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Perinatally acquired HIV (PHIV) has been associated with brain structural and functional deficiencies, and with poorer cognitive performance despite the advent of antiretroviral therapy (ART). However, investigation of brain metabolite levels in PHIV measured by proton magnetic resonance spectroscopy (MRS) methods, is still limited with often inconclusive or contradictory findings. In general, these MRS-based methods have used a single voxel approach that can only evaluate metabolite concentrations in a few select brain anatomical regions. Additionally, most of the published data have been on children perinatally infected with HIV with only a few studies examining adult populations, though not exclusively. Therefore, this prospective and cross-sectional study aims to evaluate metabolite differences at the whole-brain level, using a unique whole-brain proton magnetic resonance spectroscopy imaging (MRSI) method, in a group of PHIV infected young adults (N = 28) compared to age and gender matched control sample (N = 28), and to find associations with HIV clinical factors and neurocognitive scores. MRSI data were acquired on a 3T scanner with a TE of 70 ms. Brain metabolites levels of total N-acetylaspartate (tNAA), total choline (tCho) and total creatine (tCre), as well as ratios of tNAA/tCre, tCho/tCre, and tNAA/tCho, were obtained from the whole brain level and evaluated at the level of gray matter (GM) and white matter (WM) tissue types and anatomical regions of interest (ROI). Our results indicate extensive metabolic abnormalities throughout the brains of PHIV infected subjects with significantly elevated levels of tCre and tCho, notably in GM regions. Decreases in tNAA and ratios of tNAA/tCre and tNAA/tCho were also found mostly in WM regions. These metabolic alterations indicate increased glial activation, inflammation, neuronal dysfunction, and energy metabolism in PHIV infected individuals, which correlated with a reduction in CD4 cell count, and lower cognitive scores. Our findings suggest that significant brain metabolite alterations and associated neurological complications persist in the brains of those with PHIV on long-term ART, and advocates the need for continued monitoring of their brain health.

Traumatic brain injury (TBI) can lead to a variety of comorbidities, including chronic pain. Although brain tissue metabolite alterations have been extensively examined in several chronic pain populations, it has received less attention in people with TBI. Thus, the primary aim of this study was to compare brain tissue metabolite levels in people with TBI and chronic pain (n = 16), TBI without chronic pain (n = 17), and pain-free healthy controls (n = 31). The metabolite data were obtained from participants using whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) at 3 Tesla. The metabolite data included N-acetylaspartate, myo-inositol, total choline, glutamate plus glutamine, and total creatine. Associations between N-acetylaspartate levels and pain severity, neuropathic pain symptom severity, and psychological variables, including anxiety, depression, post-traumatic stress disorder (PTSD), and post-concussive symptoms, were also explored. Our results demonstrate N-acetylaspartate, myo-inositol, total choline, and total creatine alterations in pain-related brain regions such as the frontal region, cingulum, postcentral gyrus, and thalamus in individuals with TBI with and without chronic pain. Additionally, NAA levels in the left and right frontal lobe regions were positively correlated with post-concussive symptoms; and NAA levels within the left frontal region were also positively correlated with neuropathic pain symptom severity, depression, and PTSD symptoms in the TBI with chronic pain group. These results suggest that neuronal integrity or density in the prefrontal cortex, a critical region for nociception and pain modulation, is associated with the severity of neuropathic pain symptoms and psychological comorbidities following TBI. Our data suggest that a combination of neuronal loss or dysfunction and maladaptive neuroplasticity may contribute to the development of persistent pain following TBI, although no causal relationship can be determined based on these data.

Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three‐dimensional echo planar spectroscopic imaging (3D‐EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo‐radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow‐up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N‐acetylaspartate (Cho/NAA) were computed and co‐registered with post‐contrast T 1‐weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D‐EPSI in differentiating TP from PsP with high sensitivity and specificity.

