Dataset Information

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain.

ABSTRACT: Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMR_glc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMR_glc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMR_glc alterations compared to control were detected in all conditions except in congenitally blind where regional CMR_glc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMR_glc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMR_glc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMR_glc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMR_glc data in health and disease.

SUBMITTER: Mortensen KN

PROVIDER: S-EPMC6020504 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain.

Mortensen Kristian N KN Gjedde Albert A Thompson Garth J GJ Herman Peter P Parent Maxime J MJ Rothman Douglas L DL Kupers Ron R Ptito Maurice M Stender Johan J Laureys Steven S Riedl Valentin V Alkire Michael T MT Hyder Fahmeed F

Neural plasticity 20180612

Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMR<sub>glc</sub>) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMR<sub>glc</sub> with and without GMN in h ...[more]

PMID: 30008742

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Project description:Introduction: The disconnection hypothesis of Alzheimer's disease (AD) is supported by growing neuroimaging and neurophysiological evidence of altered brain functional connectivity in cognitively impaired individuals. Brain functional modalities such as [18F]fluorodeoxyglucose positron-emission tomography ([18F]FDG-PET) and electroencephalography (EEG) measure different aspects of synaptic functioning, and can contribute to understanding brain connectivity disruptions in AD. Aim: This study investigated the relationship between cortical glucose metabolism and topographical EEG measures of brain functional connectivity in subjects along AD continuum. Methods: Patients diagnosed with mild cognitive impairment (MCI) and AD (n = 67), and stratified into amyloid-positive (n = 32) and negative (n = 10) groups according to cerebrospinal fluid Aβ42/40 ratio, were assessed with [18F]FDG-PET and resting-state EEG recordings. EEG-based neuroimaging analysis involved standardized low-resolution electromagnetic tomography (sLORETA), which estimates functional connectivity from cortical sources of electrical activity in a 3D head model. Results: Glucose hypometabolism in temporoparietal lobes was significantly associated with altered EEG functional connectivity of the same regions of interest in clinically diagnosed MCI and AD patients and in patients with biomarker-verified AD pathology. The correlative pattern of disrupted connectivity in temporoparietal lobes, as detected by EEG sLORETA analysis, included decreased instantaneous linear connectivity in fast frequencies and increased lagged linear connectivity in slow frequencies in relation to the activity of remaining cortex. Conclusions: Topographical EEG measures of functional connectivity detect regional dysfunction of AD-vulnerable brain areas as evidenced by association and spatial overlap with the cortical glucose hypometabolism in MCI and AD patients. Impact statement The association between glucose hypometabolism, as evidenced by [18F]FDG-PET ([18F]fluorodeoxyglucose positron-emission tomography), and altered electroencephalography (EEG) functional connectivity metrics within temporoparietal lobes provides link between synaptic, neurophysiological, and metabolic impairment in mild cognitive impairment and Alzheimer's disease patients. This study reported alterations in EEG measures of both instantaneous and lagged linear connectivity across distinct frequency bands, both of which were shown to be important for inter- and intrahemispheric communication and function of memory systems in general. EEG-based imaging of brain functional connectivity has a potential to serve as a noninvasive, low-cost, and widely available alternative in assessing synaptic and network dysfunction in cognitively impaired patients.

Dataset Information

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain.

Publications

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain.

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