16 research outputs found
Glia Imaging Differentiates Multiple System Atrophy from Parkinson's Disease: A Positron Emission Tomography Study with [C-11]PBR28 and Machine Learning Analysis
Background The clinical diagnosis of multiple system atrophy (MSA) is challenged by overlapping features with Parkinson's disease (PD) and late-onset ataxias. Additional biomarkers are needed to confirm MSA and to advance the understanding of pathophysiology. Positron emission tomography (PET) imaging of the translocator protein (TSPO), expressed by glia cells, has shown elevations in MSA. Objective In this multicenter PET study, we assess the performance of TSPO imaging as a diagnostic marker for MSA.Methods We analyzed [C-11]PBR28 binding to TSPO using imaging data of 66 patients with MSA and 24 patients with PD. Group comparisons were based on regional analysis of parametric images. The diagnostic readout included visual reading of PET images against clinical diagnosis and machine learning analyses. Sensitivity, specificity, and receiver operating curves were used to discriminate MSA from PD and cerebellar from parkinsonian variant MSA. Results We observed a conspicuous pattern of elevated regional [C-11]PBR28 binding to TSPO in MSA as compared with PD, with "hotspots" in the lentiform nucleus and cerebellar white matter. Visual reading discriminated MSA from PD with 100% specificity and 83% sensitivity. The machine learning approach improved sensitivity to 96%. We identified MSA subtype-specific TSPO binding patterns. Conclusions We found a pattern of significantly increased regional glial TSPO binding in patients with MSA. Intriguingly, our data are in line with severe neuroinflammation in MSA. Glia imaging may have potential to support clinical MSA diagnosis and patient stratification in clinical trials on novel drug therapies for an alpha-synucleinopathy that remains strikingly incurable. </p
Stroke Incidentally Identified Using Improved Positron Emission Tomography for Microglial Activation
FDG-PET patterns associated with underlying pathology in corticobasal syndrome
OBJECTIVE: To evaluate brain 18Fluorodeoxyglucose PET (FDG-PET) differences among patients with a clinical diagnosis of corticobasal syndrome (CBS) and distinct underling primary pathologies. METHODS: We studied 29 patients with a diagnosis of CBS who underwent FDG-PET scan and postmortem neuropathologic examination. Patients were divided into subgroups on the basis of primary pathologic diagnosis: CBS-corticobasal degeneration (CBS-CBD) (14 patients), CBS-Alzheimer disease (CBS-AD) (10 patients), and CBS-progressive supranuclear palsy (CBS-PSP) (5 patients). Thirteen age-matched healthy patients who underwent FDG-PET were the control group (HC). FDG-PET scans were compared between the subgroups and the HC using SPM-12, with a threshold of pFWE < 0.05. RESULTS: There were no differences in Mattis Dementia Rating Scale or finger tapping scores between CBS groups. Compared to HC, the patients with CBS presented significant hypometabolism in frontoparietal regions, including the perirolandic area, basal ganglia, and thalamus of the clinically more affected hemisphere. Patients with CBS-CBD showed a similar pattern with a more marked, bilateral involvement of the basal ganglia. Patients with CBS-AD presented with posterior, asymmetric hypometabolism, including the lateral parietal and temporal lobes and the posterior cingulate. Finally, patients with CBS-PSP disclosed a more anterior hypometabolic pattern, including the medial frontal regions and the anterior cingulate. A conjunction analysis revealed that the primary motor cortex was the only common area of hypometabolism in all groups, irrespective of pathologic diagnosis. DISCUSSION AND CONCLUSIONS: In patients with CBS, different underling pathologies are associated with different patterns of hypometabolism. Our data suggest that FDG-PET scans could help in the etiologic diagnosis of CBS
18F-FCWAY, a serotonin 1A receptor radioligand, is a substrate for efflux transport at the human blood-brain barrier
Distinct patterns of increased translocator protein in posterior cortical atrophy and amnestic Alzheimer's disease
Mixed-affinity binding in humans with 18-kDa translocator protein ligands
