Do NIA‐AA criteria distinguish Alzheimer's disease from frontotemporal dementia?

Harris, Jennifer; Thompson, James C.; Gall, Claire; Richardson, Anna; Neary, David; Plessis, Daniel du; Pal, Piyali; Mann, David; Snowden, Julie S.; Jones, Matthew

doi:10.1016/j.jalz.2014.04.516

Cited by 26 publications

(22 citation statements)

References 38 publications

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“…The link between lvPPA and AD pathology raises the question whether the language characteristics of lvPPA mirror those seen in early‐onset AD, in which language problems typically constitute one component of a multi‐domain disorder that includes also deficits in episodic memory, working memory, visual perception, and spatial function, (Smits et al ., ; Snowden et al ., ). Reports have thus far been mixed with some authors describing logopenic‐type symptoms in non‐focal AD patients (Harris et al ., ) and other authors describing a differing language profile in patients with AD (Ahmed, de Jager, Haigh, & Garrard, ).…”

Section: Introductionmentioning

confidence: 85%

Neuropsychological differentiation of progressive aphasic disorders

Harris

Saxon

Jones

et al. 2018

Journal of Neuropsychology

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The differentiation of subtypes of primary progressive aphasia (PPA) remains challenging. We aimed to identify optimum neuropsychological measures for characterizing PPA, to examine the relationship between behavioural change and subtypes of PPA and to determine whether characteristic profiles of language, working memory, and behavioural changes occur in PPA. Forty-seven patients with PPA and multi-domain Alzheimer's disease (AD) together with 19 age-matched controls underwent a large battery of working memory and language tests. We found that simple tasks of sentence ordering, narrative production, and buccofacial praxis were particularly useful in differentiating non-fluent/agrammatic variant PPA (nfvPPA) from other PPA subtypes, whereas a test of single word comprehension was useful in detecting semantic dementia (SD). No individual tests were discriminating for logopenic variant PPA (lvPPA) relative to nfvPPA. LvPPA and multidomain AD exhibited similar language profiles. A principal components analysis revealed that characteristic PPA profiles extended beyond the realms of language, in particular, the presence of apraxia in nfvPPA, behavioural changes in SD, and working memory deficits in lvPPA. These findings suggest that not all tests are equally discriminatory for PPA and highlight the importance of a test profile in differentiating PPA. These results also support the view that lvPPA is a focal form of AD and emphasize the difficulties classifying lvPPA.Current diagnostic recommendations for primary progressive aphasia (PPA) include three main subtypes: non-fluent/agrammatic (nfvPPA), characterized by agrammatism and/or apraxia of speech (AOS); logopenic (lvPPA), characterized by impaired repetition and word finding difficulties; and semantic (svPPA), characterized by anomia, impaired word comprehension, and impaired object recognition (Gorno-Tempini et al., 2011). The terms nfvPPA and svPPA are commonly used interchangeably with the earlier designations progressive non-fluent aphasia (PNFA) and semantic dementia (SD; Neary et al., 1998), although they are not precisely equivalent. In particular, the term SD acknowledges the multimodal nature of patients' semantic loss and the fact that the earliest presenting symptom may be in the visual rather than verbal domain. The three PPA

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Section: Introductionmentioning

confidence: 85%

Neuropsychological differentiation of progressive aphasic disorders

Harris

Saxon

Jones

et al. 2018

Journal of Neuropsychology

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“…Although clinical symptomatology differs between the diseases, symptoms in the early stage may be unclear and can overlap [2, 3]. The current clinical criteria, which entail qualitative inspection of neuroimaging, fail to accurately differentiate AD from FTD [4]. However, early and accurate differential diagnosis of AD and FTD is very important, mainly because it gives patients access to supportive therapies [5, 6].…”

