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Background and Purpose: Knowledge of age-related physiological changes in the human brain is a prerequisite to identify neurodegenerative diseases. Therefore, in this study whole-brain (1)H-MRS was used in combination with quantitative MR imaging to study the effects of normal aging on healthy human brain metabolites and microstructure., Materials and Methods: Sixty healthy volunteers, 21-70 years of age, were studied. Brain maps of the metabolites NAA, creatine and phosphocreatine, and Cho and the tissue irreversible and reversible transverse relaxation times T2 and T2' were derived from the datasets. The relative metabolite concentrations and the values of relaxation times were measured with ROIs placed within the frontal and parietal WM, centrum semiovale, splenium of the corpus callosum, hand motor area, occipital GM, putamen, thalamus, pons ventral/dorsal, and cerebellar white matter and posterior lobe. Linear regression analysis and Pearson correlation tests were used to analyze the data., Results: Aging resulted in decreased NAA concentrations in the occipital GM, putamen, splenium of the corpus callosum, and pons ventral and decreased creatine and phosphocreatine concentrations in the pons dorsal and putamen. Cho concentrations did not change significantly in selected brain regions. T2 increased in the cerebellar white matter and decreased in the splenium of the corpus callosum with aging, while the T2' decreased in the occipital GM, hand motor area, and putamen, and increased in the splenium of the corpus callosum. Correlations were found between NAA concentrations and T2' in the occipital GM and putamen and between creatine and phosphocreatine concentrations and T2' in the putamen., Conclusions: The effects of normal aging on brain metabolites and microstructure are region-dependent. Correlations between both processes are evident in the gray matter. The obtained data could be used as references for future studies on patients., (© 2016 by American Journal of Neuroradiology.)

Purpose: To assess volumetric proton MR spectroscopic imaging (MRSI) of the human brain on multivendor MRI instruments., Methods: Echo-planar spectroscopic imaging was developed on instruments from three manufacturers, with matched specifications and acquisition protocols that accounted for differences in sampling performance, radiofrequency (RF) power, and data formats. Intersite reproducibility was evaluated for signal-normalized maps of N-acetylaspartate (NAA), creatine (Cre), and choline using phantom and human subject measurements. Comparative analyses included metrics for spectral quality, spatial coverage, and mean values in atlas-registered brain regions., Results: Intersite differences for phantom measurements were less than 1.7% for individual metabolites and less than 0.2% for ratio measurements. Spatial uniformity ranged from 79% to 91%. The human studies found differences of mean values in the temporal lobe, but good agreement in other white matter regions, with maximum differences relative to their mean of under 3.2%. For NAA/Cre, the maximum difference was 1.8%. In gray matter, a significant difference was observed for frontal lobe NAA. Primary causes of intersite differences were attributed to shim quality, B0 drift, and accuracy of RF excitation. Correlation coefficients for measurements at each site were over 0.60, indicating good reliability., Conclusion: A volumetric intensity-normalized MRSI acquisition can be implemented in a comparable manner across multivendor MR instruments., (© 2014 Wiley Periodicals, Inc.)

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., (© 2014 Wiley Periodicals, Inc.)

Magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) studies have demonstrated that measures of altered metabolism and axonal injury can be detected following traumatic brain injury. The aim of this study was to characterize and compare the distributions of altered image parameters obtained by these methods in subjects with a range of injury severity and to examine their relative sensitivity for diagnostic imaging in this group of subjects. DTI and volumetric magnetic resonance spectroscopic imaging data were acquired in 40 subjects that had experienced a closed-head traumatic brain injury, with a median of 36 d post-injury. Voxel-based analyses were performed to examine differences of group mean values relative to normal controls, and to map significant alterations of image parameters in individual subjects. The between-group analysis revealed widespread alteration of tissue metabolites that was most strongly characterized by increased choline throughout the cerebrum and cerebellum, reaching as much as 40% increase from control values for the group with the worse cognitive assessment score. In contrast, the between-group comparison of DTI measures revealed only minor differences; however, the Z-score image analysis of individual subject DTI parameters revealed regions of altered values relative to controls throughout the major white matter tracts, but with considerable heterogeneity between subjects and with a smaller extent than the findings for altered metabolite measures. The findings of this study illustrate the complimentary nature of these neuroimaging methods.

Purpose: A feasibility study of an echo-planar spectroscopic imaging (EPSI) using a short echo time (TE) that trades off sensitivity, compared with other short-TE methods, to achieve whole brain coverage using inversion recovery and spatial oversampling to control lipid bleeding., Methods: Twenty subjects were scanned to examine intersubject variance. One subject was scanned five times to examine intrasubject reproducibility. Data were analyzed to determine coefficients of variance (COV) and intraclass correlation coefficient (ICC) for N-acetylaspartate (NAA), total creatine (tCr), total choline (tCho), glutamine/glutamate (Glx), and myo-inositol (mI). Regional metabolite concentrations were derived by using multi-voxel analysis based on lobar-level anatomic regions., Results: For whole-brain mean values, the intrasubject COVs were 14%, 15%, and 20% for NAA, tCr, and tCho, respectively, and 31% for Glx and mI. The intersubject COVs were up to 6% higher. For regional distributions, the intrasubject COVs were ≤ 5% for NAA, tCr, and tCho; ≤ 9% for Glx; and ≤15% for mI, with about 6% higher intersubject COVs. The ICCs of 5 metabolites were ≥ 0.7, indicating the reliability of the measurements., Conclusion: The present EPSI method enables estimation of the whole-brain metabolite distributions, including Glx and mI with small voxel size, and a reasonable scan time and reproducibility., (© 2014 Wiley Periodicals, Inc.)

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 <0.05). This study provides additional reference data that can be utilised in interventional studies to quantify change within a single imaging session, or to assess the significance of change in longitudinal studies of brain injury and disease.

