Relationship between simultaneously acquired resting-state regional cerebral glucose metabolism and functional MRI: A PET/MR hybrid scanner study (original) (raw)
Related papers
Frontiers in Neuroscience, 2020
In the past, determination of absolute values of cerebral metabolic rate of glucose (CMRGlc) in clinical routine was rarely carried out due to the invasive nature of arterial sampling. With the advent of combined PET/MR imaging technology, CMRGlc values can be obtained non-invasively, thereby providing the opportunity to take advantage of fully quantitative data in clinical routine. However, CMRGlc values display high physiological variability, presumably due to fluctuations in the intrinsic activity of the brain at rest. To reduce CMRGlc variability associated with these fluctuations, the objective of this study was to determine whether functional connectivity measures derived from resting-state fMRI (rs-fMRI) could be used to correct for these fluctuations in intrinsic brain activity. Methods: We studied 10 healthy volunteers who underwent a test-retest dynamic [18F]FDG-PET study using a fully integrated PET/MR system (Siemens Biograph mMR). To validate the non-invasive derivation of an image-derived input function based on combined analysis of PET and MR data, arterial blood samples were obtained. Using the arterial input function (AIF), parametric images representing CMRGlc were determined using the Patlak graphical approach. Both directed functional connectivity (dFC) and undirected functional connectivity (uFC) were determined between nodes in six major networks (Default mode network, Salience, L/R Executive, Attention, and Sensory-motor network) using either a bivariate-correlation (R coefficient) or a Multi-Variate AutoRegressive (MVAR) model. In addition, the performance of a regional connectivity measure, the fractional amplitude of low frequency fluctuations (fALFF), was also investigated. Results: The average intrasubject variability for CMRGlc values between test and retest was determined as (14 ±8%) with an average inter-subject variability of 25% at test and 15% at retest. The average CMRGlc value (umol/100 g/min) across all networks was 39 ±10 at test and increased slightly to 43 ±6 at retest. The R, MVAR and fALFF coefficients showed relatively large test-retest variability in comparison to the inter-subjects variability, resulting in poor reliability (intraclass correlation in the range of 0.11–0.65). More importantly, no significant relationship was found between the R coefficients (for uFC), MVAR coefficients (for dFC) or fALFF and corresponding CMRGlc values for any of the six major networks. Discussion: Measurement of functional connectivity within established brain networks did not provide a means to decrease the inter- or intrasubject variability of CMRGlc values. As such, our results indicate that connectivity measured derived from rs-fMRI acquired contemporaneously with PET imaging are not suited for correction of CMRGlc variability associated with intrinsic fluctuations of resting-state brain activity. Thus, given the observed substantial inter- and intrasubject variability of CMRGlc values, the relevance of absolute quantification for clinical routine is presently uncertain.
European Journal of Nuclear Medicine and Molecular Imaging, 2008
Purpose Regionally connected areas of the resting brain can be detected by fluorodeoxyglucose-positron emission tomography (FDG-PET). Voxel-wise metabolic connectivity was examined, and normative data were established by performing interregional correlation analysis on statistical parametric mapping of FDG-PET data. Materials and methods Characteristics of seed volumes of interest (VOIs) as functional brain units were represented by their locations, sizes, and the independent methods of their determination. Seed brain areas were identified as population-based gyral VOIs (n=70) or as populationbased cytoarchitectonic Brodmann areas (BA; n=28). FDG uptakes in these areas were used as independent variables in a general linear model to search for voxels correlated with average seed VOI counts. Positive correlations were searched in entire brain areas. Results In normal adults, one third of gyral VOIs yielded correlations that were confined to themselves, but in the others, correlated voxels extended to adjacent areas and/or contralateral homologous regions. In tens of these latter areas with extensive connectivity, correlated voxels were found across midline, and asymmetry was observed in the patterns of connectivity of left and right homologous seed VOIs. Most of the available BAs yielded correlations reaching contralateral homologous regions and/or neighboring areas. Extents of metabolic connectivity were not found to be related to seed VOI size or to the methods used to define seed VOIs. Conclusions These findings indicate that patterns of metabolic connectivity of functional brain units depend on their regional locations. We propose that interregional correlation analysis of FDG-PET data offers a means of examining voxel-wise regional metabolic connectivity of the resting human brain.
Brain Connectivity, 2016
The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI ''nuisance signals'' were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a ''nuisance signal,'' also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states.
Neuroimage, 1999
The [ 18 F]fluorodeoxyglucose ([ 18 F]FDG) method for measuring brain metabolism has not the wide clinical application that one might expect, partly because of its high cost and the complexity of the quantification procedure, but also because of reporting techniques based on region of interest (ROI) analysis, which are time-consuming and not fully objective. In this paper we report a clinical validation of statistical parametric mapping (SPM) using rCMRglc (quantitative) and radioactivity distribution (nonquantitative) [ 18 F]FDG PET data. We show that a 10-min noninteractive voxelbased SPM analysis on a standard workstation enables objective assessment, including localization in stereotactic space, of regional glucose consumption abnormalities, whose reliability can be assessed on statistical and clinical grounds. Clinical validity was established using a small series of patients with degenerative or developmental disorders, including probable Alzheimer's disease, progressive aphasia, multiple sclerosis, developmental specific language impairment, and epilepsy. Analysis of quantitative and nonquantitative data showed the same pattern of results, suggesting that, for clinical purposes, quantitation and invasive arterial cannulation can be avoided.
