Voxel Composition Research Articles

Quantification of the neurochemical profile of the human putamen using STEAM MRS in a cohort of elderly subjects at 3 T and 7 T: Ruminations on the correction strategy for the tissue voxel composition.

The aim of this work is to quantify the metabolic profile of the human putamen in vivo in a cohort of elderly subjects using single-voxel proton magnetic resonance spectroscopy. To obtain metabolite concentrations specific to the putamen, we investigated a correction method previously proposed to account for the tissue composition of the volume of interest. We compared the method with the conventional approach, which a priori assumes equal metabolite concentrations in GM and WM. Finally, we compared the concentrations acquired at 3 Tesla (T) and 7 T MRI scanners. Spectra were acquired from 15 subjects (age: 67.7 ± 8.3 years) at 3 T and 7 T, using an ultra-short echo time, stimulated echo acquisition mode sequence. To robustly estimate the WM-to-GM metabolite concentration ratio, five additional subjects were measured for whom the MRS voxel was deliberately shifted from the putamen in order to increase the covered amount of surrounding WM. The concentration and WM-to-GM concentration ratio for 16 metabolites were reliably estimated. These ratios ranged from ~0.3 for γ-aminobutyric acid to ~4 for N-acetylaspartylglutamate. The investigated correction method led to significant changes in concentrations compared to the conventional method, provided that the ratio significantly differed from unity. Finally, we demonstrated that differences in tissue voxel composition cannot fully account for the observed concentration difference between field strengths. We provide not only a fully comprehensive quantification of the neurochemical profile of the putamen in elderly subjects, but also a quantification of the WM-to-GM concentration ratio. This knowledge may serve as a basis for future studies with varying tissue voxel composition, either due to tissue atrophy, inconsistent voxel positioning or simply when pooling data from different voxel locations.

Ultrafast Z-spectroscopic imaging in vivo at 3T using through-slice spectral encoding (TS-UFZ).

Acquisition of high-resolution Z-spectra for CEST or magnetization transfer contrast (MTC) MRI requires excessive scan times. Ultrafast Z-spectroscopy (UFZ) has been proposed to address this; however, the quality of in vivo UFZ spectra has been insufficient. Here, we present a simple approach to improve this. UFZ imaging acquires full Z-spectra by encoding the spectral dimension spatially via a gradient applied concurrently with the RF saturation pulse. Different from previous implementations, both this saturation gradient and its readout were applied in the slice direction, resulting in a relatively uniform voxel composition. Phase-encoding was applied in both in-plane directions, allowing additional under-sampling and acceleration. In phantoms, UFZ imaging with through-slice Z-spectral encoding (TS-UFZ) provided Z-spectra of salicylic acid and egg white in excellent agreement with conventional acquisitions. In vivo brain Z-spectra were influenced by flow through the imaging slice which affected the Z-spectral baseline. Still, CEST signals could be quantified after baseline fitting and mapping the residual CEST signal. Amide proton transfer (APT) contrast intensities obtained by TS-UFZ were on the same order of magnitude as conventional CEST but with different contrast across slice which likely is a result of different tissue regions contributing. TS-UFZ approach improves signal stability and spectral uniformity over previous implementations and allows high spectral-resolution imaging of saturation transfer effects in the human brain at 3T. This implementation allows for further acceleration by reducing phase encoding steps and thus opens up the possibility of mapping dynamic CEST signals in vivo with a practical temporal resolution.