Section: Introductionmentioning

confidence: 99%

Multiparametric computer-aided differential diagnosis of Alzheimer’s disease and frontotemporal dementia using structural and advanced MRI

et al. 2016

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ObjectivesTo investigate the added diagnostic value of arterial spin labelling (ASL) and diffusion tensor imaging (DTI) to structural MRI for computer-aided classification of Alzheimer's disease (AD), frontotemporal dementia (FTD), and controls.MethodsThis retrospective study used MRI data from 24 early-onset AD and 33 early-onset FTD patients and 34 controls (CN). Classification was based on voxel-wise feature maps derived from structural MRI, ASL, and DTI. Support vector machines (SVMs) were trained to classify AD versus CN (AD-CN), FTD-CN, AD-FTD, and AD-FTD-CN (multi-class). Classification performance was assessed by the area under the receiver-operating-characteristic curve (AUC) and accuracy. Using SVM significance maps, we analysed contributions of brain regions.ResultsCombining ASL and DTI with structural MRI resulted in higher classification performance for differential diagnosis of AD and FTD (AUC = 84%; p = 0.05) than using structural MRI by itself (AUC = 72%). The performance of ASL and DTI themselves did not improve over structural MRI. The classifications were driven by different brain regions for ASL and DTI than for structural MRI, suggesting complementary information.ConclusionsASL and DTI are promising additions to structural MRI for classification of early-onset AD, early-onset FTD, and controls, and may improve the computer-aided differential diagnosis on a single-subject level.Key points• Multiparametric MRI is promising for computer-aided diagnosis of early-onset AD and FTD. • Diagnosis is driven by different brain regions when using different MRI methods. • Combining structural MRI, ASL, and DTI may improve differential diagnosis of dementia. Electronic supplementary materialThe online version of this article (doi:10.1007/s00330-016-4691-x) contains supplementary material, which is available to authorized users.

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“…AD is mainly characterized by episodic memory impairment in the initial phase but deficits in visuospatial abilities, executive functioning, language and attention are also common ( Nestor et al, 2004 ; Smits et al, 2011 ). Clinical diagnostic criteria for bvFTD and AD have been proposed ( Rascovsky et al, 2011 ; McKhann et al, 2011 ), but the frequent overlap of clinical symptoms associated with AD and bvFTD and heterogeneity within one syndrome pose serious problems in the differential diagnosis ( Greicius et al, 2002 ; Miller et al, 2003 ; Walker et al, 2005 ; Harris et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study

Möller

Hafkemeijer

Pijnenburg

et al. 2015

NeuroImage: Clinical

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We investigated the ability of cortical and subcortical gray matter (GM) atrophy in combination with white matter (WM) integrity to distinguish behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) and from controls using voxel-based morphometry, subcortical structure segmentation, and tract-based spatial statistics. To determine which combination of MR markers differentiated the three groups with the highest accuracy, we conducted discriminant function analyses. Adjusted for age, sex and center, both types of dementia had more GM atrophy, lower fractional anisotropy (FA) and higher mean (MD), axial (L1) and radial diffusivity (L23) values than controls. BvFTD patients had more GM atrophy in orbitofrontal and inferior frontal areas than AD patients. In addition, caudate nucleus and nucleus accumbens were smaller in bvFTD than in AD. FA values were lower; MD, L1 and L23 values were higher, especially in frontal areas of the brain for bvFTD compared to AD patients. The combination of cortical GM, hippocampal volume and WM integrity measurements, classified 97–100% of controls, 81–100% of AD and 67–75% of bvFTD patients correctly. Our results suggest that WM integrity measures add complementary information to measures of GM atrophy, thereby improving the classification between AD and bvFTD.

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Do NIA‐AA criteria distinguish Alzheimer's disease from frontotemporal dementia?

Abstract: In patients with FTLD and predominantly early-onset AD, the NIA-AA AD dementia criteria have high specificity but lower sensitivity. The high specificity is due to the broad exclusion criteria.

Cited by 26 publications

References 38 publications

Neuropsychological differentiation of progressive aphasic disorders

Neuropsychological differentiation of progressive aphasic disorders

Multiparametric computer-aided differential diagnosis of Alzheimer’s disease and frontotemporal dementia using structural and advanced MRI

Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study

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