Gaussian Mixture Models and Model Selection for [18F] Fluorodeoxyglucose Positron Emission Tomography Classification in Alzheimer’s Disease

We present a method to discover discriminative brain metabolism patterns in [18F] fluorodeoxyglucose positron emission tomography (PET) scans, facilitating the clinical diagnosis of Alzheimer’s disease. In the work, the term “pattern” stands for a certain brain region that characterizes a target group of patients and can be used for a classification as well as interpretation purposes. Thus, it can be understood as a so-called “region of interest (ROI)”. In the literature, an ROI is often found by a given brain atlas that defines a number of brain regions, which corresponds to an anatomical approach. The present work introduces a semi-data-driven approach that is based on learning the characteristics of the given data, given some prior anatomical knowledge. A Gaussian Mixture Model (GMM) and model selection are combined to return a clustering of voxels that may serve for the definition of ROIs. Experiments on both an in-house dataset and data of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) suggest that the proposed approach arrives at a better diagnosis than a merely anatomical approach or conventional statistical hypothesis testing

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden

Disruption of functional connectivity between brain regions may represent an early functional consequence of β-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorodeoxyglucose-positron emission tomography. In healthy subjects without cognitive symptoms and patients with mild cognitive impairment, we used positron emission tomography to assess amyloid burden and cerebral glucose metabolism, structural magnetic resonance imaging to quantify atrophy and novel resting state functional magnetic resonance imaging processing methods to calculate whole-brain connectivity. Significant disruptions of whole-brain connectivity were found in amyloid-positive patients with mild cognitive impairment in typical cortical hubs (posterior cingulate cortex/precuneus), strongly overlapping with regional hypometabolism. Subtle connectivity disruptions and hypometabolism were already present in amyloid-positive asymptomatic subjects. Voxel-based morphometry measures indicate that these findings were not solely a consequence of regional atrophy. Whole-brain connectivity values and metabolism showed a positive correlation with each other and a negative correlation with amyloid burden. These results indicate that disruption of functional connectivity and hypometabolism may represent early functional consequences of emerging molecular Alzheimer's disease pathology, evolving prior to clinical onset of dementia. The spatial overlap between hypometabolism and disruption of connectivity in cortical hubs points to a particular susceptibility of these regions to early Alzheimer's-type neurodegeneration and may reflect a link between synaptic dysfunction and functional disconnection

Residual vectors for Alzheimer disease diagnosis and prognostication

Alzheimer disease (AD) is an increasingly prevalent neurodegenerative condition and a looming socioeconomic threat. A biomarker for the disease could make the process of diagnosis easier and more accurate, and accelerate drug discovery. The current work describes a method for scoring brain images that is inspired by fundamental principles from information retrieval (IR), a branch of computer science that includes the development of Internet search engines. For this research, a dataset of 254 baseline 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) scans was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For a given contrast, a subset of scans (nine of every 10) was used to compute a residual vector that typified the difference, at each voxel, between the two groups being contrasted. Scans that were not used for computing the residual vector (the remaining one of 10 scans) were then compared to the residual vector using a cosine similarity metric. This process was repeated sequentially, each time generating cosine similarity scores on 10% of the FDG-PET scans for each contrast. Statistical analysis revealed that the scores were significant predictors of functional decline as measured by the Functional Activities Questionnaire (FAQ). When logistic regression models that incorporated these scores were evaluated with leave-one-out cross-validation, cognitively normal controls were discerned from AD with sensitivity and specificity of 94.4% and 84.8%, respectively. Patients who converted from mild cognitive impairment (MCI) to AD were discerned from MCI nonconverters with sensitivity and specificity of 89.7% and 62.9%, respectively, when FAQ scores were brought into the model. Residual vectors are easy to compute and provide a simple method for scoring the similarity between an FDG-PET scan and sets of examples from a given diagnostic group. The method is readily generalizable to any imaging modality. Further interdisciplinary work between IR and clinical neuroscience is warranted

A New Method for Radiosynthesis of 11C-Labeled Carbamate Groups and its Application for a Highly Efficient Synthesis of the Kappa-Opioid Receptor Tracer [11C]GR103545