BMC nuclear medicine, 2006
The definite evaluation of the regional cerebral heterogeneity using perfusion and metabolism by a single modality of PET imaging has not been well addressed. Thus a statistical analysis of voxel variables from identical brain regions on metabolic and perfusion PET images was carried out to determine characteristics of the regional heterogeneity of F-18 FDG and O-15 H2O cerebral uptake in normal subjects. Fourteen normal subjects with normal CT and/or MRI and physical examination including MMSE were scanned by both F-18 FDG and O-15 H2O PET within same day with head-holder and facemask. The images were co-registered and each individual voxel counts (Q) were normalized by the global maximal voxel counts (M) as R = Q/M. The voxel counts were also converted to z-score map by z = (Q - mean)/SD. Twelve pairs of ROIs (24 total) were systematically placed on the z-score map at cortical locations 15-degree apart and identically for metabolism and perfusion. Inter- and intra-subject correlat...
2012
Abstract The human brain is inherently organized as separate networks, as has been widely revealed by resting-state functional magnetic resonance imaging (fMRI). Although the large-scale functional connectivity can be partially explained by the underlying white-matter structural connectivity, the question of whether the underlying functional connectivity is related to brain metabolic factors is still largely unanswered.
Concurrent CBF and CMRGlc changes during human brain activation by combined fMRI–PET scanning
NeuroImage, 2005
A novel approach for concurrent measurement of regional cerebral blood flow (CBF) and regional cerebral metabolic rate for glucose consumption (CMRGlc) in humans is proposed and validated in normal subjects during visual stimulation. 18 F-labeled fluorodeoxyglucose was administered during the measurement of CBF by continuous arterial spin labeled magnetic resonance imaging (MRI). Subsequent positron emission tomographic (PET) scanning demonstrated the distribution of labeled deoxyglucose during the MRI acquisition. An excellent concordance between regional CBF and regional CMRGlc during visual stimulation was found, consistent with previously published PET findings. Although initially validated using a brief, non-quantitative protocol, this approach can provide quantitative CBF and CMRGlc, with a broad range of potential applications in functional physiology and pathophysiology. D
Mapping the Relative Contribution of Gray Matter Activity vs. Volume in Brain PET: A New Approach
Journal of Neuroimaging, 2006
Interpretation of brain positron emission tomography (PET) in terms of function vs. structure is ambiguous owing to the partial volume effect (PVE). Therefore, observed differences in tracer distribution could reflect differences in either activity or volume, a problem that applies principally to gray matter (GM) since white matter (WM) virtually always has uniform activity. To assess the contribution of GM volume vs. activity, we implemented a method to directly compare PET images with underlying structure, and applied it to resting-state 18 Fluorodeoxy-glucose-PET (FDG) of healthy subjects. Methods. Average GM and WM PVE-corrected mean FDG uptake values were applied onto co-registered segmented magnetic resonance imaging data sets to generate a "virtual PET" in which activity is proportional to GM volume and resolution set to that of PET. The raw PET and virtual PET values were then compared across the sample of subjects, first voxel-wise to detect clusters with significant activity-volume mismatch, and second within regions-of-interest (ROI) to quantify mismatches between unsmoothed voxel values. Results. Relative to volume, there
NeuroImage, 2021
Functional connectivity (FC) and resting-state network (RSN) analyses using functional magnetic resonance imaging (fMRI) have evolved into a growing field of research and have provided useful biomarkers for the assessment of brain function in neurological disorders. However, the underlying mechanisms of the blood oxygen level-dependant (BOLD) signal are not fully resolved due to its inherent complexity. In contrast, [ 18 F]fluorodeoxyglucose positron emission tomography ([ 18 F]FDG-PET) has been shown to provide a more direct measure of local synaptic activity and may have additional value for the readout and interpretation of brain connectivity. We performed an RSN analysis from simultaneously acquired PET/fMRI data on a single-subject level to directly compare fMRI and [ 18 F]FDG-PET-derived networks during the resting state. Simultaneous [ 18 F]FDG-PET/fMRI scans were performed in 30 rats. Pairwise correlation analysis, as well as independent component analysis (ICA), were used to compare the readouts of both methods. We identified three RSNs with a high degree of similarity between PET and fMRI-derived readouts: the default-mode-like network (DMN), the basal ganglia network and the cerebellar-midbrain network. Overall, [ 18 F]FDG connectivity indicated increased integration between different, often distant, brain areas compared to the results indicated by the more segregated fMRIderived FC. Additionally, several networks exclusive to either modality were observed using ICA. These networks included mainly bilateral cortical networks of a limited spatial extent for fMRI and more spatially widespread networks for [ 18 F]FDG-PET, often involving several subcortical areas. This is the first study using simultaneous PET/fMRI to report RSNs subject-wise from dynamic [ 18 F]FDG tracer delivery and BOLD fluctuations with both independent component analysis (ICA) and pairwise correlation analysis in small animals. Our findings support previous studies, which show a close link between local synaptic glucose consumption and BOLD-fMRI-derived FC. However, several brain regions were exclusively attributed to either [ 18 F]FDG or BOLD-derived networks underlining the complementarity of this hybrid imaging approach, which may contribute to the understanding of brain functional organization and could be of interest for future clinical applications.