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The Effects of Physiological and Methodological Determinants on 18F-FDG Mouse Brain Imaging Exemplified in a Double Transgenic Alzheimer Model.

ABSTRACT: In this study, the influence of physiological determinants on 18F-fluoro-d-glucose ((18)F-FDG) brain uptake was evaluated in a mouse model of Alzheimer disease.TASTPM (Tg) and age-matched C57BL/6 J (WT) mice were fasted for 10 hours, while another group was fasted for 20 hours to evaluate the effect of fasting duration. The effect of repeatedly scanning was evaluated by scanning Tg and WT mice at days 1, 4, and 7. Brain (18)F-FDG uptake was evaluated in the thalamus being the most indicative region. Finally, the cerebellum was tested as a reference region for the relative standard uptake value (rSUV).When correcting the brain uptake for glucose, the effect of different fasting durations was attenuated and the anticipated hypometabolism in Tg mice was demonstrated. Also, with repeated scanning, the brain uptake values within a group and the hypometabolism of the Tg mice only remained stable over time when glucose correction was applied. Finally, hypometabolism was also observed in the cerebellum, yielding artificially higher rSUV values for Tg mice.Corrections for blood glucose levels have to be applied when semiquantifying (18)F-FDG brain uptake in mouse models for AD. Potential reference regions for normalization should be thoroughly investigated to ensure that they are not pathologically affected also by afferent connections.

SUBMITTER: Deleye S

PROVIDER: S-EPMC5470082 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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The Effects of Physiological and Methodological Determinants on 18F-FDG Mouse Brain Imaging Exemplified in a Double Transgenic Alzheimer Model.

Deleye Steven S Waldron Ann-Marie AM Richardson Jill C JC Schmidt Mark M Langlois Xavier X Stroobants Sigrid S Staelens Steven S

Molecular imaging 20160211

<h4>Introduction</h4>In this study, the influence of physiological determinants on 18F-fluoro-d-glucose ((18)F-FDG) brain uptake was evaluated in a mouse model of Alzheimer disease.<h4>Materials and methods</h4>TASTPM (Tg) and age-matched C57BL/6 J (WT) mice were fasted for 10 hours, while another group was fasted for 20 hours to evaluate the effect of fasting duration. The effect of repeatedly scanning was evaluated by scanning Tg and WT mice at days 1, 4, and 7. Brain (18)F-FDG uptake was eval ...[more]

PMID: 27030402

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Project description:IntroductionMetabolic brain network analysis based on graph theory using FDG PET imaging is potentially useful for investigating brain activity alternation due to metabolism changes in different stages of Alzheimer's disease (AD). Most studies on metabolic network construction have been based on group data. Here a novel approach in building an individual metabolic network was proposed to investigate individual metabolic network abnormalities.MethodFirst, a weighting matrix was calculated based on the interregional effect size difference of mean uptake between a single subject and average normal controls (NCs). Then the weighting matrix for a single subject was multiplied by a group-based connectivity matrix from an NC cohort. To study the performance of the proposed individual metabolic network, inter- and intra-hemispheric connectivity patterns in the groups of NC, sMCI (stable mild cognitive impairment), pMCI (progressive mild cognitive impairment), and AD using the proposed individual metabolic network were constructed and compared with those from the group-based results. The network parameters of global efficiency and clustering coefficient and the network density score (NDS) in the default-mode network (DMN) of generated individual metabolic networks were estimated and compared among the disease groups in AD.ResultsOur results show that the intra- and inter-hemispheric connectivity patterns estimated from our individual metabolic network are similar to those from the group-based method. In particular, the key patterns of occipital-parietal and occipital-temporal inter-regional connectivity deficits detected in the groupwise network study for differentiating different disease groups in AD were also found in the individual network. A reduction trend was observed for network parameters of global efficiency and clustering coefficient, and also for the NDS from NC, sMCI, pMCI, and AD. There was no significant difference between NC and sMCI for all network parameters.ConclusionWe proposed a novel method in constructing the individual metabolic network using a single-subject FDG PET image and a group-based NC connectivity matrix. The result has shown the effectiveness and feasibility of the proposed individual metabolic network in differentiating disease groups in AD. Future studies should include investigation of inter-individual variability and the correlation of individual network features to disease severities and clinical performance.