11C-labeled carbamates can be obtained in a three-component coupling reaction of primary or secondary amines with CO2 and 11C-methylation reagents. [11C]Methyl-triflate mediated methylation of carbamino adducts provides the corresponding 11C-labeled carbamate groups in excellent yields under mild conditions (temperatures ≤ 40°C, 2 min reaction time). The utility of the method has been demonstrated by a highly efficient radiosynthesis of [11C]GR103545

Impulsivity is Associated with Increased Metabolism in the Fronto-Insular Network in Parkinson’s Disease

Front. Behav. Neurosci. 9:317. doi: 10.3389/fnbeh.2015.00317 Various neuroimaging studies demonstrated that the fronto-insular network is implicated in impulsive behavior. We compared glucose metabolism (as a proxy measure of neural activity) among 24 patients with Parkinson’s disease (PD) who presented with low or high levels of impulsivity based on the Barratt Impulsiveness Scale 11 (BIS) scores. Subjects underwent 18-fluorodeoxyglucose positron emission tomography (FDG-PET) and the voxel-wise group difference of FDG-metabolism was analyzed in Statistical Parametric Mapping (SPM8). Subsequently, we performed a partial correlation analysis between the FDG-metabolism and BIS scores, controlling for covariates (i.e., age, sex, severity of disease and levodopa equivalent daily doses). Voxel-wise group comparison revealed higher FDG-metabolism in the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and right insula in patients with higher impulsivity scores. Moreover, there was a positive correlation between the FDG-metabolism and BIS scores. Our findings provide evidence that high impulsivity is associated with increased FDG-metabolis

Multivariate and Univariate Neuroimaging Biomarkers of Alzheimer's Disease

We performed univariate and multivariate discriminant analysis of FDG-PET scans to evaluate their ability to identify Alzheimer's disease (AD). FDG-PET scans came from two sources: 17 AD patients and 33 healthy elderly controls were scanned at the University of Michigan; 102 early AD patients and 20 healthy elderly controls were scanned at the Technical University of Munich, Germany. We selected a derivation sample of 20 AD patients and 20 healthy controls matched on age with the remainder divided into 5 replication samples. The sensitivity and specificity of diagnostic AD-markers and threshold criteria from the derivation sample were determined in the replication samples. Although both univariate and multivariate analyses produced markers with high classification accuracy in the derivation sample, the multivariate marker's diagnostic performance in the replication samples was superior. Further, supplementary analysis showed its performance to be unaffected by the loss of key regions. Multivariate measures of AD utilize the covariance structure of imaging data and provide complementary, clinically relevant information that may be superior to univariate measures

Association between cognitive performance and cortical glucose metabolism in patients with mild Alzheimer's disease

Background: Neuronal and synaptic function in Alzheimer's disease (AD) is measured in vivo by glucose metabolism using positron emission tomography (PET). Objective: We hypothesized that neuronal activation as measured by PET is a more sensitive index of neuronal dysfunction than activity during rest. We investigated if the correlations between dementia severity as measured with the Mini Mental State Examination (MMSE) and glucose metabolism are an artifact of brain atrophy. Method: Glucose metabolism was measured using {[}F-18]fluorodeoxyglucose PET during rest and activation due to audiovisual stimulation in 13 mild to moderate AD patients (MMSE score >= 17). PET data were corrected for brain atrophy. Results: In the rest condition, glucose metabolism was correlated with the MMSE score primarily within the posterior cingulate and parietal lobes. For the activation condition, additional correlations were within the primary and association audiovisual areas. Most local maxima remained significant after correcting for brain atrophy. Conclusion: PET activity measured during audiovisual stimulation was more sensitive to functional alterations in glucose metabolism in AD patients compared to the resting PET. The association between glucose metabolism and MMSE score was not dependent on brain atrophy. Copyright (C) 2005 S. Karger AG, Basel

