Distinct clinical and metabolic deficits in PCA and AD are not related to amyloid distribution

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Neurology (Impact Factor: 8.29). 05/2011; 76(21):1789-96. DOI: 10.1212/WNL.0b013e31821cccad
Source: PubMed


Patients with posterior cortical atrophy (PCA) often have Alzheimer disease (AD) at autopsy, yet are cognitively and anatomically distinct from patients with clinical AD. We sought to compare the distribution of β-amyloid and glucose metabolism in PCA and AD in vivo using Pittsburgh compound B (PiB) and FDG-PET.
Patients with PCA (n = 12, age 57.5 ± 7.4, Mini-Mental State Examination [MMSE] 22.2 ± 5.1), AD (n = 14, age 58.8 ± 9.6, MMSE 23.8 ± 6.7), and cognitively normal controls (NC, n = 30, age 73.6 ± 6.4) underwent PiB and FDG-PET. Group differences in PiB distribution volume ratios (DVR, cerebellar reference) and FDG uptake (pons-averaged) were assessed on a voxel-wise basis and by comparing binding in regions of interest (ROIs).
Compared to NC, both patients with AD and patients with PCA showed diffuse PiB uptake throughout frontal, temporoparietal, and occipital cortex (p < 0.0001). There were no regional differences in PiB binding between PCA and AD even after correcting for atrophy. FDG patterns in PCA and AD were distinct: while both groups showed hypometabolism compared to NC in temporoparietal cortex and precuneus/posterior cingulate, patients with PCA further showed hypometabolism in inferior occipitotemporal cortex compared to both NC and patients with AD (p < 0.05). Patients with AD did not show areas of relative hypometabolism compared to PCA.
Fibrillar amyloid deposition in PCA is diffuse and similar to AD, while glucose hypometabolism extends more posteriorly into occipital cortex. Further studies are needed to determine the mechanisms of selective network degeneration in focal variants of AD.