(186) Age and Pain-Related Contributions to Biochemical Brain Alterations Community-Dwelling Individuals

Altered brain neurochemistry has been previously reported in older individuals as well as in persons with chronic pain. Since chronic pain is commonly present in older individuals, is not currently known whether previously reported neurochemical and metabolic alterations are directly related to an aged central nervous system rather than the experience of chronic pain. The present study was aimed to determine age and pain-specific differences in brain metabolites and their associations with clinical and experimental pain. Younger (18-26 years old, n=20) and cognitively intact older adults (mean age=71.7±7.8, 63% female) with (n=25) and without chronic pain (n=13) participated in the Neuromodulatory Examination of Pain Across the Lifespan (NEPAL) Study at the University of Florida. Proton MRS (1H-MRS) was acquired from a frontal brain voxel using a Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) approach. LCModel was used to quantify N–acetyl aspartate (NAA-neuronal density, integrity), Myo-Inositol (Ins-glial activation, neuroinflammation), choline (tCho-cell membrane turnover), creatine (tCr- energy metabolism) and cerebrospinal fluid (CSF) voxel composition. Older individuals had significantly lower [NAA] compared to younger controls (p=0.0003). Conversely, older individuals had significantly greater [Ins], [tCr] and [tCho] compared to younger controls (p's

Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer.

Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data.Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T1-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions.Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes.Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.

Abstract 3723: Assessing the reproducibility of computer-aided nodule assessment and risk yield (CANARY) method to characterize lung adenocarcinomas

Abstract This study assessed the inter-user reproducibility of Computer-Aided Nodule Assessment and Risk Yield (CANARY), a novel analytical tool that risk stratifies lung adenocarcinomas (ADCs) according to defined computed tomography (CT) structural characteristics. CANARY detects nine distinct voxel signatures in ADCs based on standard CT imaging, thereby defining nodule characteristics correlating with patient outcomes, and corresponding to invasion or lepidic growth histologically. A software user segments the borders of each ADC prior to voxel analysis, introducing potential variability into the assessment. While CANARY is a promising method, it requires validation of the analytical variability between users and prediction of accuracy in an independent cohort. To evaluate the reproducibility of CANARY analysis, three independent users who are not part of the CANARY development team segmented and analyzed 50 biopsy-confirmed primary lung ADCs from Vanderbilt University Medical Center. The CT scans of ADCs were selected retrospectively based on the following criteria: ADC-histology proven on biopsy, diagnosed between 2009-2015, less than 3cm in greatest diameter, and stages IA-IV. Users followed a standard operating procedure established at the Mayo Clinic, and were blinded to clinical characteristics and patient outcomes. Results: To measure inter-user variability of ADC voxel composition, the intraclass correlation coefficient (ICC) was calculated based upon the percentage of each voxel subtype within the whole ADC. An ICC of 1 reflects high reproducibility between users. Amongst all 50 ADCs, the average ICC for all nine voxel types was 0.828 (95% CI 0.76, 0.895). The ICC of the four voxel types associated with invasive features on CT was 0.865 (95% CI 0.805, 0.924). ICCs were also calculated using a logarithmic transformation for data normalization, generating an ICC of 0.745 (95% CI 0.663, 0.826) for all nine voxel types, and an ICC of 0.995 (95% CI 0.993, 0.997) for the four voxel types associated with invasion. Conclusions: (1) CANARY analysis of lung ADC voxel signatures appears to be reproducible amongst users, making it a reliable tool for the evaluation of ADC voxel density. (2) Correlation of invasive signatures associated with more aggressive ADCs was nearly perfect amongst users. Additional validation metrics for CANARY with larger datasets are being evaluated, including the accuracy of tumor prognostic predictions between users and analysis of ADC datasets from other institutions. Citation Format: Erica C. Nakajima, Michael P. Frankland, Tucker Johnson, Sanja L. Antic, Ronald A. Karwoski, Bennett Landman, Heidi Chen, Ronald C. Walker, Brian J. Bartholmai, Tobias Peikert, Srinivasan Rajagopalan, Pierre P. Massion, Fabien Maldonado. Assessing the reproducibility of computer-aided nodule assessment and risk yield (CANARY) method to characterize lung adenocarcinomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3723. doi:10.1158/1538-7445.AM2017-3723

