Voxel Placement Precision for GABA-Edited Magnetic Resonance Spectroscopy.
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ABSTRACT:
SUBMITTER: Bai X
PROVIDER: S-EPMC5497851 | biostudies-other | 2017 Mar
REPOSITORIES: biostudies-other
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Project description:Background:Mutations in the isocitrate dehydrogenase (IDH) enzyme affect 40% of gliomas and represent a major diagnostic and prognostic marker. The goals of this study were to evaluate the performance of noninvasive magnetic resonance spectroscopy (MRS) methods to determine the IDH status of patients with brain gliomas through detection of the oncometabolite 2-hydroxyglutarate (2HG) and to compare performance of these methods with DNA sequencing and tissue 2HG analysis. Methods:Twenty-four subjects with suspected diagnosis of low-grade glioma were included prospectively in the study. For all subjects, MRS data were acquired at 3T using 2 MRS methods, edited MRS using Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence and a PRESS sequence optimized for 2HG detection, using a volume of interest larger than 6 mL. IDH mutational status was determined by a combination of automated immunohistochemical analysis and Sanger sequencing. Levels of 2HG in tissue samples measured by gas chromatography-mass spectrometry were compared with those estimated by MRS. Results:Edited MRS provided 100% specificity and 100% sensitivity in the detection of 2HG. The 2HG levels estimated by this technique were in line with those derived from tissue samples. Optimized PRESS provided lower performance, in agreement with previous findings. Conclusions:Our results suggest that edited MRS is one of the most reliable tools to predict IDH mutation noninvasively, showing high sensitivity and specificity for 2HG detection. Integrating edited MRS in clinical practice may be highly beneficial for noninvasive diagnosis of glioma, prognostic assessment, and treatment planning.
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Project description:To date, single voxel spectroscopy (SVS) is the most commonly used MRS technique. SVS is relatively easy to use and provides automated and immediate access to the resulting spectra. However, it is also limited in spatial coverage. A new and very promising MRS technique allows for whole-brain MR spectroscopic imaging (WB-MRSI) with much improved spatial resolution. Establishing the reproducibility of data obtained using SVS and WB-MRSI is an important first step for using these techniques to evaluate longitudinal changes in metabolite concentration. The purpose of this study was to assess and directly compare the reproducibility of metabolite quantification at 3T using SVS and WB-MRSI in 'hand-knob' areas of motor cortices and hippocampi in healthy volunteers. Ten healthy adults were scanned using both SVS and WB-MRSI on three occasions one week apart. N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) were quantified using SVS and WB-MRSI with reference to both Cr and H2 O. The reproducibility of each technique was evaluated using the coefficient of variation (CV), and the correspondence between the two techniques was assessed using Pearson correlation analysis. The measured mean (range) intra-subject CVs for SVS were 5.90 (2.65-10.66)% for metabolites (i.e. NAA, Cho, mI) relative to Cr, and 8.46 (4.21-21.07)% for metabolites (NAA, Cr, Cho, mI) relative to H2 O. The mean (range) CVs for WB-MRSI were 7.56 (2.78-11.41)% for metabolites relative to Cr, and 7.79 (4.57-14.11)% for metabolites relative to H2 O. Significant positive correlations were observed between metabolites quantified using SVS and WB-MRSI techniques when the Cr but not H2 O reference was used. The results demonstrate that reproducibilities of SVS and WB-MRSI are similar for quantifying the four major metabolites (NAA, Cr, Cho, mI); both SVS and WB-MRSI exhibited good reproducibility. Our findings add reference information for choosing the appropriate 1 H-MRS technique in future studies.
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Project description:Once an MRS dataset has been acquired, several important steps must be taken to obtain the desired metabolite concentration measures. First, the data must be preprocessed to prepare them for analysis. Next, the intensity of the metabolite signal(s) of interest must be estimated. Finally, the measured metabolite signal intensities must be converted into scaled concentration units employing a quantitative reference signal to allow meaningful interpretation. In this paper, we review these three main steps in the post-acquisition workflow of a single-voxel MRS experiment (preprocessing, analysis and quantification) and provide recommendations for best practices at each step.
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Project description:Background and purposeDerangements in brain glutamate, glutathione, and γ-amino butyric acid (GABA) are implicated in a range of neurological disorders. Reliable methods to measure these compounds non-invasively in vivo are needed. We evaluated the reproducibility of their measurements in brain regions involved in the default mode network using quantitative MRS at 7-Tesla in healthy individuals.MethodsTen right-handed healthy volunteers underwent 7-Tesla MRI scans on 2 separate days, not more than 2 weeks apart. On each day two scanning sessions took place, with a re-positioning break in between. High-resolution isotropic anatomical scans were acquired prior to each scan, followed by single-voxel 1H-MRS using the STEAM pulse sequence on an 8 mL midline cubic voxel, positioned over the posterior cingulate and precuneus regions. Concentrations were corrected for partial-volume effects.ResultsMaximal Cramér-Rao lower bounds for glutamate, glutathione, and GABA were 2.0, 8.0, and 14.0%, respectively. Mean coefficients of variation within sessions were 5.9 ± 4.8%, 9.3 ± 7.6%, and 11.5 ± 8.8%, and between sessions were 4.6 ± 4.5%, 8.3 ± 5.7%, and 9.2 ± 8.7%, respectively. The mean (±SD) Dice's coefficient for voxel overlap was 90 ± 4% within sessions and 86 ± 7% between sessions.ConclusionGlutamate, glutathione, and GABA can be reliably quantified using STEAM MRS at 7-Tesla from the posterior cingulate and precuneus cortices of healthy human subjects. STEAM MRS at 7-Tesla may be used to study the metabolic behavior of this important resting-state hub in various disease states.
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Project description:Despite maximally-safe resection of the MRI-defined contrast-enhanced (CE) central tumor area and chemo-radiotherapy, most glioblastoma patients relapse within one year in peritumor FLAIR regions. Spectroscopic MRI (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (Choline/N-acetyl-aspartate Index>2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSC), CNI+ areas might be GSC-enriched. We conducted a prospective trial in 16 GBM patients subjected to preoperative MRSI/MRI and surgery/chemo-radiotherapy to investigate GSC content in CNI+ versus CNI- biopsies from CE/FLAIR. Biopsy characterization by RNAseq revealed that FLAIR/CNI+ areas were enriched in stem-related gene signature, but also in pathways related to DNA repair, adhesion/migration and mitochondrial bioenergetics.
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Project description:Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.
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Project description:Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.
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2023-04-25 | GSE225302 | GEO
Project description:Cognitive and behavioral disabilities in preterm infants, even without obvious brain injury on conventional neuroimaging, underscores a critical need to identify the subtle underlying microstructural and biochemical derangements. The gamma-aminobutyric acid (GABA) and glutamatergic neurotransmitter systems undergo rapid maturation during the crucial late gestation and early postnatal life, and are at-risk of disruption after preterm birth. Animal and human autopsy studies provide the bulk of current understanding since non-invasive specialized proton magnetic resonance spectroscopy (1H-MRS) to measure GABA and glutamate are not routinely available for this vulnerable population due to logistical and technical challenges. We review the specialized 1H-MRS techniques including MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS), special challenges and considerations needed for interpretation of acquired data from the developing brain of preterm infants. We summarize the limited in-vivo preterm data, highlight the gaps in knowledge, and discuss future directions for optimal integration of available in-vivo approaches to understand the influence of GABA and glutamate on neurodevelopmental outcomes after preterm birth.
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