Title

Frontal Network Syndrome Testing: Clinical Tests And Positron Emission Tomography Brain Imaging Help Distinguish The 3 Most Common Dementia Subtypes

Keywords

dementia; frontal systems; neuropsychological testing; PET brain scan

Abstract

Background: Dementia diagnosis and the various subtypes are challenging in the absence of biomarkers. Aim: To examine available tests and neuroimaging procedures that may help distinguish these disorders. Methods: Alzheimer's disease (AD), cognitive vascular disorder (CVD), and Frontotemporal lobe disorders (FTLD) were tested with a hierarchical neuropsychological battery that included the Frontal Systems Behavior Scale, Mini-Mental State Examination, Montreal Cognitive Assessment Test, and subtests. All patients had multimodality magnetic resonance imaging and 18F fluorodeoxyglucose-positron emission tomography (FDG-PET) brain scans. Results: Of the 161 patients evaluated for dysmemory and cognitive impairment, 31 satisfied the full protocol. The mean T scores for the 3 principal frontal system syndromes for the AD group were all abnormal save disinhibition. For the CVD and FTLD groups, all the 4 subcategory scores were abnormal. Disinhibition differed significantly between the AD and FTD group (analysis of variance [ANOVA], P = .02) and there was a strong association between the memory for 5 words test and a significant difference in the word list generation test score among the 3 groups (ANOVA, P = .0233). There was a strong association between the FDG-PET and the disease subtype (P < .0001). Conclusion: Evaluation for disinhibition, word list generation, 5-word memory testing and PET brain imaging may help distinguish the 3 most common dementia subtypes. © The Author(s) 2013.

Publication Date

1-1-2013

Publication Title

American Journal of Alzheimer's Disease and other Dementias

Volume

28

Issue

5

Number of Pages

477-484

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1177/1533317513488920

Socpus ID

84881433487 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84881433487

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