Background and Purpose: Studies of brain tumors have identified altered tissue metabolism and water diffusion in MRI normal appearing tissue regions. In this retrospective study the relationship of these imaging measures with tumor grade in gliomas was investigated., Methods: MR spectroscopic imaging of whole brain and mean diffusivity (MD) measurements were obtained in subjects with untreated glioma and from normal control subjects. Mean metabolite values for N-acetylaspartate (NAA), total creatine (Cre), and total choline (Cho) were obtained in gray- and white-matter regions for the hemisphere contralateral to the tumor location, and MD values were obtained from contralateral normal-appearing white matter. Analyses tested for differences in mean values between subject groups while accounting for age., Results: Analysis demonstrated increased NAA/Cre and MD, and decreased Cho/NAA for all tumor grades relative to control values. Differences between tumor grades were also observed for NAA, NAA/Cre, and Cho/NAA. Abnormal values of water diffusion were also observed, but with only a weak association between alterations in diffusion and tissue metabolites., Conclusions: This study supports previous observations of altered tissue metabolism and water diffusion in normal-appearing white matter while additionally finding differences of metabolite values in gray matter and an association with tumor grade., (Copyright © 2013 by the American Society of Neuroimaging.)

Purpose: Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV])., Methods and Materials: Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV46 and CTV60, respectively). MTVCho and MTVNAA were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue., Results: The MRSI coverage of the brain was between 70% and 76%. The MTVNAA were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTVCho was outside of the edema (median, 33%) and for some patients it was also outside of the CTV46 and CTV60. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTVCho for these patients were outside of CTV60., Conclusions: This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on metabolic information., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background and Purpose: Increased glycine concentration in the brain is associated with altered metabolism in cancer and can be detected by using in vivo MR spectroscopy. This has been proposed as a marker for grade IV gliomas; however, little is known about the potential significance and frequency of in vivo glycine observation. The purpose of this study was to examine the rate of occurrence and spatial distribution of glycine observation with respect to other MR imaging parameters., Materials and Methods: Data from volumetric whole-brain MR spectroscopic imaging of 59 subjects with glioma were analyzed with glycine included in the spectral model. The associations of the signal amplitude and spatial distributions of glycine with findings from contrast-enhanced T1, perfusion, and diffusion MR imaging were then examined., Results: Glycine was detected in 24% of all studies, though with a wide range of signal amplitude and extent of the spatial distributions. While more commonly seen in grade IV tumors (42% of studies), relatively large concentrations were also detected in grade II and III gliomas. Coanalysis with other metabolites indicated a strong association with choline and that glycine was frequently seen to be overlapping with, and adjacent to, areas of high lactate concentration. Increased glycine was always associated with contrast enhancement and areas of increased cerebral blood flow, but without any clear association with other image parameters., Conclusions: Detection of increased glycine in gliomas appears to identify a subgroup of tumors and areas of increased proliferation., (© 2014 by American Journal of Neuroradiology.)

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)

Purpose: To assess the impact of accelerated acquisitions on the spectral quality of volumetric magnetic resonance spectroscopic imaging (MRSI) and to evaluate their ability in detecting metabolic changes with mild injury., Materials and Methods: The implementation of a generalized autocalibrating partially parallel acquisition (GRAPPA) method for a high-resolution whole-brain echo planar SI (3D-EPSI) sequence is first described and the spectral accuracy of the GRAPPA-EPSI method is investigated using lobar and voxel-based analyses for normal subjects and patients with mild traumatic brain injuries (mTBI). The performance of GRAPPA was compared with that of fully encoded EPSI for five datasets collected from normal subjects at the same scanning session, as well as on 45 scans (20 normal subjects and 25 mTBI patients) for which the reduced k-space sampling was simulated. For comparison, a central k-space lower-resolution 3D-EPSI acquisition was also simulated. Differences in individual metabolites and metabolite ratio distributions of the mTBI group relative to those of age-matched control subjects were statistically evaluated using analyses divided into hemispheric brain lobes and tissue types., Results: GRAPPA-EPSI with 16-minute scan time yielded robust and similar results in terms of MRSI quantitation, spectral fitting, and accuracy with that of fully sampled 3D-EPSI acquisitions and was more accurate than central k-space acquisition. Primary findings included high correlations (accuracy of 92.6%) between the GRAPPA and fully sampled results., Conclusion: Although the reduced encoding method is associated with lower signal-to-noise ratio (SNR) that impacts the quality of spectral analysis, the use of the parallel imaging method can lead to the same diagnostic outcomes as the fully sampled data when using the sensitivity-limited volumetric MRSI., (Copyright © 2013 Wiley Periodicals, Inc.)

An efficient method for obtaining longitudinal relaxation time (T1) maps is based on acquiring two spoiled gradient recalled echo (SPGR) images in steady states with different flip angles, which has also been extended, with additional acquisitions, to obtain a tissue water content (M0) map. Several factors, including inhomogeneities of the radio-frequency (RF) fields and low signal-to-noise ratios may negatively affect the accuracy of this method and produce systematic errors in T1 and M0 estimations. Thus far, these limitations have been addressed by using additional measurements and applying suitable corrections; however, the concomitant increase in scan time is undesirable for clinical studies. In this note, a modified dual-acquisition SPGR method based on an optimization of the sequence formulism is presented for good and reliable M0 mapping with an isotropic spatial resolution of 1×1×1mm(3) that covers the entire human brain in 6:30min. A combined RF transmit/receive map is estimated from one of the SPGR scans and the optimal flip angles for M0 map are found analytically. The method was successfully evaluated in eight healthy subjects producing mean M0 values of 69.8% (in white matter) and 80.1% (in gray matter) that are in good agreement with those found in the literature and with high reproducibility. The mean value of the resultant voxel-based coefficients-of-variation was 3.6%., (© 2013.)

