Neural correlates of the DemTect in Alzheimer's disease and frontotemporal lobar degeneration – A combined MRI & FDG-PET study

Abstract

Valid screening devices are critical for an early diagnosis of dementia. The DemTect is such an internationally accepted tool. We aimed to characterize the neural networks associated with performance on the DemTect's subtests in two frequent dementia syndromes: early Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Voxel-based group comparisons of cerebral glucose utilization (as measured by F-18-fluorodeoxyglucose positron emission tomography) and gray matter atrophy (as measured by structural magnetic resonance imaging) were performed on data from 48 subjects with AD (n = 21), FTLD (n = 14) or subjective cognitive impairment (n = 13) as a control group. We performed group comparisons and correlation analyses between multimodal imaging data and performance on the DemTect's subtests. Group comparisons showed regional patterns consistent with previous findings for AD and FTLD. Interestingly, atrophy dominated in FTLD, whereas hypometabolism in AD. Across diagnostic groups performance on the “wordlist” subtest was positively correlated with glucose metabolism in the left temporal lobe. The “number transcoding” subtest was significantly associated with glucose metabolism in both a predominantly left lateralized frontotemporal network and a parietooccipital network including parts of the basal ganglia. Moreover, this subtest was associated with gray matter density in an extensive network including frontal, temporal, parietal and occipital areas. No significant correlates were observed for the “supermarket task” subtest. Scores on the “digit span reverse” subtest correlated with glucose metabolism in the left frontal cortex, the bilateral putamen, the head of caudate nucleus and the anterior insula. Disease-specific correlation analyses could partly verify or extend the correlates shown in the analyses across diagnostic groups. Correlates of gray matter density were found in FTLD for the “number transcoding” subtest and the “digit span reverse” subtest. Correlates of glucose metabolism were found in AD for the “wordlist” subtest and in FTLD for the “digit span reverse” subtest. Our study contributes to the understanding of the neural correlates of cognitive deficits in AD and FTLD and supports an external validation of the DemTect providing preliminary conclusions about disease-specific correlates.

Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses – The case of behavioral variant frontotemporal dementia

“…Although this fact might suggest a chronological process in bvFTD, this could not be confirmed with our data sample, as the investigated MRI and FDG-PET cohorts did only partly overlap. Accordingly, further longitudinal studies have to explore whether the different imaging approaches mirror a topographical and chronological hierarchical ‘nexopathic’ model as suggested for Alzheimer’s disease previously, where regional hypometabolism, presumably due to diaschisis/disconnection effects, is followed by regional atrophy (Chételat et al, 2008; Dukart et al, 2013b; Jack et al, 2010; Villain et al, 2008; Woost et al, 2013). The (meta-analytically) identified prototypical networks might be used as ‘hubs or networks of interest’ to increase individual diagnostic accuracy based on multimodal imaging and machine learning algorithms such as support vector machine classification (Dukart et al, 2011, 2013a), and to further the disease’s understanding with connectivity analyses (Farb et al, 2013; Filippi et al, 2013; Jech et al, 2013; Mueller et al, 2013; Seeley et al, 2009; Warren et al, 2012; Zhou et al, 2012).…”

Mapping brain morphological and functional conversion patterns in predementia late-onset bvFTD

“…All the default choices of SPM8 were followed with one exception. Since it has been shown that the use of the tracer unmatched PET template to normalize brain scans may generate inconsistent results [24] and because the default SPM brain PET template is an H 2 15 O template, a customized brain FDG PET template was used [24].…”

“…In another study a substantial overlap between hypometabolism and GM density reduction comparing MAPT gene carriers and noncarriers was found, but comparisons with healthy controls were not carried out [29]. In 14 patients with mild but overt FTD, including all FTD subtypes, atrophy and hypometabolism showed a greater overlap than in subjects with subjective cognitive impairment [15], but again FDG PET was more accurate than structural MRI in differentiating these 14 patients from controls [30]. Also, in FTD-amyotrophic lateral sclerosis complex a considerable overlap between atrophy and hypometabolism was found but hypometabolism exceeded atrophy in several regions [31].…”

“…Yet neuroimaging changes would be even more relevant during the predementia stage, as in AD where neuroimaging biomarkers increase the likelihood of diagnosis during the MCI stage [8]. It has been shown that both atrophy [9,10] and hypometabolism/hypoperfusion [6,[11][12][13][14][15][16][17] are detectable early in anterior cortical regions in overt FTD, when they can support the diagnosis [18] and help differentiate bvFTD from psychiatric disorders in the elderly [19]. In principle, hypometabolism/hypoperfusion, that are exquisitely sensitive to synaptic dysfunction [20], should be detectable earlier and be more extensive than atrophy [15,16,21] The aim of this study was to verify whether hypometabolism is more extensive than, and thus probably precedes, atrophy in patients with probable bvFTD investigated during the predementia stage.…”

Regional Brain Glucose Metabolism and Neurocognitive Function in Adult Survivors of Childhood Cancer Treated with Cranial Radiation

“…Glucose metabolism in frontal, parietal, and temporal lobes has been found to distinguish healthy aging adults from those diagnosed with Alzheimer disease, with 89% sensitivity and 86% specificity (10). 18 F-FDG PET has also demonstrated differences between Alzheimer and frontotemporal dementia (11), the latter of which is characterized by patterns of executive dysfunction (12) similar to those observed in adult survivors of childhood ALL (3). Frontotemporal dementia appears related to dysfunction in the frontostriatal circuit (12), a network involving reciprocal connections between dorsolateral frontal lobe regions and the basal ganglia.…”