Intra voxel analysis in magnetic resonance imaging

A technique for analyzing the composition of each voxel, in the magnetic resonance imaging (MRI) framework, is presented. By combining different acquisitions, a novel methodology, called intra voxel analysis (IVA), for the detection of multiple tissues and the estimation of their spin–spin relaxation times is proposed. The methodology exploits the sparse Bayesian learning (SBL) approach in order to solve a highly underdetermined problem imposing the solution sparsity. IVA, developed for spin echo imaging sequence, can be easily extended to any acquisition scheme. For validating the approach, simulated and real data sets are considered. Monte Carlo simulations have been implemented for evaluating the performances of IVA compared to methods existing in literature. Two clinical datasets acquired with a 3T scanner have been considered for validating the approach. With respect to other approaches presented in literature, IVA has proved to be more effective in the voxel composition analysis, in particular in the case of few acquired images. Results are interesting and very promising: IVA is expected to have a remarkable impact on the research community and on the diagnostic field.

Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model.

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexibl representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplifie treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.

Tissue correction for GABA-edited MRS: Considerations of voxel composition, tissue segmentation, and tissue relaxations.

To develop a tissue correction for GABA-edited magnetic resonance spectroscopy (MRS) that appropriately addresses differences in voxel gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) fractions. Simulations compared the performance of tissue correction approaches. Corrections were then applied to in vivo data from 16 healthy volunteers, acquired at 3T. GM, WM, and CSF fractions were determined from T1 -weighted images. Corrections for CSF content, GM/WM GABA content, and water relaxation of the three compartments are combined into a single, fully corrected measurement. Simulations show that CSF correction increases the dependence of GABA measurements on GM/WM fraction, by an amount equal to the fraction of CSF. Furthermore, GM correction substantially (and nonlinearly) increases the dependence of GABA measurements on GM/WM fraction, for example, by a factor of over four when the voxel GM tissue fraction is 50%. At this tissue fraction, GABA is overestimated by a factor of 1.5. For the in vivo data, correcting for voxel composition increased measured GABA values (P < 0.001 for all regions), but did not reduce intersubject variance (P > 0.5 for all regions). Corrected GABA values differ significantly based on the segmentation procedure used (P < 0.0001) and tissue parameter assumptions made (P < 0.0001). We introduce a comprehensive tissue correction factor that adjusts GABA measurements to correct for different voxel compositions of GM, WM, and CSF.

Feasibility and reproducibility of neurochemical profile quantification in the human hippocampus at 3 T.

Hippocampal dysfunction is known to be associated with several neurological and neuropsychiatric disorders such as Alzheimer's disease, epilepsy, schizophrenia and depression; therefore, there has been significant clinical interest in studying hippocampal neurochemistry. However, the hippocampus is a challenging region to study using (1) H MRS, hence the use of MRS for clinical research in this region has been limited. Our goal was therefore to investigate the feasibility of obtaining high-quality hippocampal spectra that allow reliable quantification of a neurochemical profile and to establish inter-session reproducibility of hippocampal MRS, including reproducibility of voxel placement, spectral quality and neurochemical concentrations. Ten healthy volunteers were scanned in two consecutive sessions using a standard clinical 3 T MR scanner. Neurochemical profiles were obtained with a short-echo (T(E) = 28 ms) semi-LASER localization sequence from a relatively small (~4 mL) voxel that covered about 62% of the hippocampal volume as calculated from segmentation of T1 -weighted images. Voxel composition was highly reproducible between sessions, with test-retest coefficients of variation (CVs) of 3.5% and 7.5% for gray and white matter volume fraction, respectively. Excellent signal-to-noise ratio (~54 based on the N-acetylaspartate (NAA) methyl peak in non-apodized spectra) and linewidths (~9 Hz for water) were achieved reproducibly in all subjects. The spectral quality allowed quantification of NAA, total choline, total creatine, myo-inositol and glutamate with high scan-rescan reproducibility (CV ≤ 6%) and quantification precision (Cramér-Rao lower bound, CRLB < 9%). Four other metabolites, including glutathione and glucose, were quantified with scan-rescan CV below 20%. Therefore, the highly optimized, short-echo semi-LASER sequence together with FASTMAP shimming substantially improved the reproducibility and number of quantifiable metabolites relative to prior reports. In addition, the between-session variation in metabolite concentrations, as well as CRLB, was lower than the between-subject variation of the concentrations for most metabolites, indicating that the method has the sensitivity to detect inter-individual differences in the healthy brain.