Purpose: To detect regional metabolic differences in amyotrophic lateral sclerosis (ALS) with whole-brain echo-planar spectroscopic imaging., Materials and Methods: Sixteen patients with ALS (nine men, seven women; mean age, 56.6 years), five persons suspected of having ALS (four men, one woman; mean age, 62.6 years), and 10 healthy control subjects (five men, five women; mean age, 56.1 years) underwent echo-planar spectroscopic imaging after providing informed consent. The study was approved by the institutional review board and complied with HIPAA. Data were analyzed with the Metabolic Imaging and Data Analysis System software, and processed metabolite maps were coregistered and normalized to a standard brain template. Metabolite maps of creatine (Cr), choline (Cho), and N-acetylaspartate (NAA) were segmented into 81 regions with Automated Anatomical Labeling software to measure metabolic changes throughout the brains of patients with ALS. Statistical analysis involved an unpaired, uncorrected, two-sided Student t test., Results: The NAA/Cho ratio across six regions was significantly lower by a mean of 23% (P ≤ .01) in patients with ALS than in control subjects. These regions included the caudate, lingual gyrus, supramarginal gyrus, and right and left superior and right inferior occipital lobes. The NAA/Cr ratio was significantly lower (P ≤ .01) in eight regions in the patient group, by a mean of 16%. These included the caudate, cuneus, frontal inferior operculum, Heschl gyrus, precentral gyrus, rolandic operculum, and superior and inferior occipital lobes. The Cho/Cr ratio did not significantly differ in any region between patient and control groups., Conclusion: Whole-brain echo-planar spectroscopic imaging permits detection of regional metabolic abnormalities in ALS, including not only the motor cortex but also several other regions implicated in ALS pathophysiologic findings.

Introduction: Accurate grading of cerebral glioma using conventional structural imaging techniques remains challenging due to the relatively poor sensitivity and specificity of these methods. The purpose of this study was to evaluate the relative sensitivity and specificity of structural magnetic resonance imaging and MR measurements of perfusion, diffusion, and whole-brain spectroscopic parameters for glioma grading., Methods: Fifty-six patients with radiologically suspected untreated glioma were studied with T1- and T2-weighted MR imaging, dynamic contrast-enhanced MR imaging, diffusion tensor imaging, and volumetric whole-brain MR spectroscopic imaging. Receiver-operating characteristic analysis was performed using the relative cerebral blood volume (rCBV), apparent diffusion coefficient, fractional anisotropy, and multiple spectroscopic parameters to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, and positive and negative predictive values for identifying high-grade gliomas. Logistic regression was performed to analyze all the parameters together., Results: The rCBV individually classified glioma as low and high grade with a sensitivity and specificity of 100 and 88 %, respectively, based on a threshold value of 3.34. On combining all parameters under consideration, the classification was achieved with 2 % error and sensitivity and specificity of 100 and 96 %, respectively., Conclusion: Individually, CBV measurement provides the greatest diagnostic performance for predicting glioma grade; however, the most accurate classification can be achieved by combining all of the imaging parameters.

Recent reports have indicated that a measure of adiposity, the body mass index (BMI), is associated with MR-observed brain metabolite concentrations and tissue volume measures. In addition to indicating possible associations between brain metabolism, BMI and cognitive function, the inclusion of BMI as an additional subject selection criterion could potentially improve the detection of metabolic and structural differences between subjects and study groups. In this study, a retrospective analysis of 140 volumetric MRSI datasets was carried out to investigate the value of including BMI in the subject selection relative to age and gender. The findings replicate earlier reports of strong associations of N-acetylaspartate, creatine, choline and gray matter with age and gender, with additional observations of slightly increased spectral linewidth with age and in female relative to male subjects. Associations of metabolite levels, linewidth and gray matter volume with BMI were also observed, although only in some regions. Using voxel-based analyses, it was also observed that the patterns of the relative changes of metabolites with BMI matched those of linewidth with BMI or weight, and that residual magnetic field inhomogeneity and measures of spectral quality were influenced by body weight. It is concluded that, although associations of metabolite levels and tissue distributions with BMI occur, these may be attributable to issues associated with data acquisition and analysis; however, an organic origin for these findings cannot be specifically excluded. There is, however, sufficient evidence to warrant the inclusion of body weight as a subject selection parameter, secondary to age, and as a factor in data analysis for MRS studies of some brain regions., (Copyright © 2011 John Wiley & Sons, Ltd.)

Changes in the distribution of the proton magnetic resonance spectroscopy (MRS) observed metabolites N-acetyl aspartate (NAA), total-choline (Cho), and total-creatine (Cre) in the entire intracranial corticospinal tract (CST) including the primary motor cortex were evaluated in patients with amyotrophic lateral sclerosis (ALS). The study included 38 sporadic definite-ALS subjects and 70 age-matched control subjects. All received whole-brain MR imaging and spectroscopic imaging scans at 3T and clinical neurological assessments including percentage maximum forced vital capacity (FVC) and upper motor neuron (UMN) function. Differences in each individual metabolite and its ratio distributions were evaluated in the entire intracranial CST and in five segments along the length of the CST (at the levels of precentral gyrus (PCG), centrum semiovale (CS), corona radiata (CR), posterior limb of internal capsule (PLIC) and cerebral peduncle (CP)). Major findings included significantly decreased NAA and increased Cho and Cho/NAA in the entire intracranial CST, with the largest differences for Cho/NAA in all the groups. Significant correlations between Cho/NAA in the entire intracranial CST and the right finger tap rate were noted. Of the ten bilateral CST segments, significantly decreased NAA in 4 segments, increased Cho in 5 segments and increased Cho/NAA in all the segments were found. Significant left versus right CST asymmetries were found only in ALS for Cho/NAA in the CS. Among the significant correlations found between Cho/NAA and the clinical assessments included the left-PCG versus FVC and right finger tap rate, left -CR versus FVC and right finger tap rate, and left PLIC versus FVC and right foot tap rate. These results demonstrate that a significant and bilaterally asymmetric alteration of metabolites occurs along the length of the entire intracranial CST in ALS, and the MRS metrics in the segments correlate with measures of disease severity and UMN function.

