to optimize the analysis for each test.

Results

Significant discrimination (P < 0.05) between controls and AD, naMCI and aMCI, naMCI and AD, and aMCI and AD by PiB PET measurements was observed. The paired groupwise comparisons of the global measures demonstrated that PiB PET versus 18F-FDG PET showed similar significant group separation, with only PiB showing significant separation of naMCI and aMCI subjects.

Conclusion

PiB PET and 18F-FDG PET have similar diagnostic accuracy in early cognitive impairment. However, significantly better group discrimination in naMCI and aMCI subjects by PiB, compared with 18F-FDG, was seen and may suggest early amyloid deposition before cerebral metabolic disruption in this group.

This study compares diagnostic accuracy of magnetic resonance (MR)-based hippocampal volumetry, single voxel (SV) 1H MR Spectroscopy (MRS) and MR diffusion weighted imaging (DWI) measurements in discriminating patients with amnestic mild cognitive impairment (MCI), Alzheimer’s disease (AD) and normally aging elderly. Sixty-one normally aging elderly, 24 MCI, and 22 AD patients underwent MR-based hippocampal volumetry, 1H MRS, and DWI. 1H MRS voxels were placed over both of the posterior cingulate gyri and N-acetyl aspartate (NAA) / creatine (Cr), myoinositol (MI) /Cr and NAA /MI ratios were obtained. Apparent diffusion coefficient (ADC) maps were derived from DWI and hippocampal borders were traced to measure hippocampal ADC. At 80% specificity, the most sensitive single measurement to discriminate MCI (79 %) and AD (86 %) from controls was hippocampal volumes. The most sensitive single measurement to discriminate AD from MCI was posterior cingulate gyrus NAA /Cr (67 %). At high specificity (>85 –90%) combinations of MR measures had superior diagnostic sensitivity compared to any single MR measurement for the AD vs. control and control vs. MCI comparisons. The MR measures that best discriminate more from less affected individuals along the cognitive continuum from normal to AD vary with disease severity. Selection of imaging measures used for clinical assessment or monitoring efficiency of therapeutic intervention should be tailored to the clinical stage of the disease.

Background

TAR DNA-binding protein 43 (TDP-43) is one of the major disease proteins in frontotemporal lobar degeneration with ubiquitin immunoreactivity. Approximately 1/4 of subjects with pathologically confirmed Alzheimer's disease (AD) have abnormal TDP-43 (abTDP-43) immunoreactivity. The aim of this study was to determine if subjects with pathologically confirmed AD and abTDP-43 immunoreactivity have distinct clinical, neuropsychological, imaging or pathological features compared to subjects with AD without abTDP-43 immunoreactivity.

Methods

Eighty-four subjects were identified that had a pathological diagnosis of AD, neuropsychometric testing, and volumetric MRI. Immunohistochemistry for TDP-43 was performed on sections of hippocampus and medial temporal lobe, and positive cases were classified into one of three types. Neuropsychometric data was collated and compared in subjects with and without abTDP-43 immunoreactivity. Voxel-based morphometry was used to assess patterns of gray matter atrophy in subjects with and without abTDP-43 immunoreactivity compared to age and gender matched controls.

Results

Twenty-nine (34%) of the 84 AD subjects had abTDP-43 immunoreactivity. Those with abTDP-43 immunoreactivity were older at onset and death, and performed worse on the Clinical Dementia Rating scale, Mini-Mental State Examination and Boston Naming Test than subjects without abTDP-43 immunoreactivity. Subjects with and without abTDP-43 immunoreactivity had medial temporal and temporoparietal gray matter loss compared to controls; however, those with abTDP-43 immunoreactivity showed greater hippocampal atrophy. Multivariate logistic regression adjusting for age at death demonstrated that hippocampal sclerosis was the only pathological predictor of abTDP-43 immunoreactivity.

Conclusions

The presence of abTDP-43 immunoreactivity is associated with a modified AD clinicopathological and radiological phenotype.

