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1.  Corticospinal tract degeneration associated with TDP-43 type C pathology and semantic dementia 
Brain  2013;136(2):455-470.
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.
PMCID: PMC3572926  PMID: 23358603
TDP-43 type C; corticospinal tract; MRI; semantic dementia; right temporal lobe
2.  Imaging and acetylcholinesterase inhibitor response in dementia with Lewy bodies 
Brain  2012;135(8):2470-2477.
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.
PMCID: PMC3407425  PMID: 22810436
dementia with Lewy bodies; acetylcholinesterase inhibitors; MRI; PiB; PET; amyloid
4.  Characterizing a neurodegenerative syndrome: primary progressive apraxia of speech 
Brain  2012;135(5):1522-1536.
Apraxia of speech is a disorder of speech motor planning and/or programming that is distinguishable from aphasia and dysarthria. It most commonly results from vascular insults but can occur in degenerative diseases where it has typically been subsumed under aphasia, or it occurs in the context of more widespread neurodegeneration. The aim of this study was to determine whether apraxia of speech can present as an isolated sign of neurodegenerative disease. Between July 2010 and July 2011, 37 subjects with a neurodegenerative speech and language disorder were prospectively recruited and underwent detailed speech and language, neurological, neuropsychological and neuroimaging testing. The neuroimaging battery included 3.0 tesla volumetric head magnetic resonance imaging, [18F]-fluorodeoxyglucose and [11C] Pittsburg compound B positron emission tomography scanning. Twelve subjects were identified as having apraxia of speech without any signs of aphasia based on a comprehensive battery of language tests; hence, none met criteria for primary progressive aphasia. These subjects with primary progressive apraxia of speech included eight females and four males, with a mean age of onset of 73 years (range: 49–82). There were no specific additional shared patterns of neurological or neuropsychological impairment in the subjects with primary progressive apraxia of speech, but there was individual variability. Some subjects, for example, had mild features of behavioural change, executive dysfunction, limb apraxia or Parkinsonism. Voxel-based morphometry of grey matter revealed focal atrophy of superior lateral premotor cortex and supplementary motor area. Voxel-based morphometry of white matter showed volume loss in these same regions but with extension of loss involving the inferior premotor cortex and body of the corpus callosum. These same areas of white matter loss were observed with diffusion tensor imaging analysis, which also demonstrated reduced fractional anisotropy and increased mean diffusivity of the superior longitudinal fasciculus, particularly the premotor components. Statistical parametric mapping of the [18F]-fluorodeoxyglucose positron emission tomography scans revealed focal hypometabolism of superior lateral premotor cortex and supplementary motor area, although there was some variability across subjects noted with CortexID analysis. [11C]-Pittsburg compound B positron emission tomography binding was increased in only one of the 12 subjects, although it was unclear whether the increase was actually related to the primary progressive apraxia of speech. A syndrome characterized by progressive pure apraxia of speech clearly exists, with a neuroanatomic correlate of superior lateral premotor and supplementary motor atrophy, making this syndrome distinct from primary progressive aphasia.
PMCID: PMC3338923  PMID: 22382356
primary progressive apraxia of speech; apraxia of speech; primary progressive aphasia; voxel-based morphometry; diffusion tensor imaging; fluorodeoxyglucose; Pittsburg compound B; supplementary motor area
5.  Neuroimaging signatures of frontotemporal dementia genetics: C9ORF72, tau, progranulin and sporadics 
Brain  2012;135(3):794-806.
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.
PMCID: PMC3286334  PMID: 22366795
frontotemporal dementia; magnetic resonance imaging; C9ORF72; tau; progranulin
6.  Characterization of frontotemporal dementia and/or amyotrophic lateral sclerosis associated with the GGGGCC repeat expansion in C9ORF72 
Brain  2012;135(3):765-783.
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.
PMCID: PMC3286335  PMID: 22366793
frontotemporal dementia; amyotrophic lateral sclerosis; motor neuron disease; TDP-43; neurogenetics; chromosome 9
7.  Predicting functional decline in behavioural variant frontotemporal dementia 
Brain  2011;134(2):432-448.
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.
PMCID: PMC3030765  PMID: 21252111
frontotemporal dementia; behaviour; functional decline; brain volumes; mixed effects models
8.  Cognitive reserve and Alzheimer's disease biomarkers are independent determinants of cognition 
Brain  2011;134(5):1479-1492.