Previous studies have evaluated motor and extramotor cerebral cortical regions in patients with amyotrophic lateral sclerosis (ALS) using (1) H MRS, but none have evaluated the thalamus or basal ganglia. The objective of this exploratory study was to evaluate the subclinical involvement of the basal ganglia and thalamus in patients with ALS using (1) H MRS. Fourteen patients (52±7 years) with sporadic definite ALS and 17 age-matched controls were studied using volumetric MRSI on a 3-T scanner. The concentration of the metabolites N-acetylaspartate (NAA), choline (Cho) and their ratio (NAA/Cho) were obtained bilaterally from the basal ganglia (lentiform nucleus, caudate) and thalamus. The maximum rates of finger and foot tap and lip and tongue movements were obtained to assess extrapyramidal and pyramidal tract function. In patients with ALS, relative to controls, the NAA concentration was significantly lower (p<0.02) in the basal ganglia and thalamus, and the Cho concentration was higher (p<0.01) in these structures, except in the caudate (p=0.04). Correspondingly, the NAA/Cho ratio was significantly lower (p<0.01) in these structures, except in the caudate (p=0.03), in patients than in controls. There were mild to strong correlations (r=0.4-0.7) between the metabolites of the basal ganglia and finger tap, foot tap and lip and tongue movement rates. In conclusion, decreased NAA in the basal ganglia and thalamus and increased Cho and decreased NAA/Cho in the lentiform nucleus and thalamus are indicative of neuronal loss or dysfunction and alterations in choline-containing membranes in these structures., (Copyright © 2011 John Wiley & Sons, Ltd.)

There is increasing interest in the use of two-dimensional J-resolved spectroscopic acquisition (multiecho) methods for in vivo proton magnetic resonance spectroscopy due to the improved discrimination of overlapping J-coupled multiplet resonances that is provided. Of particular interest is the potential for discrimination of the overlapping resonances of glutamate and glutamine. In this study, a new time-domain parametric spectral model that makes use of all available data is described for fitting the complete two-dimensional multiecho data, and the performance of this method was compared with fitting of one-dimensional spectra obtained following averaging multiecho data (echo time-averaged) and single-echo time PRESS (Point Resolved Spectroscopy) acquired spectra. These methods were compared using data obtained from a phantom containing typical brain metabolites and a human brain. Results indicate that improved performance and accuracy is obtained for the two-dimensional acquisition and spectral fitting model., (2010 Wiley-Liss, Inc.)

A k-space-time Bayesian statistical reconstruction method (K-Bayes) is proposed for the reconstruction of metabolite images of the brain from proton (1H) magnetic resonance (MR) spectroscopic imaging (MRSI) data. K-Bayes performs full spectral fitting of the data while incorporating structural (anatomical) spatial information through the prior distribution. K-Bayes provides increased spatial resolution over conventional discrete Fourier transform (DFT) based methods by incorporating structural information from higher resolution coregistered and segmented structural MR images. The structural information is incorporated via a Markov random field (MRF) model that allows for differential levels of expected smoothness in metabolite levels within homogeneous tissue regions and across tissue boundaries. By further combining the structural prior model with a k -space-time MRSI signal and noise model (for a specific set of metabolites and based on knowledge from prior spectral simulations of metabolite signals), the impact of artifacts generated by low-resolution sampling is also reduced. The posterior-mode estimates are used to define the metabolite map reconstructions, obtained via a generalized expectation-maximization algorithm. K-Bayes was tested using simulated and real MRSI datasets consisting of sets of k-space-time-series (the recorded free induction decays). The results demonstrated that K-Bayes provided qualitative and quantitative improvement over DFT methods.

Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. In this study, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach (described in detail in Part II: Modeling and Technical Development) combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT.

The reproducibility of serial measurements using a volumetric proton MR Spectroscopic Imaging (MRSI) acquisition implemented at 3 Tesla and with lipid suppression by inversion-recovery has been evaluated. Data were acquired from two subjects at five time points, and processed using fully-automated procedures that included rigid registration between studies. These data were analyzed to determine coefficients of variance (COV) for each metabolite and for metabolite ratio images based on an individual voxel analysis, as well as for average and grey-matter and white-matter values from atlas-defined brain regions. The volumetric MRSI acquisition was found to obtain data of sufficient quality for analysis over 70 +/- 6% of the total brain volume, and spatial distributions of the resultant COV values were found to reflect the known distributions of susceptibility-induced magnetic field inhomogeneity. Median values of the resultant voxel-based COVs were 6.2%, 7.2%, and 9.7% for N-acetylaspartate, creatine, and choline respectively. The corresponding mean values obtained following averaging over lobar-scale brain regions within the cerebrum were 3.5%, 3.7%, and 5.2%. These results indicate that longitudinal volumetric MRSI studies with post-acquisition registration can provide an intra-subject reproducibility for voxel-based analyses that is comparable to previously-reported single-voxel MRS measurements, while additionally enabling increased sensitivity by averaging over larger tissue volumes., (2009 John Wiley & Sons, Ltd.)

Changes in the distribution of the magnetic resonance (MR)-observable brain metabolites N-acetyl aspartate (NAA), total choline (Cho), and total creatine (Cre), following mild-to-moderate closed-head traumatic brain injury (mTBI) were evaluated using volumetric proton MR spectroscopic imaging (MRSI). Studies were carried out during the subacute time period following injury, and associations of metabolite indices with neuropsychological test (NPT) results were evaluated. Twenty-nine subjects with mTBI and Glasgow Coma Scale (GCS) scores of 10-15 were included. Differences in individual metabolite and metabolite ratio distributions relative to those of age-matched control subjects were evaluated, as well as analyses by hemispheric lobes and tissue types. Primary findings included a widespread decrease of NAA and NAA/Cre, and increases of Cho and Cho/NAA, within all lobes of the TBI subject group, and with the largest differences seen in white matter. Examination of the association between all of the metabolite measures and the NPT scores found the strongest negative correlations to occur in the frontal lobe and for Cho/NAA. No significant correlations were found between any of the MRSI or NPT measures and the GCS. These results demonstrate that significant and widespread alterations of brain metabolites occur as a result of mild-to-moderate TBI, and that these measures correlate with measures of cognitive performance.

