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1	Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology.
	Laforce, Robert; Tosun, Duygu; Ghosh, Pia; Lehmann, Manja; Madison, Cindee M; Weiner, Michael W; Miller, Bruce L; Jagust, William J; Rabinovici, Gil D. - : eScholarship, University of California, 2014
	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 ((11)C)-labeledPittsburgh 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 meetingthe 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 independentcomponent analysis (pICA), a method that enables joint analyses of multimodal imaging data. The relationships between PET components and clinical group were examined using aReceiver 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 (areaunder 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 whichincreased frontal and decreased PCC/precuneus PiB correlated with decreased FDG in the 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 suggests 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.
	Keyword: Acquired Cognitive Impairment; AD or AD-memory; AD-language or LPA; Aging; Alzheimer Disease; Alzheimer's disease; Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD); Amyloid beta-Peptides; Amyloid imaging; Aniline Compounds; area under the curve; AUC; Benzothiazoles; Biomarkers; Biomedical Imaging; Brain; Brain Disorders; Clinical Research; Computer-Assisted; Data Interpretation; Dementia; FDG-PET; Female; Fluorodeoxyglucose F18; Functional connectivity; Glucose; Humans; Image Interpretation; logopenic variant primary progressive aphasia; Male; Middle Aged; Multimodal Imaging; Multivariate data analysis; Networks; Neurodegenerative; Neurological; Neurosciences; Parallel ICA; PCA or AD-visuospatial; PCC; PiB-PET; Positron-Emission Tomography; posterior cingulate cortex; posterior cortical atrophy; posterior parietal cortex; PPC; Principal Component Analysis; Radiopharmaceuticals; Reproducibility of Results; Sensitivity and Specificity; Statistical; Thiazoles
	URL: https://escholarship.org/uc/item/1kn1q950
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2	Parallel ICA of FDG-PET and PiB-PET in three conditions with underlying Alzheimer's pathology.
	Laforce, Robert; Tosun, Duygu; Ghosh, Pia. - : eScholarship, University of California, 2014
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