Increased Glutamate Plus Glutamine in the Right Middle Cingulate in Early Schizophrenia but Not in Bipolar Psychosis: A Whole Brain 1H-MRS Study

Proton magnetic resonance spectroscopy (1H-MRS) studies have examined glutamatergic abnormalities in schizophrenia and bipolar-I disorders, mostly in single voxels. Though the critical nodes remain unknown, schizophrenia and bipolar-I involve brain networks with broad abnormalities. To provide insight on the biochemical differences that may underlie these networks, the combined glutamine and glutamate signal (Glx) and other metabolites were examined in patients in early psychosis with whole brain 1H-MRS imaging (1H-MRSI). Data were acquired in young schizophrenia subjects (N = 48), bipolar-I subjects (N = 21) and healthy controls (N = 51). Group contrasts for Glx, as well as for N-acetyl aspartate, choline, myo-inositol and creatine, from all voxels that met spectral quality criteria were analyzed in standardized brain space, followed by cluster-corrected level alpha-value (CCLAV ≤ 0.05) analysis. Schizophrenia subjects had higher Glx in the right middle cingulate gyrus (19 voxels, CCLAV = 0.05) than bipolar-I subjects. Healthy controls had intermediate Glx values, though not significant. Schizophrenia subjects also had higher N-acetyl aspartate (three clusters, left occipital, left frontal, right frontal), choline (two clusters, left and right frontal) and myo-inositol (one cluster, left frontal) than bipolar-I, with healthy controls having intermediate values. These increases were likely accounted for by antipsychotic medication effects in the schizophrenia subgroup for N-acetyl aspartate and choline. Likewise, creatine was increased in two clusters in treated vs. antipsychotic-naïve schizophrenia, supporting a medication effect. Conversely, the increments in Glx in right cingulate were not driven by antipsychotic medication exposure. We conclude that increments in Glx in the cingulate may be critical to the pathophysiology of schizophrenia and are consistent with the NMDA hypo-function model. This model however may be more specific to schizophrenia than to psychosis in general. Postmortem and neuromodulation schizophrenia studies focusing on right cingulate, may provide critical mechanistic and therapeutic advancements, respectively.

Uncertainty in denoising of MRSI using low-rank methods

Purpose: Low-rank denoising of MRSI data results in an apparent increase in spectral SNR. However, it is not clear if this translates to a lower uncertainty in metabolite concentrations after spectroscopic fitting. Estimation of the true uncertainty after denoising is desirable for downstream analysis in spectroscopy. In this work the uncertainty reduction from low-rank denoising methods based on spatio-temporal separability and linear predictability in MRSI are assessed. A new method for estimating metabolite concentration uncertainty after denoising is proposed. Finally, automatic rank threshold selection methods are assessed in simulated low SNR regimes. Methods: Assessment of denoising methods is conducted using Monte Carlo simulation of proton MRSI data, and by reproducibility of repeated in vivo acquisitions in five subjects. Results: In simulated and in vivo data, spatio-temporal based denoising is shown to reduce the concentration uncertainty, but linear prediction denoising increases uncertainty. Uncertainty estimates provided by fitting algorithms after denoising consistently under-estimate actual metabolite uncertainty. However, the proposed uncertainty estimation, based on an analytical expression for entry-wise variance after denoising, is more accurate. Finally, it is shown automated rank threshold selection using Marchenko-Pastur distribution can bias the data in low SNR conditions. An alternative soft-thresholding function is proposed. Conclusion: Low-rank denoising methods based on spatio-temporal separability do reduce uncertainty in MRS(I) data. However, thorough assessment is needed as assessment by SNR measured from residual baseline noise is insufficient given the presence of non-uniform variance. It is also important to select the right rank thresholding method in low SNR cases.

Repeatability and reproducibility of in-vivo brain temperature measurements

ABSTRACTBackgroundMagnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that can be used to noninvasively map brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range.MethodsHealthy participants aged 23-46 years (N=18; 7 females) were scanned at two time points, ∼12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values.ResultsThe mean global brain temperature over all subjects was 37.2°C, with spatial variations across ROIs. There was a significant main effect for time (F(1, 1591)=37.0, p < 0.0001) and for brain region (F(46, 1591)=2.66, p<0.0001). The time*brain region interaction was not significant (F(46, 1591)=0.80, p=0.83)). Participants’ TCRE was stable for each ROI across both time points, with ROIs’ COVrep ranging from 0.81 – 3.08% (mean COVrep = 1.92%); 30 ROIs had a COVrep < 2.0%.ConclusionsBrain temperature demonstrated subtle regional variations that were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring pathological brain temperature changes when other modalities are unrevealing. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.