Purpose: The aim of this study was to evaluate volumetric proton magnetic resonance spectroscopic imaging (MRSI) for localization of epileptogenic foci in neocortical epilepsy., Methods: Twenty-five subjects reporting seizures considered to be of neocortical origin were recruited to take part in a 3-T MR study that included high-resolution structural MRI and a whole-brain MRSI acquisition. Using a fully automated MRSI processing protocol, maps for signal intensity normalized N-acetylaspartate (NAA), creatine, and choline were created, together with the relative volume fraction of grey-matter, white-matter, and CSF within each MRSI voxel. Analyses were performed using visual observation of the metabolite and metabolite ratio maps; voxel-based calculation of differences in these metabolite maps relative to normal controls; comparison of average grey-matter and white-matter metabolite values over each lobar volume; and examination of relative left-right asymmetry factors by brain region., Results: Data from 14 subjects were suitable for inclusion in the analysis. Eight subjects had MRI-visible pathologies that were associated with decreases in NAA/creatine, which extended beyond the volume indicated by the MRI. Five subjects demonstrated no significant metabolic alterations using any of the analysis methods, and one subject had no findings on MRI or MRSI., Conclusions: This proof of principle study supports previous evidence that alterations of MR-detected brain metabolites can be detected in tissue areas affected by neocortical seizure activity, while additionally demonstrating advantages of the volumetric MRSI approach.

For magnetic resonance spectroscopic imaging studies of the brain, it is important to measure the distribution of metabolites in a regionally unbiased way; that is, without restrictions to a priori defined regions of interest. Since magnetic resonance spectroscopic imaging provides measures of multiple metabolites simultaneously at each voxel, there is furthermore great interest in utilizing the multidimensional nature of magnetic resonance spectroscopic imaging for gains in statistical power. Voxelwise multivariate statistical mapping is expected to address both of these issues, but it has not been previously employed for spectroscopic imaging (SI) studies of brain. The aims of this study were to (1) develop and validate multivariate voxel-based statistical mapping for magnetic resonance spectroscopic imaging and (2) demonstrate that multivariate tests can be more powerful than univariate tests in identifying patterns of altered brain metabolism. Specifically, we compared multivariate to univariate tests in identifying known regional patterns in simulated data and regional patterns of metabolite alterations due to amyotrophic lateral sclerosis, a devastating brain disease of the motor neurons., (Copyright (c) 2009 Wiley-Liss, Inc.)

Distributions of proton MR-detected metabolites have been mapped throughout the brain in a group of normal subjects using a volumetric MR spectroscopic imaging (MRSI) acquisition with an interleaved water reference. Data were processed with intensity and spatial normalization to enable voxel-based analysis methods to be applied across a group of subjects. Results demonstrate significant regional, tissue, and gender-dependent variations of brain metabolite concentrations, and variations of these distributions with normal aging. The greatest alteration of metabolites with age was observed for white-matter choline and creatine. An example of the utility of the normative metabolic reference information is then demonstrated for analysis of data acquired from a subject who suffered a traumatic brain injury. This study demonstrates the ability to obtain proton spectra from a wide region of the brain and to apply fully automated processing methods. The resultant data provide a normative reference for subsequent utilization for studies of brain injury and disease.

A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely large data sets because they work on successive subsets of the data. They are comparable in quality to application of fuzzy c-means to all of the data. The clustering algorithms coupled with inhomogeneity correction and smoothing are used to create a framework for automatically segmenting magnetic resonance images of the human brain. The framework is applied to a set of normal human brain volumes acquired from different magnetic resonance scanners using different head coils, acquisition parameters and field strengths. Results are compared to those from two widely used magnetic resonance image segmentation programs, Statistical Parametric Mapping and the FMRIB Software Library (FSL). The results are comparable to FSL while providing significant speed-up and better scalability to larger volumes of data.

Sensitivity limitations of in vivo magnetic resonance spectroscopic imaging (MRSI) require that the extent of spatial-frequency (k-space) sampling be limited, thereby reducing spatial resolution and increasing the effects of Gibbs ringing that is associated with the use of Fourier transform reconstruction. Additional problems occur in the spectral dimension, where quantitation of individual spectral components is made more difficult by the typically low signal-to-noise ratios, variable lineshapes, and baseline distortions, particularly in areas of significant magnetic field inhomogeneity. Given the potential of in vivo MRSI measurements for a number of clinical and biomedical research applications, there is considerable interest in improving the quality of the metabolite image reconstructions. In this report, a reconstruction method is described that makes use of parametric modeling and MRI-derived tissue distribution functions to enhance the MRSI spatial reconstruction. Additional preprocessing steps are also proposed to avoid difficulties associated with image regions containing spectra of inadequate quality, which are commonly present in the in vivo MRSI data.

High-spatial-resolution acquisition (HR) was previously proposed for 3D echo-planar spectroscopic imaging (EPSI) in combination with a high-spatial-resolution water reference EPSI data set to minimize inhomogeneous spectral line broadening, allowing for local frequency shift (B(0) shift) correction in human brain metabolite maps at 1.5 T (Ebel A et al., Magn. Reson. Imaging 21:113-120, 2003). At a higher magnetic field strength, B(0), increased field inhomogeneities typically lead to increased line broadening. Additionally, increased susceptibility variations render shimming of the main magnetic field over the whole head more difficult. This study addressed the question whether local B(0)-shift correction still helps limit line broadening in whole-brain 3D EPSI at higher magnetic fields. The combination of HR and local B(0)-shift correction to limit line broadening was evaluated at 4 T. Similar to the results at 1.5 T, the approach provided a high yield of voxels with good spectral quality for 3D EPSI, resulting in improved brain coverage.

