Resting state FDG-PET functional connectivity as an early biomarker of Alzheimer's disease using conjoint univariate and independent component analyses

Toussaint, Paule-Joanne; Perlbarg, Vincent; Bellec, Pierre; Désarnaud, Serge; Lacomblez, Lucette; Doyon, Julien; Habert, Marie Odile; Benali, Habib

doi:10.1016/j.neuroimage.2012.03.091

Cited by 93 publications

(80 citation statements)

References 72 publications

(79 reference statements)

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“…Thus, investigation of connectivity with (FDG-) PET has been considered as principally possible at a group level only. Yet, very recent evidence indicates encouraging properties of FDG-PET-based resting state connectivity at an individual level (Huang et al, 2010;Toussaint et al, 2012). To differentiate from functional connectivity as quantified with fMRI, here we use the term "metabolic connectivity" suggested by Lee et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

et al. 2013

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Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation to normal working memory (WM). Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC nodes as way points was performed in a subset of subjects.FDG uptake in the DMN nodes did not differ between high and low performers. However, significantly (p=0.01) lower metabolic connectivity was found in the group of low performers.Furthermore, as compared to high performers, low performers showed lower density of the left superior cingulate bundle.Verbal WM performance is related to metabolic and structural connectivity within the DMN in young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive marker of the normal variability in some cognitive functions.

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Section: Introductionmentioning

confidence: 99%

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

et al. 2013

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“…Actually, the sensitivity and specificity of [ 18 F]FDG PET (as well as of all AD biomarkers) depend largely on the method of interpretation, resulting in improved diagnostic and prognostic accuracy with software-aided reading [24]. In summary, we do not agree with the view of the authors of the Cochrane review that the variability in diagnostic performance represents the main limitation in the use of [ [41,42]. Three of these 19 studies used a normal reference population as the source of normative data, an approach that was not considered in the Cochrane review [38,39,41].…”

Section: Results Of the Cochrane Reviewmentioning

confidence: 63%

A Cochrane review on brain [18F]FDG PET in dementia: limitations and future perspectives

Morbelli

Garibotto

Giessen

et al. 2015

Eur J Nucl Med Mol Imaging

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“…Pattern recognition techniques can therefore be used to extract these patterns and to quantify their salience. This approach can be based on summing or averaging indices that measure deviation from normal (e.g., z or t scores) in brain regions that are typically affected in AD [31,32], or by multivariate techniques employing principal component analysis, independent component analysis, or machine learning [33][34][35][36]. Some of these measures have already been validated for use in multicentre studies (e.g., NEST-DD, ADNI) [37,38].…”

Section: Quantification Of Fdg Pet Studies In Dementiamentioning

confidence: 99%

The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia

Herholz

2014

Clin Transl Imaging

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Positron emission tomography (PET) with FDG or amyloid tracers is an important diagnostic tool, which also provides imaging biomarkers for patient selection in therapeutic trials in Alzheimer's disease. PET is also a quantitative technique with the potential to measure disease severity and progression. Limitations in spatial resolution result in partial volume effects that can be minimized by correction algorithms and image reconstruction with resolution recovery. Quantitative local rates of cerebral glucose metabolism can be calculated from FDG uptake. Reaching the highest degree of accuracy still requires blood sampling, while bloodless techniques have improved and can provide useful approximations. Advanced image processing techniques allow semiautomatic standardised assessment of diagnostic metabolic patterns and disease severity. Amyloid imaging provides excellent categorical classification of fibrillary amyloid deposition, but quantitative measures derived from amyloid tracer uptake are less well understood.

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Resting state FDG-PET functional connectivity as an early biomarker of Alzheimer's disease using conjoint univariate and independent component analyses

Cited by 93 publications

References 72 publications

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

A Cochrane review on brain [18F]FDG PET in dementia: limitations and future perspectives

The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia

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