The partial volume effect in the quantification of 1H magnetic resonance spectroscopy in Alzheimer's disease and aging.

1H-MRS variability increases due to normal aging and also as a result of atrophy in grey and white matter caused by neurodegeneration. In this work, an automatic process was developed to integrate data from spectra and high-resolution anatomical images to quantify metabolites, taking into account tissue partial volumes within the voxel of interest avoiding additional spectra acquisitions required for partial volume correction. To evaluate this method, we use a cohort of 135 subjects (47 male and 88 female, aged between 57 and 99 years) classified into 4 groups: 38 healthy participants, 20 amnesic mild cognitive impairment patients, 22 multi-domain mild cognitive impairment patients, and 55 Alzheimer's disease patients. Our findings suggest that knowing the voxel composition of white and grey matter and cerebrospinal fluid is necessary to avoid partial volume variations in a single-voxel study and to decrease part of the variability found in metabolites quantification, particularly in those studies involving elder patients and neurodegenerative diseases. The proposed method facilitates the use of 1H-MRS techniques in statistical studies in Alzheimer's disease, because it provides more accurate quantitative measurements, reduces the inter-subject variability, and improves statistical results when performing group comparisons.

Erratum: Reduced subcortical glutamate/glutamine in adults with autism spectrum disorders: a [1H]MRS study

Dysfunctional glutamatergic neurotransmission has been implicated in autism spectrum disorder (ASD). However, relatively few studies have directly measured brain glutamate in ASD adults, or related variation in glutamate to clinical phenotype. We therefore set out to investigate brain glutamate levels in adults with an ASD, comparing these to healthy controls and also comparing results between individuals at different points on the spectrum of symptom severity. We recruited 28 adults with ASD and 14 matched healthy controls. Of those with ASD, 15 fulfilled the 'narrowly' defined criteria for typical autism, whereas 13 met the 'broader phenotype'. We measured the concentration of the combined glutamate and glutamine signal (Glx), and other important metabolites, using proton magnetic resonance spectroscopy in two brain regions implicated in ASD--the basal ganglia (including the head of caudate and the anterior putamen) and the dorsolateral prefrontal cortex--as well as in a parietal cortex 'control' region. Individuals with ASD had a significant decrease (P<0.001) in concentration of Glx in the basal ganglia, and this was true in both the 'narrow' and 'broader' phenotype. Also, within the ASD sample, reduced basal ganglia Glx was significantly correlated with increased impairment in social communication (P=0.013). In addition, there was a significant reduction in the concentration of other metabolites such as choline, creatine (Cr) and N-acetylaspartate (NAA) in the basal ganglia. In the dorsolateral prefrontal cortex, Cr and NAA were reduced (P<0.05), although Glx was not. There were no detectable differences in Glx, or any other metabolite, in the parietal lobe control region. There were no significant between-group differences in age, gender, IQ, voxel composition or data quality. In conclusion, individuals across the spectrum of ASD have regionally specific abnormalities in subcortical glutamatergic neurotransmission that are associated with variation in social development.

