18F–FDG PET diagnostic and prognostic patterns do not overlap in Alzheimer’s disease (AD) patients at the mild cognitive impairment (MCI) stage

Morbelli, Silvia; Bauckneht, Matteo; Arnaldi, Dario; Picco, Agnese; Pardini, Matteo; Brugnolo, Andrea; Buschiazzo, Ambra; Pagani, Marco; Girtler, Nicola; Nieri, Alberto; Chincarini, A.; Carli, Fabrizio De; Sambuceti, Gianmario; Nobili, Flavio

doi:10.1007/s00259-017-3790-5

Cited by 32 publications

(28 citation statements)

References 42 publications

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“…[23][24][25] Preserved metabolism in PCC was hereby confirmed, but we demonstrated that this finding is significantly dependent on the severity of cognitive impairment. 28,29 Previous studies in smaller groups suggested that FDG PET might be able to mirror clinical heterogeneity of DLB by showing core feature metabolic correlates, but firm conclusions on the interplay between core features and potentially confounding clinical and demographic variables, such as MMSE score, age, and education, were unfeasible. 26,27 Instead, the relatively preserved metabolism in bilateral MTL was less affected by the severity of cognitive impairment, was not affected by the region used as reference for intensity normalization, and thus may retain diagnosis utility at all stages.…”

Section: Discussionmentioning

confidence: 99%

“…FDG PET, as a general marker of neurodegeneration, may help in understanding the neurodegeneration processes leading to either one. 28,29 Previous studies in smaller groups suggested that FDG PET might be able to mirror clinical heterogeneity of DLB by showing core feature metabolic correlates, but firm conclusions on the interplay between core features and potentially confounding clinical and demographic variables, such as MMSE score, age, and education, were unfeasible. [30][31][32] Despite the relatively high number of patients, we could not directly compare subgroups according to individual core feature because "pure" subgrouping was hampered by the very low number of patients presenting only 1 core feature, as is the common clinical presentation of DLB.…”

Section: Discussionmentioning

confidence: 99%

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Metabolic patterns across core features in dementia with lewy bodies

Morbelli

Chincarini

Brendel

et al. 2019

Annals of Neurology

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Objective: To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern. Methods: Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map. Results: Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal View this article online at wileyonlinelibrary.com.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Metabolic patterns across core features in dementia with lewy bodies

Morbelli

Chincarini

Brendel

et al. 2019

Annals of Neurology

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“…Metabolic connectivity is a valuable concept in the fast‐developing field of brain connectivity, which less dependent on neurovascular coupling as in fMRI and are indicative of a presumed steady state of neuronal activity during the recording interval . Growing evidence indicates that metabolic connectivity may serve a marker of normal and pathological cognitive function . So far, many analysis models of metabolic connectivity are best established in neurodegenerative disorders, such as seed correlation or IRCA, PCA and independent components analysis, sparse inverse covariance estimation, and graph theory .…”

Section: Discussionmentioning

confidence: 95%

“…24,25 Growing evidence indicates that metabolic connectivity may serve a marker of normal and pathological cognitive function. [26][27][28] So far, many analysis models of metabolic connectivity are best established in neurodegenerative disorders, such as seed correlation or IRCA, PCA and independent components analysis, sparse inverse covariance estimation, and graph theory. 24 Here, we first adopted a covariance method to construct metabolic networks such as VBM or cortical thickness covariance networks and then used graph theory to parse them.…”

Section: Brain Metabolism and Metabolic Brain Covariance Networkmentioning

confidence: 99%

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy

Wang

Liu

et al. 2018

CNS Neurosci Ther

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Summary Objective We aimed to study the networks’ mechanism of metabolic covariance networks in mesial temporal lobe epilepsy (mTLE), through examining the brain value of fluorine‐18‐fluorodeoxyglucose positron emission tomography (18F‐FDG‐PET). Methods 18F‐FDG‐PET images from 16 patients with mTLE were analyzed using local and global metabolic covariance network (MCN) approaches, including whole metabolic pattern analysis (WMPA), hippocampus‐based (h‐) MCN, whole brain (w‐) MCN, and edge‐based connectivity analysis (EBCA). Results WMPA showed a typical ipsilateral hypometabolism and contralateral hypermetabolism pattern to epileptic zones in mTLE. h‐MCN revealed decreased hippocampus‐based synchronization in contralateral regions. w‐MCN exhibited a disrupted metabolic network with globally increased small‐world properties and regionally decreased nodal metrics in the ipsilateral hemisphere. Hippocampus (h)‐EBCA and whole brain EBCA (w‐EBCA) both detected a reduced‐connectivity dominated metabolic covariant network. Moreover, the reduced interhemisphere connectivity seemingly played a major role in the aberrant epileptic topological pattern. Conclusion From a metabolic point of view, we demonstrated the damaging effects with reduced contralateral intranetwork metrics properties and the compensatory effects in contralateral intranetworks with increased network properties. However, the import role of significant reduced interhemisphere connection has rarely been reported in other mTLE studies. Taken together, 18F‐FDG‐PET MCN analysis provides new evidence that the mTLE is a system neurological disorder with disrupted networks.

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“…As for ITG, significant hypometabolism is seen during early AD, despite minimal amyloid beta deposition (La Joie, et al, 2012; Scheff, et al, 2011). Hypometabolism in the ITG has been reported to be associated with conversion from MCI to AD (Convit, et al, 2000; Morbelli, et al, 2017). This region is involved in verbal fluency and its increased activity predicts better cognitive reserve in AD patients (Halawa, et al, 2019; Weissberger, et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Decoupling of inter-regional functional connectivity and regional neural activity in Alzheimer Disease

Maleki-Balajoo

Rahmani²,

Khosrowabadi

et al. 2019

Preprint

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199/200)Alzheimer's disease (AD) and mild cognitive impairment (MCI) are characterized by aberrant regional neural activity and disrupted inter-regional functional connectivity (FC). It is, however, poorly understood how changes in regional neural activity and inter-regional FC interact in AD and MCI. Here, we investigated the link between regional neural activity and nodal topological measures of FC through simultaneous PET/MR measurement in 20 patients with MCI, 33 patients with AD, and 26 healthy individuals. First, we assessed regional glucose metabolism identified through FDG-PET (rFDG) (as a proxy of regional neural activity), and regional FC topology through clustering coefficient (CC) and degree centrality (DC) (as surrogates of local segregation and global connectivity, respectively). Next, we examined the potential moderating effect of disease status (AD or MCI) on the link between rFDG and FC topology using hierarchical moderated multiple regression analysis. Alterations in rFDG, CC, and DC were widespread in patients, and AD alters physiological coupling between regional metabolism and functional connectivity particularly in the inferior temporal gyus and supplementary motor areas. While rFDG correlated with CC in healthy subjects, this correlation was lost in AD patients. We suggest that AD pathology decouples the normal association between regional neural activity and functional segregation.

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18F–FDG PET diagnostic and prognostic patterns do not overlap in Alzheimer’s disease (AD) patients at the mild cognitive impairment (MCI) stage

Cited by 32 publications

References 42 publications

Metabolic patterns across core features in dementia with lewy bodies

Metabolic patterns across core features in dementia with lewy bodies

Metabolic covariance networks combining graph theory measuring aberrant topological patterns in mesial temporal lobe epilepsy

Decoupling of inter-regional functional connectivity and regional neural activity in Alzheimer Disease

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