The objective of this study was to investigate how a measure of educational and occupational attainment, a component of cognitive reserve, modifies the relationship between biomarkers of pathology and cognition in Alzheimer's disease. The biomarkers evaluated quantified neurodegeneration via atrophy on magnetic resonance images, neuronal injury via cerebral spinal fluid t-tau, brain amyloid-β load via cerebral spinal fluid amyloid-β1–42 and vascular disease via white matter hyperintensities on T2/proton density magnetic resonance images. We included 109 cognitively normal subjects, 192 amnestic patients with mild cognitive impairment and 98 patients with Alzheimer's disease, from the Alzheimer's Disease Neuroimaging Initiative study, who had undergone baseline lumbar puncture and magnetic resonance imaging. We combined patients with mild cognitive impairment and Alzheimer's disease in a group labelled ‘cognitively impaired’ subjects. Structural Abnormality Index scores, which reflect the degree of Alzheimer's disease-like anatomic features on magnetic resonance images, were computed for each subject. We assessed Alzheimer's Disease Assessment Scale (cognitive behaviour section) and mini-mental state examination scores as measures of general cognition and Auditory–Verbal Learning Test delayed recall, Boston naming and Trails B scores as measures of specific domains in both groups of subjects. The number of errors on the American National Adult Reading Test was used as a measure of environmental enrichment provided by educational and occupational attainment, a component of cognitive reserve. We found that in cognitively normal subjects, none of the biomarkers correlated with the measures of cognition, whereas American National Adult Reading Test scores were significantly correlated with Boston naming and mini-mental state examination results. In cognitively impaired subjects, the American National Adult Reading Test and all biomarkers of neuronal pathology and amyloid load were independently correlated with all cognitive measures. Exceptions to this general conclusion were absence of correlation between cerebral spinal fluid amyloid-β1–42 and Boston naming and Trails B. In contrast, white matter hyperintensities were only correlated with Boston naming and Trails B results in the cognitively impaired. When all subjects were included in a flexible ordinal regression model that allowed for non-linear effects and interactions, we found that the American National Adult Reading Test had an independent additive association such that better performance was associated with better cognitive performance across the biomarker distribution. Our main conclusions included: (i) that in cognitively normal subjects, the variability in cognitive performance is explained partly by the American National Adult Reading Test and not by biomarkers of Alzheimer's disease pathology; (ii) in cognitively impaired subjects, the American National Adult Reading Test, biomarkers of neuronal pathology (structural magnetic resonance imaging and cerebral spinal fluid t-tau) and amyloid load (cerebral spinal fluid amyloid-β1–42) all independently explain variability in general cognitive performance; and (iii) that the association between cognition and the American National Adult Reading Test was found to be additive rather than to interact with biomarkers of Alzheimer's disease pathology.
PMCID: PMC3097887  PMID: 21478184
Alzheimer's disease; mild cognitive impairment; CSF biomarkers; MRI; cognitive reserve
9.  Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study 
Brain  2009;132(11):2932-2946.
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.
PMCID: PMC2768663  PMID: 19762452
behavioural variant frontotemporal dementia; atrophy; cluster analysis; voxel-based morphometry
10.  Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease 
Brain  2010;133(11):3336-3348.
Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.
PMCID: PMC2965425  PMID: 20935035
mild cognitive impairment; amyloid imaging; magnetic resonance imaging; cerebrospinal fluid; Alzheimer’s disease biomarkers
11.  Rates of cerebral atrophy differ in different degenerative pathologies 
Brain : a journal of neurology  2007;130(Pt 4):1148-1158.