(11)C-PBR28 PET can detect the 18-kDa translocator protein (TSPO) expressed within macrophages. However, quantitative evaluation of the signal in brain tissue from donors with multiple sclerosis (MS) shows that PBR28 binds the TSPO with high affinity (binding affinity [K(i)], ~4 nM), low affinity (K(i), ~200 nM), or mixed affinity (2 sites with K(i), ~4 nM and ~300 nM). Our study tested whether similar binding behavior could be detected in brain tissue from donors with no history of neurologic disease, with TSPO-binding PET ligands other than (11)C-PBR28, for TSPO present in peripheral blood, and with human brain PET data acquired in vivo with (11)C-PBR28. METHODS: The affinity of TSPO ligands was measured in the human brain post-mortem from donors with a history of MS (n = 13), donors without any history of neurologic disease (n = 20), and in platelets from healthy volunteers (n = 13). Binding potential estimates from thirty-five (11)C-PBR28 PET scans from an independent sample of healthy volunteers were analyzed using a gaussian mixture model. RESULTS: Three binding affinity patterns were found in brains from subjects without neurologic disease in similar proportions to those reported previously from studies of MS brains. TSPO ligands showed substantial differences in affinity between subjects classified as high-affinity binders (HABs) and low-affinity binders (LABs). Differences in affinity between HABs and LABs are approximately 50-fold with PBR28, approximately 17-fold with PBR06, and approximately 4-fold with DAA1106, DPA713, and PBR111. Where differences in affinity between HABs and LABs were low (~4-fold), distinct affinities were not resolvable in binding curves for mixed-affinity binders (MABs), which appeared to express 1 class of sites with an affinity approximately equal to the mean of those for HABs and LABs. Mixed-affinity binding was detected in platelets from an independent sample (HAB, 69%; MAB, 31%), although LABs were not detected. Analysis of (11)C-PBR28 PET data was not inconsistent with the existence of distinct subpopulations of HABs, MABs, and LABs. CONCLUSION: With the exception of (11)C-PK11195, all TSPO PET ligands in current clinical application recognize HABs, LABs, and MABs in brain tissue in vitro. Knowledge of subjects’ binding patterns will be required to accurately quantify TSPO expression in vivo using PET
11C-PBR28 binding to translocator protein increases with progression of Alzheimer's disease
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Down syndrome: Distribution of brain amyloid in mild cognitive impairment.
IntroductionDown syndrome (DS) is associated with a higher risk of dementia. We hypothesize that amyloid beta (Aβ) in specific brain regions differentiates mild cognitive impairment in DS (MCI-DS) and test these hypotheses using cross-sectional and longitudinal data.Methods18F-AV-45 (florbetapir) positron emission tomography (PET) data were collected to analyze amyloid burden in 58 participants clinically classified as cognitively stable (CS) or MCI-DS and 12 longitudinal CS participants.ResultsThe study confirmed our hypotheses of increased amyloid in inferior parietal, lateral occipital, and superior frontal regions as the main effects differentiating MCI-DS from the CS groups. The largest annualized amyloid increases in longitudinal CS data were in the rostral middle frontal, superior frontal, superior/middle temporal, and posterior cingulate cortices.DiscussionThis study helps us to understand amyloid in the MCI-DS transitional state between cognitively stable aging and frank dementia in DS. The spatial distribution of Aβ may be a reliable indicator of MCI-DS in DS
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Down syndrome: Distribution of brain amyloid in mild cognitive impairment.
IntroductionDown syndrome (DS) is associated with a higher risk of dementia. We hypothesize that amyloid beta (Aβ) in specific brain regions differentiates mild cognitive impairment in DS (MCI-DS) and test these hypotheses using cross-sectional and longitudinal data.Methods18F-AV-45 (florbetapir) positron emission tomography (PET) data were collected to analyze amyloid burden in 58 participants clinically classified as cognitively stable (CS) or MCI-DS and 12 longitudinal CS participants.ResultsThe study confirmed our hypotheses of increased amyloid in inferior parietal, lateral occipital, and superior frontal regions as the main effects differentiating MCI-DS from the CS groups. The largest annualized amyloid increases in longitudinal CS data were in the rostral middle frontal, superior frontal, superior/middle temporal, and posterior cingulate cortices.DiscussionThis study helps us to understand amyloid in the MCI-DS transitional state between cognitively stable aging and frank dementia in DS. The spatial distribution of Aβ may be a reliable indicator of MCI-DS in DS