Neural origins of human sickness in interoceptive responses to inflammation

BACKGROUND: Inflammation is associated with psychological, emotional, and behavioral disturbance, known as sickness behavior. Inflammatory cytokines are implicated in coordinating this central motivational reorientation accompanying peripheral immunologic responses to pathogens. Studies in rodents suggest an afferent interoceptive neural mechanism, although comparable data in humans are lacking. METHODS: In a double-blind, randomized crossover study, 16 healthy male volunteers received typhoid vaccination or saline (placebo) injection in two experimental sessions. Profile of Mood State questionnaires were completed at baseline and at 2 and 3 hours. Two hours after injection, participants performed a high-demand color word Stroop task during functional magnetic resonance imaging. Blood samples were performed at baseline and immediately after scanning. RESULTS: Typhoid but not placebo injection produced a robust inflammatory response indexed by increased circulating interleukin-6 accompanied by a significant increase in fatigue, confusion, and impaired concentration at 3 hours. Performance of the Stroop task under inflammation activated brain regions encoding representations of internal bodily state. Spatial and temporal characteristics of this response are consistent with interoceptive information flow via afferent autonomic fibers. During performance of this task, activity within interoceptive brain regions also predicted individual differences in inflammation-associated but not placebo-associated fatigue and confusion. Maintenance of cognitive performance, despite inflammation-associated fatigue, led to recruitment of additional prefrontal cortical regions. CONCLUSIONS: These findings suggest that peripheral infection selectively influences central nervous system function to generate core symptoms of sickness and reorient basic motivational states. PMID:19409533[PubMed - indexed for MEDLINE] PMCID: PMC2885492Free PMC Articl

EANM-EAN recommendations for the use of brain 18 F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) in neurodegenerative cognitive impairment and dementia: Delphi consensus

BACKGROUND: Recommendations for using FDG-PET to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. METHODS: We defined 21 questions on diagnostic issues and on semi-automated analysis to assist visual reading. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiving operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion. RESULTS: Of the 1435 papers, 58 provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudodementia; differentiating between AD and DLB, FTLD, or vascular dementia, between DLB and FTLD, and between Parkinson's disease (PD) and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in PD; using semi-automated assessment to assist visual reading. Panelists did not support FDG-PET use for preclinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis (ALS) and Huntington disease (HD) diagnoses, and ALS or HD-related cognitive decline. CONCLUSIONS: Despite limited formal evidence, panelists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semiautomated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations. This article is protected by copyright. All rights reserved

Monolithic crystals for PET devices: optical coupling optimization

NOTICE: this is the author’s version of a work that was accepted for publication in Nuclear Instruments and Methods in Physics Research Section A. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Nuclear Instruments and Methods in Physics Research Section A [Volume 731, 11 December 2013, Pages 288–294] DOI 10.1016/j.nima.2013.05.049[EN] In this work we present a method to efficiently collect scintillation light when using monolithic scintillator crystals. The acceptance angle of the scintillation light has been reduced by means of optical devices reducing the border effect which typically affects continuous crystals. We have applied this procedure on gamma detectors for PET systems using both position sensitive PMTs and arrays of SiPMs. In the case of using SiPMs, this approach also helps to reduce the photosensor active area. We evaluated the method using PMTs with a variety of different crystals with thicknesses ranging from 10 to 24 mm. We found that our design allows the use of crystal blocks with a thickness of up to 18 mm without degrading the spatial resolution caused by edge effects and without a significant detriment to the energy resolution. These results were compared with simulated data. The first results of monolithic LYSO crystals coupled to an array of 256 SiPMs by means of individual optical light guides are also presented.This work was supported by the Centre for Industrial Technological Development co-funded by FEDER through the Technology Fund (DREAM Project, IDI-20110718), the Spanish Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica (I+D +I) under Grant no. FIS2010-21216-CO2-01 and the Valencian Local Government under Grant PROMETEO 2008/114.González Martínez, AJ.; Peiró, A.; Conde, P.; Hernández Hernández, L.; Moliner Martínez, L.; Orero Palomares, A.; Rodríguez-Álvarez, M.... (2013). Monolithic crystals for PET devices: optical coupling optimization. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 731:288-294. https://doi.org/10.1016/j.nima.2013.05.049S28829473