An application that provides a flexible and easy to use interface to the GAMMA spectral simulation package is described that is targeted at investigations using in vivo MR spectroscopic methods. The program makes available a number of widely used spatially localized MRS pulse sequences and NMR parameters for commonly observed tissue metabolites, enabling spectra to be simulated for any pulse sequence parameter and viewed in an integrated display. The application is interfaced with a database for storage of all simulation parameters and results of the simulations. This application provides a convenient method for generating a priori spectral information used in parametric spectral analyses and for visual examination of the effects of difference pulse sequences and parameter settings.

Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained from MRI data can enhance the display of low-resolution metabolite images and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this paper, a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby allowing the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing and analysis methods and enable improved mapping of metabolite distributions in the human brain., (Copyright 2006 John Wiley & Sons, Ltd.)

Complete coverage of the in vivo proton metabolite spectrum, including downfield resonances, requires a spectral bandwidth of approximately 9 ppm. Spectral bandwidth of in vivo echo-planar spectroscopic imaging (EPSI) is primarily limited by gradient strength of the oscillating readout gradient, gradient slew rate, and limits on peripheral nerve stimulation for human subjects. Furthermore, conventional EPSI reconstruction, which utilizes even and odd readout echoes separately, makes use of only half the spectral bandwidth. In order to regain full spectral bandwidth in EPSI, it has previously been suggested to apply an interlaced Fourier transform (iFT), which uses even and odd echoes simultaneously. However, this method has not been thoroughly analyzed regarding its usefulness for in vivo 3D EPSI. In this Note, limitations of the iFT method are discussed and an alternative, cyclic spectral unwrapping, is proposed, which is based on prior knowledge of typical in vivo spectral patterns., (Copyright (c) 2005 Wiley-Liss, Inc.)

A PRESS localization (1)H MRS acquisition sequence with a Carr-Purcell train of refocusing pulses (CP-PRESS) has been implemented using global refocusing "sandwich" pulses. The CP pulse train minimized the effects of J-coupled dephasing in metabolites with strongly coupled, multiplet resonance groups as demonstrated in both phantom data and in vivo single-voxel spectroscopy in normal volunteers. Metabolites with multiplet resonance patterns were maintained with greater signal to noise and a simpler resonance pattern at long echo times. T(2) decay times for metabolites with singlet and multiplet resonances were similar to published values, except for the NAA multiplet at 2.5 ppm, which had a significantly shorter T(2) value (147 ms) than that typically reported for the singlet at 2.01 ppm. Metabolite-nulled spectra were acquired in normal volunteers to evaluate the effects of CP-PRESS on baseline signal contributions from residual water, lipids, and macromolecules. The T(2) decay times in four baseline regions in data acquired with the CP-PRESS sequence showed longer decays than corresponding regions in metabolite-nulled spectra from a standard PRESS sequence, but were significantly diminished long before the metabolites of interest were gone. The spectral analysis for spectra with longer TE times also showed less variability due the higher metabolite SNR, simpler spectral patterns, and the decreased baseline contributions.

Numerical simulations of NMR spectra can provide a rapid and convenient method for optimizing acquisition sequence parameters and generating prior spectral information required for parametric spectral analysis. For spatially resolved spectroscopy, spatially dependent variables affect the resultant spectral amplitudes and phases, which must therefore be taken into account in any spectral simulation model. In this study, methods for numerical simulation of spectra obtained using the PRESS localization pulse sequence are examined. A comparison is made between three different simulation models that include different levels of detail regarding the spatial distributions of the excitation functions, and spin evolution during application of the pulses. These methods were evaluated for measurement of spectra from J-coupled spin systems that are of interest for in vivo proton spectroscopy and results compared with experimental data. It is demonstrated that for optimized refocusing pulses it is sufficient to account for chemical shift effects only, although there is some advantage to implementing a more general numerical simulation approach that includes information on RF pulse excitation profiles, which provides sufficient accuracy while maintaining moderate computational requirements and flexibility to handle different spin systems.

Spectral quality in 1H magnetic resonance spectroscopic imaging (MRSI) critically depends on the stability of the main magnetic field. For echo-planar MRSI implemented at 3 T, temperature variation in the passive steel shims of the magnet system can lead to a significant drift in the resonance frequency. A method is presented that incorporates interleaved measurement of the instantaneous resonance frequency of a reference water signal into a volumetric MRSI sequence and allows correction for the drift during postprocessing. Results from normal human brain at 3 T indicate that the correction largely removes lineshape distortions, recovers metabolite signal loss, and improves spectral quality by reducing the width of spectral lines; however, particularly in inferior regions, other sources of distortion may be present that cause broadening of spectral lines.

Analysis of in vivo short TE 1H spectra is complicated by broad baseline signal contributions and resonance line-shape distortions. Although the assumptions of ideal metabolite resonance line-shapes and slowly varying baseline signals can be used to separate these signals, the presence of broad or asymmetric line-shapes can invalidate this model. More complex line-shape models are computationally expensive or difficult to constrain, particularly for the low signal-to-noise commonly found for in vivo MR spectroscopic imaging applications. In this study, two time-domain models for fitting variable spectral line-shapes are examined, one using B-splines and another using summed sinusoids. The methods were verified using both phantom and human data, and Monte Carlo simulations were used to evaluate variations in calculated metabolite amplitudes due to interactions between the baseline and line-shape estimations. Additional studies investigated the use of prior line-shape information, obtained from either a water MRSI measurement or calculations from B(0) maps, to determine parameter starting values or optimization constraints. Both line-shape models showed the ability to fit the variety of line-shapes present in both the phantom and human MRSI data, with similar or improved accuracy over a Gaussian line-shape model; however, this improvement resulted in only minor improvement for the high-SNR phantom data and moderate improvements in regions with asymmetry for the fitted in vivo metabolite images. The use of prior line-shape information was of most benefit when applied toward setting optimization constraints but was of limited benefit when used to define initial starting values., ((c) 2004 Wiley-Liss, Inc.)

