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Article type: Research Article
Authors: Henkel, Rebeccaa; b | Brendel, Matthiasb | Paolini, Marcoa | Brendel, Evab | Beyer, Leonieb | Gutzeit, Andreasc | Pogarell, Oliverd | Rominger, Axele | Blautzik, Januscha; b; c; *
Affiliations: [a] Department of Radiology, University Hospital, LMU Munich, Munich, Germany | [b] Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany | [c] Institute for Radiology and Nuclear Medicine, Hirslanden Klinik St. Anna, Lucerne, Switzerland | [d] Department of Psychiatry, University Hospital, LMU Munich, Munich, Germany | [e] Department of Nuclear Medicine, Inselspital, University of Bern, Bern, Switzerland
Correspondence: [*] Correspondence to: Janusch Blautzik, Institute for Radiology and Nuclear Medicine, Hirslanden Klinik St. Anna, Sankt-Anna-Strasse 32, 6006 Lucerne, Switzerland. Tel.: +41 41 208 3030; E-mail: janusch.blautzik@hirslanden.ch.
Abstract: Background:Various reasons may lead to cognitive symptoms in elderly, including the development of cognitive decline and dementia. Often, mixed pathologies such as neurodegeneration and cerebrovascular disease co-exist in these patients. Diagnostic work-up commonly includes imaging modalities such as FDG PET, MRI, and CT, each delivering specific information. Objective:To study the informative value of neuroimaging-based data supposed to reflect neurodegeneration (FDG PET), cerebral small vessel disease (MRI), and cerebral large vessel atherosclerosis (CT) with regard to cognitive performance in patients presenting to our memory clinic. Methods:Non-parametric partial correlations and an ordinal logistic regression model were run to determine relationships between scores for cortical hypometabolism, white matter hyperintensities, calcified plaque burden, and results from Mini-Mental State Examination (MMSE). The final study group consisted of 162 patients (female: 94; MMSE: 6–30). Results:Only FDG PET data was linked to and predicted cognitive performance (r(157) = –0.388, p < 0.001). Overall, parameters linked to cerebral small and large vessel disease showed no significant association with cognition. Further findings demonstrated a relationship between white matter hyperintensities and FDG PET data (r(157) = 0.230, p = 0.004). Conclusion:Only FDG PET imaging mirrors cognitive performance, presumably due to the examination’s ability to reflect neurodegeneration and vascular dysfunction, thus capturing a broader spectrum of pathologies. This makes the examination a useful imaging-based diagnostic tool in the work-up of patients presenting to a memory clinic. Parameters of vascular dysfunction alone as depicted by conventional MRI and CT are less adequate in such a situation, most likely because they reflect one pathology complex only.
Keywords: Atherosclerosis, cognitive performance, computed tomography, FDG PET, magnetic resonance imaging, neurodegeneration, small vessel disease
DOI: 10.3233/JAD-200826
Journal: Journal of Alzheimer's Disease, vol. 78, no. 1, pp. 207-216, 2020
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