Reduced subcortical glutamate/glutamine in adults with autism spectrum disorders: a [1H]MRS study

Dysfunctional glutamatergic neurotransmission has been implicated in autism spectrum disorder (ASD). However, relatively few studies have directly measured brain glutamate in ASD adults, or related variation in glutamate to clinical phenotype. We therefore set out to investigate brain glutamate levels in adults with an ASD, comparing these to healthy controls and also comparing results between individuals at different points on the spectrum of symptom severity. We recruited 28 adults with ASD and 14 matched healthy controls. Of those with ASD, 15 fulfilled the ‘narrowly' defined criteria for typical autism, whereas 13 met the ‘broader phenotype'. We measured the concentration of the combined glutamate and glutamine signal (Glx), and other important metabolites, using proton magnetic resonance spectroscopy in two brain regions implicated in ASD—the basal ganglia (including the head of caudate and the anterior putamen) and the dorsolateral prefrontal cortex—as well as in a parietal cortex ‘control' region. Individuals with ASD had a significant decrease (P<0.001) in concentration of Glx in the basal ganglia, and this was true in both the ‘narrow' and ‘broader' phenotype. Also, within the ASD sample, reduced basal ganglia Glx was significantly correlated with increased impairment in social communication (P=0.013). In addition, there was a significant reduction in the concentration of other metabolites such as choline, creatine (Cr) and N-acetylaspartate (NAA) in the basal ganglia. In the dorsolateral prefrontal cortex, Cr and NAA were reduced (P<0.05), although Glx was not. There were no detectable differences in Glx, or any other metabolite, in the parietal lobe control region. There were no significant between-group differences in age, gender, IQ, voxel composition or data quality. In conclusion, individuals across the spectrum of ASD have regionally specific abnormalities in subcortical glutamatergic neurotransmission that are associated with variation in social development.

WE‐C‐108‐11: Patient‐Specific Monte Carlo Simulation of Lung Brachytherapy: Metallic Artifact Reduction and Organ‐Constrained Tissue Assignment

Purpose: To investigate techniques for developing accurate patient‐specific computational phantoms for Monte Carlo simulations of lung brachytherapy. Methods to mitigate streaking artifacts due to brachytherapy sources in CT images and organ‐constrained tissue assignment schemes are explored. Methods: Three different metallic artifact reduction (MAR) techniques are applied to lung brachytherapy patient CT data: thresholding replaces high CT values with estimated true values; fan‐beam virtual sinogram replaces artifact‐affected values in a virtual sinogram; and 3D median filter uses local voxel values to guide the replacement of outlying voxel values. Computational phantoms are generated from metallic artifact corrected and uncorrected images with voxel composition defined by CT number and density defined either by nominal tissue density or a CT number to density calibration. Multiple tissue assignment schemes are considered, including some with organ‐specific constraints. Dose distributions for I–125 and Cs‐131 seeds are calculated using the EGSnrc user‐code BrachyDose and are compared directly as well as through DVHs and dose metrics for target volumes surrounding surgical sutures. Results: The most effective MAR technique is the virtual sinogram method as it effectively mitigates artifacts while maintaining image integrity. Thresholding only removes artifacts in the vicinity of sources (leaving artifacts in other regions) and median filtering degrades tissue heterogeneities. Dose distributions for phantoms treated with various MAR techniques and tissue assignment schemes can vary significantly. Dose differences between MAR and uncorrected phantoms are reduced by constraining tissue assignments in lung contours; in one example, differences in D90 of 20% are reduced to 3%. Phantoms with nominal densities Result in higher doses than those with CT derived densities. Conclusion: Application of MAR techniques to CT data is necessary to develop realistic computational phantoms for Monte Carlo simulations; the virtual sinogram method is a promising image‐based technique. Organ‐constrained tissue assignment is necessary for accurate tissue assignment. This work was supported by the Natural Sciences and Engineering Research Council, the Canada Research Chairs program, and an Ontario Graduate Scholarship.