Background and Purpose: Poor clinical outcomes without notable neuroimaging findings after mild traumatic brain injury (MTBI) suggest diffuse tissue damage and altered metabolism not observable with conventional MR imaging and CT. In this study, MTBI-associated metabolic changes were assessed over the entire brain by using volumetric proton MR spectroscopic imaging (MRSI) and the findings related to injury and outcome assessments., Methods: Fourteen subjects with mild closed head injury (Glasgow Coma Scale [GCS] scores of 13-15) underwent structural MR imaging and proton MRSI at 1.5 T within 1 month of injury. Distributions of N-acetylaspartate (NAA), total creatine (Cr), and total choline (Cho) were mapped over a wide region of the brain, and metabolite ratios were calculated for 25 regions without MR imaging abnormalities. Results were compared with data from 13 control subjects., Results: Significant changes (P <.05) were found for some, but not all, brain regions for the average values from all MTBI subjects, with reduced NAA/Cr, increased Cho/Cr, and reduced NAA/Cho. Global NAA/Cho obtained from the sum of all sampled regions in two subjects was significantly reduced. Metabolite ratios were not significantly correlated with GCS score at admission or Glasgow Outcome Scale (GOS) score at 6 months after injury, although they were weakly correlated with GOS score at discharge., Conclusion: These results show evidence of widespread metabolic changes following MTBI in regions that appear normal on diagnostic MR images. Although the association with injury assessment and outcome is weak, this preliminary study demonstrates the applicability of volumetric proton MRSI for evaluating diffuse injury associated with MTBI.

A new method, based on a deformable shape-intensity model (DSM), was developed to improve the signal-to-noise ratio (SNR) of multidimensional magnetic resonance spectroscopic imaging (MRSI) data sets without affecting spectral lineshapes and linewidths. Improvements with DSM, compared to digital filters using conventional signal apodization, were demonstrated on both simulated and experimental in vivo (1)H MRS images from 22 cognitively normal (CN) elderly subjects and 25 patients with Alzheimer's disease (AD). Simulated MRSI data showed that DSM achieved superior noise suppression compared to a matched apodization filter. Experimental MRSI data showed that SNR could be increased 2.1-fold with DSM without distorting spectral resolution, thus maintaining all spectral features of the raw, unfiltered data. In conclusion, DSM should be used to achieve high SNR in reconstructing MRSI data., (Copyright 2003 Wiley-Liss, Inc.)

Purpose: In follow-up examinations of irradiated brain metastases conventional contrast-enhanced morphological MR imaging is often unable to distinguish between transient radiation effects, radionecrosis,and tumor recurrence. To evaluate changes of relative cerebral blood flow (rCBF) in irradiated brain metastases arterial spin-labeling techniques (ASL) were applied and compared to the outcome of (1)H MR spectroscopy and spectroscopic imaging ((1)H MRS, SI)., Patients and Methods: In 2 patients follow-up examinations of irradiated brain metastases were performed on a 1.5-T tomograph (average single dose: 20 Gy/80% isodose). Relative CBF values of gray matter (GM), white matter (WM),and metastases (Met) were measured by means of the ASL techniques ITS-FAIR and Q2TIPS. (1)H MRS was performed with PRESS 1500/135., Results: In both patients with initially hyperperfused metastases (Met/GM >1) the reduction of rCBF after stereotactic radiosurgery indicated response to treatment--even if the contrast-enhancing region increased--while increasing rCBF values indicated tumor progression. The findings were confirmed by (1)H MRS, SI and subsequent follow-up., Conclusion: The ASL techniques ITS-FAIR and Q2TIPS are able to monitor changes of rCBF in irradiated brain metastases. The two cases imply a possible role for ASL-MR perfusion imaging and (1)H MR spectroscopy in differentiating radiation effects from tumor progression.

To reduce contamination from subcutaneous lipid regions in MR spectroscopic imaging (MRSI) of whole brain, lipid signals are often suppressed using T(1) nulling methods. If a range of lipid T(1) values is present, the suppression efficiency will be improved using multiple inversion recovery (MIR) preparation. This study compared single IR (SIR) and double IR (DIR) applied with a volumetric MRSI sequence at 1.5 T based on experimental measurement of lipid T(1) and T(2) relaxation rates. At short and medium echo times (TEs), an approximately 28-47% improvement in lipid suppression was achieved with DIR compared to SIR. However, it also led to a loss of 37-43% in signal-to-noise ratio (SNR) for metabolites. Thus, SIR appears to be the better choice for suppressing lipid signals and maintaining metabolite sensitivity., (Copyright 2003 Wiley-Liss, Inc.)

Spectral quality in (1)H MR spectroscopic imaging (MRSI) of the brain is often significantly degraded in regions subject to local magnetic susceptibility variations, which results in broadened and distorted spectral lineshapes. In this report, a modified acquisition strategy for volumetric echo-planar spectroscopic imaging (3D EPSI) is presented that extends the region of the brain that can be observed. The data are sampled at higher spatial resolution, then corrected for local B(0) shifts and reconstructed such that the final spatial resolution matches that of 3D EPSI data acquired with the conventional lower spatial resolution. Comparison of in vivo data obtained at 1.5 T with these two acquisition schemes shows that the high spatial resolution acquisition provides considerable reduction of spectral linewidths in many problematic brain regions, though with a reduction in signal-to-noise ratio by a factor of approximately 1.4 to 1.6 for the matrix sizes used in this study. However, the effect of the increased noise was largely offset by the improved spectral quality, leading to an overall improvement of the metabolite image quality obtained using automated spectral analysis.