This study tests if measures of hippocampal water diffusivity at baseline can predict future progression to Alzheimer’s Disease (AD) in amnestic mild cognitive impairment (aMCI). Higher baseline hippocampal diffusivity was associated with a greater hazard of progression to AD in aMCI (p=0.002). MR diffusion weighted imaging (DWI) may help identify patients with aMCI who will progress to AD as well or better than structural MRI measures of hippocampal atrophy.

Objective

To determine the 1H MR spectroscopic (MRS) findings and inter-group differences among common dementias: Alzheimer's disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD).

Methods

We consecutively recruited 206 normal elderly, 121 patients with AD, 41 with FTLD, 20 with DLB, and 8 with VaD. We evaluated the 1H MRS metabolite ratio changes in common dementias with respect to normal, and also differences among the common dementias.

Results

N-acetylaspartate/Creatine (NAA/Cr) was lower than normal in patients with AD, FTLD, and VaD. Myo-inositol (mI)/Cr was higher than normal in patients with AD and FTLD. Choline (Cho)/Cr was higher than normal in patients with, AD, FTLD, and DLB. There were no metabolite differences between patients with AD and FTLD, nor between patients with DLB and VaD. NAA /Cr was lower in patients with AD and FTLD than DLB. MI /Cr was higher in patients with AD and FTLD than VaD. MI /Cr was also higher in patients with FTLD than DLB.

Conclusions

NAA/Cr levels are decreased in dementias that are characterized by neuron loss such as AD, FTLD, and VaD. MI/Cr levels are elevated in dementias that are pathologically characterized by gliosis such as AD and FTLD. Cho/Cr levels are elevated in dementias that are characterized by a profound cholinergic deficit such as AD and DLB.

Magnetic Resonance (MR)- based volume measurements of atrophy are potential markers of disease progression in patients with amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD). Longitudinal changes in 1H MR spectroscopy (1H MRS) metabolite markers have not been characterized in aMCI subjects. Our objective was to determine the longitudinal 1H MRS metabolite changes in patients with aMCI, and AD, and to compare 1H MRS metabolite ratios and ventricular volumes in tracking clinical disease progression in AD. The neuronal integrity marker N-acetylaspartate/Creatine ratio declined in aMCI and AD patients compared to cognitively normal elderly. The changein 1H MRS metabolite ratios correlated with clinical progression about as strongly as the rate of ventricular expansion, suggesting that 1H MRS metabolite ratios may be useful markers for the progression of AD. Choline/Creatine ratio declined in stable aMCI, compared to converter aMCI patients and cognitively normal elderly, which may be related to a compensatory mechanism in aMCI patients who did not to progress to AD.

The aim of this study was to examine the associations of Apolipoprotein E (APOE) genotype, metabolic changes in the posterior cingulate detected by 1H magnetic resonance spectroscopy (MRS), and neuropsychologic measures of memory and cognition both in normally aging elderly, and in patients with mild cognitive impairment (MCI) and AD. We studied 67 controls, 18 MCI and 33 AD patients. We used the Dementia Rating Scale total score (DRSTOT) as a measure of general cognitive function and the total learning from the Auditory Verbal Learning Test (AVTOT) as a measure of memory performance. No differences were noted on 1H MRS metabolite ratios or cognitive measures across APOE genotype within control and patient groups.. In controls, age was a significant predictor of both cognitive test scores, and NAA/Cr was a univariate associate of DRSTOT. All three 1H MRS metabolite ratios, N-acetylaspartate (NAA)/Creatine (Cr), myoinositol (MI)/Cr, and NAA/MI, were univariate associates of AVTOT and DRSTOT scores in the combined MCI and AD group. In stepwise regression analyses in the combined patient group only NAA/MI entered the model. These data suggest NAA/Cr could be a modest predictor of general cognitive function in both healthy elderly and impaired patients, while MI/Cr is a more specific marker for neuropsychologic dysfunction associated with neurodegenerative disease. Among 1H MRS measurements, the NAA/MI ratio maybe the most efficient predictor of memory and cognitive function in patients with MCI and AD.