Absolute quantitation of brain metabolites with respect to heterogeneous tissue compositions in 1H-MR spectroscopic volumes

Referencing metabolite intensities to the tissue water intensity is commonly applied to determine metabolite concentrations from in vivo (1)H-MRS brain data. However, since the water concentration and relaxation properties differ between grey matter, white matter and cerebrospinal fluid (CSF), the volume fractions of these compartments have to be considered in MRS voxels. The impact of partial volume correction was validated by phantom measurements in voxels containing mixtures of solutions with different NAA and water concentrations as well as by analyzing in vivo (1)H-MRS brain data acquired with various voxel compositions. Phantom measurements indicated substantial underestimation of NAA concentrations when assuming homogeneously composed voxels, especially for voxels containing solution, which simulated CSF (error: ≤ 92%). This bias was substantially reduced by taking into account voxel composition (error: ≤ 10%). In the in vivo study, tissue correction reduced the overall variation of quantified metabolites by up to 35% and revealed the expected metabolic differences between various brain tissues. Tissue composition affects extraction of metabolite concentrations and may cause misinterpretations when comparing measurements performed with different voxel sizes. This variation can be reduced by considering the different tissue types by means of combined analysis of spectroscopic and imaging data.

Striatal metabolic alterations in non-psychotic adolescent offspring at risk for schizophrenia: A 1H spectroscopy study

In vivo proton ( 1H) Magnetic Resonance spectroscopy ( 1H MRS) has shown abnormalities in young first-episode patients with schizophrenia. It is unclear whether these abnormalities reflect trait related vs. state related alterations in schizophrenia. We compared young first-degree relatives of schizophrenia patients and healthy controls using 1H MRS. We hypothesized alterations in the 1H MRS metabolites N-acetyl aspartate (NAA) and glutamate in corticostriatal and thalamic brain regions. We obtained multi-voxel, short-TE 1H MRS measurements at 1.5 Tesla in 40 consenting adolescent offspring at risk for schizophrenia (HR), and 48 age matched healthy controls (HC). Absolute levels of NAA, phosphocreatine plus creatine (PCr + Cr), choline-containing compounds (GPC + PC), myo-inositol and glutamate plus glutamine (Glu + Gln) were obtained from the seven different anatomical brain areas (nominal voxel size of 4.5 cm 3 each) and corrected for tissue voxel composition. HR subjects showed NAA ( p = .0049), PCr + Cr ( p = 0.028) and GPC + PC ( p = 0.0086) reductions in the caudate compared with HC subjects. Male HR subjects had significant Glu + Gln reductions compared to male HC subjects ( p = .0022). HR subjects had increased NAA in prefrontal white matter. NAA levels in the prefrontal white matter and Glu + Gln levels in the inferior parietal/occipital region were both increased in HR without psychopathology compared with HC subjects. Lower NAA, PCr + Cr and GPC + PC levels may reflect an overall reduction in cellular processes in the caudate of HC subjects, perhaps related to decreases in cell density, or synaptic overpruning. Further studies are needed to examine the pathophysiologic significance of these observations, and their potential predictive value for schizophrenia related psychopathology that may emerge in these at risk relatives during adolescence and early adulthood.

Further Evidence for Altered Cerebellar Neuronal Integrity in Schizophrenia

The authors' goal was to investigate the distribution of metabolites and voxel composition in the pons and three cerebellar subregions and compare metabolite integral values and differences in voxel composition between patients with schizophrenia and healthy subjects. Proton magnetic resonance spectroscopic imaging was used to study the cerebellum and pons of 14 patients with schizophrenia and 14 healthy comparison subjects. The voxel composition was not significantly different between the groups, but the patients with schizophrenia had significantly lower N-acetylaspartate levels in the cerebellar cortex and vermis. The lower integral value of N-acetylaspartate in the cerebellar cortex and the vermis of patients with schizophrenia supports the theory of a dysfunctional corticocerebellar-thalamic-cortical circuit in schizophrenia.