Project description:PurposeTo investigate the possibility of reducing the injected activity for whole-body [18F]FDG-PET/CT studies of paediatric oncology patients and to assess the usefulness of time-of-flight (TOF) acquisition on PET image quality at reduced count levels.ProceduresTwenty-nine paediatric oncology patients (12F/17M, 3-18 years old (median age 13y), weight 45±20 kg, BMI 19±4 kg/m2), who underwent routine whole-body PET/CT examinations on a Siemens Biograph mCT TrueV system with TOF capability (555ps) were included in this study. The mean injected activity was 156 ± 45 MBq (3.8 ± 0.8 kg/MBq) and scaled to patient weight. The raw data was collected in listmode (LM) format and pre-processed to simulate reduced levels of [18F]FDG activity (75, 50, 35, 20 and 10% of the original counts) by randomly removing events from the original LM data. All data were reconstructed using the vendor-specific e7-tools with standard OSEM only, with OSEM plus resolution recovery (PSF). The reconstructions were repeated with added TOF (TOF) and PSF+TOF. The benefit of TOF together with the reduced count levels was evaluated by calculating the gains in signal-to-noise ratio (SNR) in the liver and contrast-to-noise ratio (CNR) in all PET-positive lesions before and after TOF employed at every simulated reduced count level. Finally, the PSF+TOF images at 50, 75 and 100% of counts were evaluated clinically on a 5-point scale by three nuclear medicine physicians.ResultsThe visual inspection of the reconstructed images did not reveal significant differences in image quality between 75 and 100% count levels for PSF+TOF. The improvements in SNR and CNR were the greatest for TOF reconstruction and PSF combined. Both SNR and CNR gains did increase linearly with the patients BMI for both OSEM only and PSF reconstruction. These benefits were observed until reducing the counts to 50 and 35% for SNR and CNR, respectively.ConclusionsThe benefit of using TOF was noticeable when using 50% or greater of the counts when evaluating the CNR and SNR. For [18F]FDG-PET/CT, whole-body paediatric imaging the injected activity can be reduced to 75% of the original dose without compromising PET image quality.

Project description:UnlabelledIn the recently revised diagnostic criteria for Alzheimer disease (AD), the National Institute on Aging and Alzheimer Association suggested that confidence in diagnosing dementia due to AD and mild cognitive impairment (MCI) due to AD could be improved by the use of certain biomarkers, such as (18)F-FDG PET evidence of hypometabolism in AD-affected brain regions. Three groups have developed automated data analysis techniques to characterize the AD-related pattern of hypometabolism in a single measurement. In this study, we sought to directly compare the ability of these three (18)F-FDG PET data analysis techniques--the PMOD Alzheimer discrimination analysis tool, the hypometabolic convergence index, and a set of meta-analytically derived regions of interest reflecting AD hypometabolism pattern (metaROI)--to distinguish moderate or mild AD dementia patients and MCI patients who subsequently converted to AD dementia from cognitively normal older adults.MethodsOne hundred sixty-six (18)F-FDG PET patients from the AD Neuroimaging Initiative, 308 from the Network for Efficiency and Standardization of Dementia Diagnosis, and 176 from the European Alzheimer Disease Consortium PET study were categorized, with masking of group classification, as AD, MCI, or healthy control. For each AD-related (18)F-FDG PET index, receiver-operating-characteristic curves were used to characterize and compare subject group classifications.ResultsThe 3 techniques were roughly comparable in their ability to distinguish each of the clinical groups from cognitively normal older adults with high sensitivity and specificity. Accuracy of classification (in terms of area under the curve) in each clinical group varied more as a function of dataset than by technique. All techniques were differentially sensitive to disease severity, with the classification accuracy for MCI due to AD to moderate AD varying from 0.800 to 0.949 (PMOD Alzheimer tool), from 0.774 to 0.967 (metaROI), and from 0.801 to 0.983 (hypometabolic convergence index).ConclusionThe 3 tested techniques have the potential to help detect AD in research and clinical settings. Additional efforts are needed to clarify their ability to address particular scientific and clinical questions. Their incremental diagnostic value over other imaging and biologic markers makes them easier to implement by other groups for these purposes.

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The Effects of Physiological and Methodological Determinants on 18F-FDG Mouse Brain Imaging Exemplified in a Double Transgenic Alzheimer Model.

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The Effects of Physiological and Methodological Determinants on 18F-FDG Mouse Brain Imaging Exemplified in a Double Transgenic Alzheimer Model.

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