Title:Hypometabolism in Brain of Cognitively Normal Patients with Depressive Symptoms is Accompanied by Atrophy-Related Partial Volume Effects
VOLUME: 13 ISSUE: 5
Author(s):Matthias Brendel, Veronika Reinisch, Eva Kalinowski, Johannes Levin, Andreas Delker, Sonja Därr, Oliver Pogarell, Stefan Förster, Peter Bartenstein, Axel Rominger and Alzheimer’s Disease Neuroimaging Initiative.
Affiliation:Department of Nuclear Medicine, University of Munich, Germany.
Keywords:Alzheimer's disease, depressive symptoms, FDG-PET, mild cognitive impairment, MRI, partial volume effect
correction.
Abstract:Late life depression (LLD) even in subsyndromal stages shows high conversion rates from
cognitively normal (CN) to mild cognitive impairment (MCI). Results of [18F]-fluorodesoxyglucose
positron-emission-tomography (FDG-PET) were inconsistent in LLD patients, whereas atrophy was
repeatedly described. Therefore, we set out to investigate FDG metabolism and the effect of atrophy
correction (PVEC) in geriatric CN patients with depressive symptoms. 21 CN subjects with positive
item for the depression category (DEP) in the Neuropsychiatric-Inventory-Questionnaire and 29 CN subjects with an absent
depression item (NON-DEP) were selected from the ADNI cohort. FDG-PETs were analyzed in individual PET
space using volumes-of-interest (VOI) and statistical-parametric-mapping (SPM) approaches. VOI- and MRI-based
PVEC were applied to PET data. DEP subjects showed significant hypometabolism in fronto-temporal cortices and the
posterior cingulate cortex (PCC) when contrasted against NON-DEP in uncorrected data. Both in VOI- and SPM-based
approaches PVEC eliminated significance in PCC, while fronto-temporal regions remained significant or even attained
significance such as in case of the left amygdala. Subsyndromally depressed CN subjects had decreased FDG metabolism
in mood-related brain regions, which may be relevant to their elevated risk for conversion from CN to MCI. Methodological
advances in PET analyses should be considered in future studies as PVEC relevantly changed results of FDG-PET for
detecting apparent metabolic differences between DEP and NON-DEP subjects. Furthermore, VOI-based analyses in individual
PET space will allow a more accurate consideration of variability in anatomy, especially in subcortical regions.