T160. HIGH-RESOLUTION WHOLE BRAIN MR SPECTROSCOPIC IMAGING IN YOUTHS AT CLINICAL HIGH RISK FOR PSYCHOSIS: A PILOT STUDY

Background In general, MR spectroscopy (MRS) studies report alterations of both glutamatergic indices and NAA not only in first episode psychosis and established schizophrenia but also in high risk populations, suggesting that altered excitatory neurotransmission and loss of neuronal integrity are early pathophysiological processes. However, interpretation of these findings is limited by the region-of-interest approach of current MRS techniques, limiting the measurement of metabolites to delimited cerebral volumes, selected by a priori hypotheses. In that context, we developed and implemented a new technique including specific MR sequence and data reconstruction that allows for whole brain high-resolution MRS imaging (MRSI) in two or three dimensions. The results enable the mapping of main metabolites in all brain regions (cortex, white matter, deep grey matter) of youths at clinical high risk for psychosis (CHR-P). Methods An FID-MRSI (Henning et al. NMR Biomed 2009) sequence with a 3D phase encoding accelerated by compressed-sensing was implemented on a 3T Prisma fit MRI (Siemens, Erlangen, Germany). The echo time (TE) was 0.65 ms, repetition time (TR) was 355 ms and the flip angle 35 degree. FID was acquired with 4 kHz bandwidth. The size of the excited Volume of Interest (VOI) was (A/P-R/L-H/F) 210 mm by 160 mm by 95 mm with a matrix of 42 x 32 x 20 resulting in 5 mm isotropic resolution. After reconstruction (Klauser A et al. Magn Reson Med. 2018), 3D MRSI data were quantified with LCModel to produce 3D metabolite maps. Concentration for total N-acetyl aspartate (tNAA), total creatinine (tCre), choline-containing compounds (Cho), myo-inositol (Ins), glutamate and glutamine (Glx) were calculated in every single voxel. A T1-weighted MPRAGE anatomical scan was acquired for positioning of the 3D MRSI and for the segmentation of the brain. For each participant, brain tissue was segmented into gray and white matter. Cerebral lobes and deep grey mater structures were also delineated using Freesurfer software package. CHR-P individuals were recruited in the service of child and adolescent psychiatry and in the service of general psychiatry, department of psychiatry at Lausanne university hospital. They were help-seeking adolescents and young adults aged between 14 and 35, who presented a psychosis-risk syndrome or basic symptoms as assessed by the Structured Interview for Psychosis-Risk Syndromes (SIPS) and the Schizophrenia Proneness Instrument, Adult (SPI-A) or Child & Youth version (SPI-CY). Healthy controls matched for age and sex were recruited in the general population. Results Three-dimension MRSI provides spatial specificity by allowing main metabolites (i.e., tNAA, tCre, Cho, Ins and Glx) to be reliably mapped in the volume of the entire brain. The resulting contrast allows the recognition of brain compartments and subcortical structures. Individual brain segments, cerebral lobes and subcortical structures were registered to 3D MRSI data and the mean concentration in each structure was computed to allow group comparisons between CHR-P and HC. Discussion In general, there is a strong need to develop new tools for the identification and stratification of CHR-P populations. Alterations of gross brain anatomy are relatively late events but early and subtle neurochemical changes and especially those reflecting oxidative stress and concomitant synaptic remodeling are promising candidates. This pilot study illustrates the potential of three-dimension MRSI to detect such alterations in the whole brain and with a good spatial resolution.

A method for cranial target delineation in radiotherapy treatment planning aided by single-voxel magnetic resonance spectroscopy: evaluation using a custom-designed gel-based phantom and simulations

Objective: Magnetic resonance spectroscopy (MRS) has been useful in radiotherapy treatment planning (RTP) especially in tumor delineation. Routinely, 2D/3D MRSI data are used for this application. However, not all centers have access to 2D/3D MRSI. The objective of this study was to introduce a method of using single-voxel spectroscopy (SVS) data in target delineation and assess its reliability. Methods: A gel-based phantom containing Creatine (Cr), N-acetyl-l-aspartic-acid (NAA), and Choline (Cho) was designed and built. The metabolite ratios simulate the normal and tumoral part of the brain. The jMRUI software (v. 6.0) was used to simulate a 1.5 T GE MRI scanner. The metabolite spectra provided by different time of echos (TE)s of the Point-RESolved Spectroscopy pulse-sequence (PRESS), different data-points, and post-processings were quantized by jMRUI. PseudoMRSI maps of Cho/Cr, NAA/Cr, and Cho + Cr/NAA were created. A conformity index (CI) was used to determine which metabolite-ratio isolines are more appropriate for tumor delineation. Results: The simulation accuracy was verified. There were no differences > 4% between the measured and simulated spectra in peak regions. The pseudoMRSI map of Cho + Cr/NAA smoothly followed the complicated geometry of the tumor inside the gel-based phantom. The results showed that the single-voxel spectra produced by the PRESS pulse sequence with the TE of 144 ms, 512 data-points, and minimum post-processings of water suppression, eddy current correction, and baseline correction can be used for target delineation. Conclusion: This study suggests that SVS data can be used to aid target delineation by using a mathematical approach. This can enable a wider use of MR-derived information in radiotherapy. Advances in knowledge: To the best of our knowledge, until now, 2D or 3D MRSI data provided from 3T MRI scanners have been used for MRS-based radiotherapy treatment planning. However, there are a lot of centers that are equipped to 1.5 T MRI scanners and some of them just equipped to SVS. This study introduces a mathematical approach to help these centers to take the benefits of MRS-based treatment planning.