A Computational Morphometric MRI Study of Schizophrenia: Effects of Hallucinations

Quantitative magnetic resonance imaging (MRI) studies in patients with schizophrenia have shown reliable deficits in global tissue volume as well as some regionally specific changes, particularly in the temporal and frontal lobes. Recent technical advances have enabled automated voxel-wise analyses, which have the advantage of facilitating whole brain coverage without the restrictions of anatomically defined regions of interest and imperfect rater reliability. We used such a method to estimate voxel composition from segmentation of bivariate, dual-echo spin-echo data in 72 men with schizophrenia. Of these, 41 had a prominent history of auditory-verbal hallucinations and 31 had no such history. The patients were compared with 32 age, gender, handedness and IQ matched healthy controls. The study revealed localized areas of reduced grey-matter tissue proportion aggregating around the medial temporal lobes, the insulae, orbito-frontal cortex including anterior cingulate, and the precuneus (and lingual) gyri, in the schizophrenia patients as a whole. There were also reductions in white-matter tissue proportion extending along much of the large anterior-posterior frontal tracts in the right hemisphere. Small regions of increased grey matter were also noted in the right inferior parietal lobe. A contrast between the hallucinator and non-hallucinator patient groups showed a single region of reduced grey-matter tissue proportion affecting the left insula and adjacent temporal lobe. These data confirm the utility of voxel-based morphometric methods in schizophrenia research and point towards disruption to a 'paralimbic' neural network, as underlying schizophrenic psychopathology in general, with abnormalities of the left insula specifically related to hallucinations.

Quantitation of localized (31)P magnetic resonance spectra based on the reciprocity principle.

There is a need for absolute quantitation methods in (31)P magnetic resonance spectroscopy, because none of the phosphorous-containing metabolites is necessarily constant in pathology. Here, a method for absolute quantitation of in vivo (31)P MR spectra that provides reproducible metabolite contents in institutional or standard units is described. It relies on the reciprocity principle, i.e., the proportionality between the B(1) field map and the map of reception strength for a coil with identical relative current distributions in receive and transmit mode. Cerebral tissue contents of (31)P metabolites were determined in a predominantly white matter-containing location in healthy subjects. The results are in good agreement with the literature and the interexamination coefficient of variance is better than that in most previous studies. A gender difference found for some of the (31)P metabolites may be explained by different voxel composition.

Reduced glutamate in the anterior cingulate cortex in depression: an in vivo proton magnetic resonance spectroscopy study

Background: Functional imaging studies suggest a specific role of the anterior brain regions in the pathogenesis of major depression. The aim of this study was to evaluate possible neurochemical alterations in the frontomesial cortex in patients with major depressive episode using in vivo proton magnetic resonance spectroscopy ( 1H-MRS). Methods: Single voxel 1H-MRS was performed in 19 patients with major depressive episodes and 18 age-matched healthy controls within the anterior cingulate cortex and the parietal white matter. Absolute concentrations were estimated for N-acetyl-aspartate, choline-containing compounds, total creatine, myo-inositol, unresolved glutamate and glutamine (Glx) and glutamate alone (Glu). Voxel composition was analyzed by image segmentation into cerebrospinal fluid (CSF), grey and white matter. Results: MANOVA test for Glx and Glu using age, percent CSF and percent grey matter contribution as covariates yielded a significant group effect within the anterior cingulate due to decrease of Glx in patients (−10.4%, p = .013). Considering only severely depressed patients, both Glx and Glu (−14.3%, p = .03) showed a significant decrease. There was no significant group effect for the neuronal marker NAA, creatine, choline or myo-inositol in either localization. Conclusions: This study suggests a possible role of altered glutamatergic neurotransmission within the anterior cingulate in the pathogenesis of mood disorders. The otherwise unremarkable findings of major brain metabolites confirms lack of neurodegenerative or membrane metabolic changes in major depression.

Measurement of Brain Compartment Volumes in MR using Voxel Composition Calculations

A computer method was developed for brain compartment volume measurement in MR images. The method is a statistical averaging technique, in which each voxel is viewed as a mixture of adjacent tissues in a measurable proportion. This method is based on sampling representative tissue intensities and then interpolating intermediate intensities. It can automatically correct for volume averaging artifacts occurring in voxels that contain heterogeneous tissues.