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    • "The fact that none of the seven estimated amyloid deposition components were significant predictors of clinical conditions is congruent with most studies, which have reported overlapping patterns of amyloid accumulation in distinct variants of AD ( Lehmann et al., 2013a ). Although single case reports and small series initially reported atypical binding patterns in AD-language and AD-visuospatial ( Ng et al., 2007 ), larger series have found a diffuse pattern indistinguishable from typical AD and dissociated from their focal structural and metabolic signatures ( de Souza et al., 2011 ; Lehmann et al., 2013a ; Leyton et al., 2011 ; Rabinovici et al., 2008 ; Rosenbloom et al., 2011 ). Other studies comparing PiB binding in early and late age-of-onset AD found that differences in cognitive profiles could not be explained by the distribution or burden of PiB, which was identical in the groups ( Rabinovici et al., 2010 ). "
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    ABSTRACT: The relationships between clinical phenotype, β-amyloid (Aβ) deposition and neurodegeneration in Alzheimer’s disease (AD) are incompletely understood yet have important ramifications for future therapy. The goal of this study was to utilize multimodality positron emission tomography (PET) data from a clinically heterogeneous population of patients with probable AD in order to: (1) identify spatial patterns of Aβ deposition measured by (11C)-labeled Pittsburgh Compound B (PiB-PET) and glucose metabolism measured by FDG-PET that correlate with specific clinical presentation, and (2) explore associations between spatial patterns of Aβ deposition and glucose metabolism across the AD population. We included all patients meeting criteria for probable AD (NIA-AA) who had undergone MRI, PiB and FDG-PET at our center (N = 46, mean age 63.0 ± 7.7, Mini-Mental State Examination 22.0 ± 4.8). Patients were subclassified based on their cognitive profiles into an amnestic/dysexecutive group (AD-memory; n = 27), a language-predominant group (AD-language; n = 10) and a visuospatial-predominant group (AD-visuospatial; n = 9). All patients were required to have evidence of amyloid deposition on PiB-PET. To capture the spatial distribution of Aβ deposition and glucose metabolism, we employed parallel independent components analysis (pICA), a method that enables joint analyses of multimodal imaging data. The relationships between PET components and clinical group were examined using a Receiver Operator Characteristic approach, including age, gender, education and apolipoprotein E ε4 allele carrier status as covariates. Results of the first set of analyses independently examining the relationship between components from each modality and clinical group showed three significant components for FDG: a left inferior frontal and temporoparietal component associated with AD-language (area under the curve [AUC] 0.82, p = 0.011), and two components associated with AD-visuospatial (bilateral occipito-parieto-temporal [AUC 0.85, p = 0.009] and right posterior cingulate cortex [PCC]/precuneus and right lateral parietal [AUC 0.69, p = 0.045]). The AD-memory associated component included predominantly bilateral inferior frontal, cuneus and inferior temporal, and right inferior parietal hypometabolism but did not reach significance (AUC 0.65, p = 0.062). None of the PiB components correlated with clinical group. Joint analysis of PiB and FDG with pICA revealed a correlated component pair, in which increased frontal and decreased PCC/precuneus PiB correlated with decreased FDG in frontal, occipital and temporal regions (partial r = 0.75, p < 0.0001). Using multivariate data analysis, this study reinforced the notion that clinical phenotype in AD is tightly linked to patterns of glucose hypometabolism but not amyloid deposition. These findings are strikingly similar to those of univariate paradigms and provide additional support in favor of specific involvement of the language network, higher-order visual network, and default mode network in clinical variants of AD. The inverse relationship between Aβ deposition and glucose metabolism in partially overlapping brain regions suggest that Aβ may exert both local and remote effects on brain metabolism. Applying multivariate approaches such as pICA to multimodal imaging data is a promising approach for unraveling the complex relationships between different elements of AD pathophysiology.
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    • "In neuropathologically confirmed cases, the authors found that PiB was slightly superior with a sensitivity of 89.5% for AD and specificity of 83%.13 However, PiB correlates poorly with the distribution of hypometabolism and clinical syndromes between different variants of AD.14 CSF biomarkers are also an area of active investigation in CBD. Borroni et al,15 for example, reported that CSF tau to Aβ ratio correlated with 99mTc-ECD single photon emission CT scan results suggestive of a diagnosis of Alzheimer's pathology, although also without neuropathological confirmation of diagnosis. "
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    • "Several studies have detected high PIB binding in patients with posterior cortical atrophy, a visuospatial/biparietal clinical syndrome often caused by AD [52-54]. Although single case reports and small series initially reported atypical binding patterns in PPA and posterior cortical atrophy [55], larger series have found a diffuse binding pattern in these syndromes that is indistinguishable from typical AD and dissociated from the focal structural and metabolic signatures of these syndromes (see PIB and FDG in AD vs. logopenic variant PPA in Figure 1) [50,51,53,54]. Similarly, a study comparing PIB binding in early and late age-of-onset AD found that differences in cognitive profiles (more global deficits in early-onset AD, and restricted amnesia in late-onset AD) could not be explained by the distribution or burden of PIB, which was identical in the two groups [45]. "
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    ABSTRACT: In the past decade, positron emission tomography (PET) with carbon-11-labeled Pittsburgh Compound B (PIB) has revolutionized the neuroimaging of aging and dementia by enabling in vivo detection of amyloid plaques, a core pathologic feature of Alzheimer's disease (AD). Studies suggest that PIB-PET is sensitive for AD pathology, can distinguish AD from non-AD dementia (for example, frontotemporal lobar degeneration), and can help determine whether mild cognitive impairment is due to AD. Although the short half-life of the carbon-11 radiolabel has thus far limited the use of PIB to research, a second generation of tracers labeled with fluorine-18 has made it possible for amyloid PET to enter the clinical era. In the present review, we summarize the literature on amyloid imaging in a range of neurodegenerative conditions. We focus on potential clinical applications of amyloid PET and its role in the differential diagnosis of dementia. We suggest that amyloid imaging will be particularly useful in the evaluation of mildly affected, clinically atypical or early age-at-onset patients, and illustrate this with case vignettes from our practice. We emphasize that amyloid imaging should supplement (not replace) a detailed clinical evaluation. We caution against screening asymptomatic individuals, and discuss the limited positive predictive value in older populations. Finally, we review limitations and unresolved questions related to this exciting new technique.
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