Neurodegenerative disorders are pathologically characterized by the deposition of abnormal proteins in the brain. It is likely that future treatment trials will target the underlying protein biochemistry and it is therefore increasingly important to be able to distinguish between different pathologies during life. The aim of this study was to determine whether rates of brain atrophy differ in neurodegenerative dementias that vary by pathological diagnoses and characteristic protein biochemistry. Fifty-six autopsied subjects were identified with a clinical diagnosis of dementia and two serial head MRI. Subjects were subdivided based on pathological diagnoses into Alzheimer's disease (AD), dementia with Lewy bodies (DLB), mixed AD/DLB, frontotemporal lobar degeneration with ubiquitin-only-immunoreactive changes (FTLD-U), corticobasal degeneration (CBD) and progressive supranuclear palsy (PSP). Twenty-five controls were matched by age, gender, and scan interval, to the study cohort. The boundary-shift integral was used to calculate change over time in whole brain (BBSI) and ventricular volume (VBSI). All BSI results were annualized by adjusting for scan interval. The rates of whole brain atrophy and ventricular expansion were significantly increased compared to controls in the AD, mixed AD/DLB, FTLD-U, CBD and PSP groups. However, atrophy rates in the DLB group were not significantly different from control rates of atrophy. The largest rates of atrophy were observed in the CBD group which had a BBSI of 2.3% and VBSI of 16.2%. The CBD group had significantly greater rates of BBSI and VBSI than the DLB, mixed AD/DLB, AD and PSP groups, with a similar trend observed when compared to the FTLD-U group. The FTLD-U group showed the next largest rates with a BBSI of 1.7% and VBSI of 9.6% which were both significantly greater than the DLB group. There was no significant difference in the rates of atrophy between the AD, mixed AD/DLB and PSP groups, which all showed similar rates of atrophy; BBSI of 1.1, 1.3 and 1.0% and VBSI of 8.3, 7.2 and 10.9% respectively. Rates of atrophy therefore differ according to the pathological diagnoses and underlying protein biochemistry. While rates are unlikely to be useful in differentiating AD from cases with mixed AD/DLB pathology, they demonstrate important pathophysiological differences between DLB and those with mixed AD/DLB and AD pathology, and between those with CBD and PSP pathology.
PMCID: PMC2752409  PMID: 17347250
magnetic resonance imaging; Alzheimer's disease; dementia with Lewy bodies; frontotemporal lobar degeneration; progressive supranuclear palsy
12.  Clinicopathologic and Imaging Correlates of Progressive Aphasia and Apraxia of Speech 
Brain : a journal of neurology  2006;129(Pt 6):1385-1398.
Apraxia of speech (AOS) is a motor speech disorder characterized by slow speaking rate, abnormal prosody and distorted sound substitutions, additions, repetitions and prolongations, sometimes accompanied by groping and trial-and error articulatory movements. Although AOS is frequently subsumed under the heading of aphasia, and indeed most often co-occurs with aphasia, it can be the predominant or even the sole manifestation of a degenerative neurologic disease. In this study we determined whether the clinical classifications of aphasia and AOS correlated with pathological diagnoses and specific biochemical and anatomical structural abnormalities. Seventeen cases with initial diagnoses of a degenerative aphasia or AOS were reclassified independently by two speech-language pathologists — blinded to pathologic and biochemical findings - into one of five operationally defined categories of aphasia and AOS. Pathological diagnoses in the 17 cases were progressive supranuclear palsy in six, corticobasal degeneration in five, frontotemporal lobar degeneration with ubiquitin-only-immunoreactive changes in five, and Pick’s disease in one. Voxel-based morphometry and SPECT were completed, blinded to the clinical diagnoses, and clinico-imaging and clinico-pathological associations were then sought. Interjudge clinical classification reliability was 87% (κ =0.8) for all evaluations. Eleven cases had evidence of AOS, of which all (100%) had a pathological diagnosis characterized by underlying tau biochemistry, while five of the other six cases without AOS did not have tau biochemistry (p=0.001). A majority of the 17 cases had more than one yearly evaluation, demonstrating the evolution of the speech and language syndromes, as well as motor signs. Voxel-based morphometry revealed the premotor and supplemental motor cortices to be the main cortical regions associated with AOS, while the anterior peri-sylvian region was associated with non-fluent aphasia. Refining the classification of the degenerative aphasias and AOS may be necessary to improve our understanding of the relationships among behavioral, pathological, and imaging correlations.
PMCID: PMC2748312  PMID: 16613895
Premotor cortex; supplementary motor cortex; progressive supranuclear palsy; apraxia of speech; aphasia
13.  11C PiB and Structural MRI Provide Complementary Information in Imaging of AD and Amnestic MCI 
Brain : a journal of neurology  2008;131(Pt 3):665-680.
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.
PMCID: PMC2730157  PMID: 18263627
Alzheimer's disease; Mild Cognitive Impairment; Pittsburgh Compound B; amyloid imaging; Magnetic Resonance Imaging; hippocampus
14.  Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease 
Brain  2009;132(5):1355-1365.
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.
PMCID: PMC2677798  PMID: 19339253
Alzheimer's disease; amyloid imaging; magnetic resonance imaging, longitudinal imaging; mild cognitive impairment; Pittsburgh compound B
15.  Automatic classification of MR scans in Alzheimer’s disease 
Brain : a journal of neurology  2008;131(Pt 3):681-689.
To be diagnostically useful, structural MRI must reliably distinguish Alzheimer’s disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.
PMCID: PMC2579744  PMID: 18202106
Alzheimer’s; frontotemporal lobar degeneration; linear support vectors; classification

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