BACKGROUND: Diffusion kurtosis imaging (DKI) measures have been shown to provide increased sensitivity relative to diffusion tensor imaging (DTI) in detecting pathologies. PURPOSE: To compare the sensitivity of DKI derived kurtosis and diffusion maps for assessment of low-grade gliomas (LGG). STUDY TYPE: Prospective study. POPULATION: 19 LGG patients and 26 healthy control subjects were recruited. FIELD STRENGTH/SEQUENCE: EPI diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner. ASSESSMENT: Maps for mean, axial and radial diffusivity (MD, AD, and RD) and kurtosis (MK, AK, and RK), and fractional anisotropy (FA) were evaluated in the tumor, perilesional white matter, and contralateral normal appearing white matter regions. STATISTICAL TESTING: General linear models (GLM), Cohen’s d for effect size estimates, false discovery rate (FDR) for multiple corrections, Cochran Q-test. RESULTS: Pairwise differences were observed for all diffusion and kurtosis measures between the studied regions (FDR p

Estimation of brain metabolite concentrations by MR spectroscopic imaging (MRSI) is complicated by partial volume contributions from different tissues. This study evaluates a method for increasing tissue specificity that incorporates prior knowledge of tissue distributions.A spectral decomposition (sDec) technique was evaluated for separation of spectra from white matter (WM) and gray matter (GM), and for measurements in small brain regions using whole-brain MRSI. Simulation and in vivo studies compare results of metabolite quantifications obtained with the sDec technique to those obtained by spectral fitting of individual voxels using mean values and linear regression against tissue fractions and spectral fitting of regionally integrated spectra.Simulation studies showed that, for GM and the putamen, the sDec method offers 2% and 3.5% error, respectively, in metabolite estimates. These errors are considerably reduced in comparison to methods that do not account for partial volume effects or use regressions against tissue fractions. In an analysis of data from 197 studies, significant differences in mean metabolite values and changes with age were found. Spectral decomposition resulted in significantly better linewidth, signal-to-noise ratio, and spectral fitting quality as compared to individual spectral analysis. Moreover, significant partial volume effects were seen on correlations of neurometabolite estimates with age.The sDec analysis approach is of considerable value in studies of pathologies that may preferentially affect WM or GM, as well as smaller brain regions significantly affected by partial volume effects. Magn Reson Med 79:2886-2895, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Item does not contain fulltext A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units. © RSNA, 2014 Online supplemental material is available for this article.

International audience; PURPOSE: To detect local metabolic abnormalities over the complete human brain in multiple sclerosis (MS) patients, we used optimized fast volumic echo planar spectroscopic imaging (3D-EPSI). MATERIALS AND METHODS: Weighted mean combination of two 3D-EPSI covering the whole brain acquired at 3T in AC-PC and AC-PC+15° axial planes was performed to obtain high-quality metabolite maps for five metabolites: N-acetyl aspartate (NAA), glutamate+glutamine (Glx), choline (Cho), myo-inositol (m-Ins), and creatine+phosphocreatine (tCr). After spatial normalization, maps from 19 patients suffering from relapsing-remitting MS were compared to 19 matched controls using statistical mapping analyses to determine the topography of metabolic abnormalities. Probabilistic white matter (WM) T2 lesion maps and gray matter (GM) atrophy maps were also generated. RESULTS: Two-group analysis of variance (ANOVA) (SPM8, P \textless 0.005, false discovery rate [FDR]-corrected P \textless 0.05 at the cluster level with age and sex as confounding covariates) comparing patients and controls matched for age and sex showed clusters of abnormal metabolite levels with 1) decreased NAA (around -15%) and Glx (around 20%) predominantly in GM within prefrontal cortices, motor cortices, bilateral thalami, and mesial temporal cortices in line with neuronal/neuro-astrocytic dysfunction; 2) increased m-Ins (around + 20%) inside WM T2 lesions and in the normal-appearing WM of temporal-occipital lobes, suggesting glial activation. CONCLUSION: We demonstrate the ability to noninvasively map over the complete brain-from vertex to cerebellum-with a validated sequence, the metabolic abnormalities associated with MS, for characterizing the topography of pathological processes affecting widespread areas of WM and GM and its functional impact. J. Magn. Reson. Imaging 2016;44:411-419.

To evaluate methods for multichannel combination of three-dimensional MR spectroscopic imaging (MRSI) data with a focus on using information from a water-reference spectroscopic image.Volumetric MRSI data were acquired for a phantom and for human brain using 8- and 32-channel detection. Acquisition included a water-reference dataset that was used to determine the weights for several multichannel combination methods. Results were compared using the signal-to-noise ratio (SNR) of the N-acetylaspartate resonance.Performance of all methods was very similar for the phantom study, with the whitened singular value decomposition (WSVD) and signal magnitude (S) weighting combination having a small advantage. For in vivo studies, the S weighting, SNR weighting and signal to noise squared (S/N(2) ) weighting were the three best methods and performed similarly. Example spectra and SNR maps indicated that the SVD and WSVD methods tend to fail for voxels at the outer edges of the brain that include strong lipid signal contributions.For data combination of MRSI data using water-reference information, the S/N(2) weighting, SNR and S weighting were the best methods in terms of spectral quality SNR. These methods are also computationally efficient and easy to implement. Magn Reson Med 76:733-741, 2016. © 2015 Wiley Periodicals, Inc.

International audience; BACKGROUND: To improve the extent over which whole brain quantitative three-dimensional (3D) magnetic resonance spectroscopic imaging (MRSI) maps can be obtained and be used to explore brain metabolism in a population of healthy volunteers. METHODS: Two short echo time (20 ms) acquisitions of 3D echo planar spectroscopic imaging at two orientations, one in the anterior commissure-posterior commissure (AC-PC) plane and the second tilted in the AC-PC +15° plane were obtained at 3 Tesla in a group of 10 healthy volunteers. B1 (+) , B1 (-) , and B0 correction procedures and normalization of metabolite signals with quantitative water proton density measurements were performed. A combination of the two spatially normalized 3D-MRSI, using a weighted mean based on the pixel wise standard deviation metabolic maps of each orientation obtained from the whole group, provided metabolite maps for each subject allowing regional metabolic profiles of all parcels of the automated anatomical labeling (AAL) atlas to be obtained. RESULTS: The combined metabolite maps derived from the two acquisitions reduced the regional intersubject variance. The numbers of AAL regions showing N-acetyl aspartate (NAA) SD/Mean ratios lower than 30% increased from 17 in the AC-PC orientation and 41 in the AC-PC+15° orientation, to a value of 76 regions of 116 for the combined NAA maps. Quantitatively, regional differences in absolute metabolite concentrations (mM) over the whole brain were depicted such as in the GM of frontal lobes (cNAA = 10.03 + 1.71; cCho = 1.78 ± 0.55; cCr = 7.29 ± 1.69; cmIns = 5.30 ± 2.67) and in cerebellum (cNAA = 5.28 ± 1.77; cCho = 1.60 ± 0.41; cCr = 6.95 ± 2.15; cmIns = 3.60 ± 0.74). CONCLUSION: A double-angulation acquisition enables improved metabolic characterization over a wide volume of the brain. J. Magn. Reson. Imaging 2015;42:280-289.

The aim of these studies was to provide reference data on intersubject variability and reproducibility of metabolite ratios for Choline/Creatine (Cho/Cr), N-acetyl aspartate/Choline (NAA/Cho) and N-acetyl aspartate/Creatine (NAA/Cr), and individual signal-intensity normalised metabolite concentrations of NAA, Cho and Cr. Healthy volunteers underwent imaging on two occasions using the same 3T Siemens Verio magnetic resonance scanner. At each session two identical Metabolic Imaging and Data Acquisition Software (MIDAS) sequences were obtained along with standard structural imaging. Metabolite maps were created and regions of interest applied in normalised space. The baseline data from all 32 volunteers were used to calculate the intersubject variability, while within session and between session reproducibility were calculated from all the available data. The reproducibility of measurements were used to calculate the overall and within session 95% prediction interval for zero change. The within and between session reproducibility data were lower than the values for intersubject variability, and were variable across the different brain regions. The within and between session reproducibility measurements were similar for Cho/Cr, NAA/Choline, Cho and Cr (11.8%, 11.4%, 14.3 and 10.6% vs. 11.9%, 11.4%, 13.5% and 10.5% respectively), but for NAA/Creatine and NAA between session reproducibility was lower (9.3% and 9.1% vs. 10.1% and 9.9%; p

The translation of MRS to clinical practice has been impeded by the lack of technical standardization. There are multiple methods of acquisition, post-processing, and analysis whose details greatly impact the interpretation of the results. These details are often not fully reported, making it difficult to assess MRS studies on a standardized basis. This hampers the reviewing of manuscripts, limits the reproducibility of study results, and complicates meta-analysis of the literature. In this paper a consensus group of MRS experts provides minimum guidelines for the reporting of MRS methods and results, including the standardized description of MRS hardware, data acquisition, analysis, and quality assessment. This consensus statement describes each of these requirements in detail and includes a checklist to assist authors and journal reviewers and to provide a practical way for journal editors to ensure that MRS studies are reported in full.