Background and Purpose: Extensive metabolic impairments have been reported in association with mesial temporal lobe epilepsy (mTLE). We investigated whether proton MR spectroscopy ((1)H-MRS) depicts metabolic changes beyond the hippocampus in cases of mTLE and whether these changes help lateralize the seizure focus., Methods: MR imaging and (1)H-MRS were performed in 15 patients with mTLE with a postoperative diagnosis of mesial temporal sclerosis and in 12 control volunteers. Point-resolved spectroscopy and multisection (1)H-MRS measured N-acetylaspartate (NAA), creatine (Cr), and choline (Cho) in the hippocampus, temporal opercular and lateral cortices, insula and cerebellum, and frontal, parietal, and occipital lobes. Metabolites were assessed as ratios to Cr and in absolute units., Results: Twelve patients had ipsilateral hippocampal atrophy; three had negative imaging results. In the ipsilateral hippocampus, absolute NAA (/NAA/) was 27.3% lower in patients compared with that in control volunteers (P <.001) and 18.5% lower compared with that in the contralateral side (P <.01). /NAA/ averaged over selected regions in the ipsilateral temporal lobes of patients with mTLE was 19.3% lower compared with the mean in the control group (P <.0001) and by 17.7% lower compared with the contralateral values (P <.00001). Using only hippocampal data, 60% of the cases of mTLE were correctly lateralized. Lateralization, determined using whole temporal lobe data, had 87% sensitivity and 92% specificity. /NAA/ was bilaterally reduced in the frontal, parietal, and occipital lobes of patients with mTLE compared with that in control volunteers (P <.01)., Conclusion: Multisection (1)H-MRS depicts interictal reductions of NAA in the ipsilateral temporal lobe beyond the hippocampus and accurately lateralizes seizure foci.

Objective: To determine 1) the reproducibility of metabolite measurements by (1)H MRS in the motor cortex; 2) the extent to which (1)H MRS imaging (MRSI) detects abnormal concentrations of N-acetylaspartate (NAA)-, choline (Cho)-, and creatine (Cre)-containing compounds in early stages of ALS; and 3) the metabolite changes over time in ALS., Methods: Sixteen patients with definite or probable ALS, 12 with possible or suspected ALS, and 12 healthy controls underwent structural MRI and multislice (1)H MRSI. (1)H MRSI data were coregistered with tissue-segmented MRI data to obtain concentrations of NAA, Cre, and Cho in the left and right motor cortex and in gray matter and white matter of nonmotor regions in the brain., Results: The interclass correlation coefficient of NAA was 0.53 in the motor cortex tissue and 0.83 in nonmotor cortex tissue. When cross-sectional data for patients were compared with those for controls, the NAA/(Cre + Cho) ratio in the motor cortex region was significantly reduced, primarily due to increases in Cre and Cho and a decrease in NAA concentrations. A similar, although not significant, trend of increased Cho and Cre and reduced NAA levels was also observed for patients with possible or suspected ALS. Furthermore, in longitudinal studies, decreases in NAA, Cre, and Cho concentrations were detected in motor cortex but not in nonmotor regions in ALS., Conclusion: Metabolite changes measured by (1)H MRSI may provide a surrogate marker of ALS that can aid detection of early disease and monitor progression and treatment response.

The inter- and intrasubject reproducibility of the metabolite levels of N-acetylaspartate (NAA), creatine (Cr), and choline (Cho), obtained with three-dimensional (3D) multivoxel proton spectroscopy (1H-MRS), was analyzed in eight healthy volunteers. Serial, back-to-back measurements on a phantom showed the methodology and instrumentation to be highly reproducible, with a median coefficient of variation (CV) of 3.8%. In the human brain, the metabolite levels' variability was larger, with intrasubject median CVs for a total of 1876 signal voxels of 13.8%, 18.5%, and 20.1% for NAA, Cr, and Cho, respectively. These variations possibly arise from small, unavoidable, +/-1-2 mm volume-of-interest (VOI) repositioning uncertainties, which vary each 0.75-cm(3) voxel's partial fluid/gray/white-matter fractions. Comparing the CVs between eight subjects in a total of 324 selected voxels gave total interindividual CVs of 15.6%, 23.3%, and 24.4%, compared with intraindividual CVs in the same voxels of 14.4%, 14.8%, and 15.3%, for NAA, Cr, and Cho, respectively. Replacing the signal(s) from each voxel by the average of itself with its six canonical neighbors reduces the intrasubject median CVs to 8.3%, 9.5%, and 9.7%. The measurement uncertainties can be reduced at a cost of either spatial resolution (by using larger voxels) or time (by performing serial follow-ups)., (Copyright 2002 Wiley-Liss, Inc.)

For many clinical applications of proton MR spectroscopic imaging (MRSI) of the brain, diagnostic assessment is limited by insufficient coverage provided by single- or multislice acquisition methods as well as by the use of volume preselection methods. Additionally, traditional spectral analysis methods may limit the operator to detailed analysis of only a few selected brain regions. It is therefore highly desirable to use a fully 3D approach, combined with spectral analysis procedures that enable automated assessment of 3D metabolite distributions over the whole brain. In this study, a 3D echo-planar MRSI technique has been implemented without volume preselection to provide sufficient spatial resolution with maximum coverage of the brain. Using MRSI acquisitions in normal subjects at 1.5T and a fully automated spectral analysis procedure, an assessment of the resultant spectral quality and the extent of viable data in human brain was carried out. The analysis found that 69% of brain voxels were obtained with acceptable spectral quality at TE = 135 ms, and 52% at TE = 25 ms. Most of the rejected voxels were located near the sinuses or temporal bones and demonstrated poor B0 homogeneity and additional regions were affected by stronger lipid contamination at TE = 25 ms., (Copyright 2001 Wiley-Liss, Inc.)

Multislice proton magnetic resonance spectroscopic imaging (1H MRSI) at 25 ms echo time was used to measure concentrations of myo-inositol (mI), N-acetylaspartate (NAA), and creatine (Cr) and choline (Cho) in ten normal subjects between 22 and 84 years of age (mean age 44 +/- 18 years). By co-analysis with MRI based tissue segmentation results, metabolite distributions were analyzed for each tissue type and for different brain regions. Measurement reliability was evaluated using intraclass correlation coefficients (ICC). Significant differences in metabolite distributions were found for all metabolites. mI of frontal gray matter was 84% of parietal gray matter and 87% of white matter. NAA of frontal gray matter was 86% of parietal gray matter and 85% of white matter. Cho of frontal gray matter was 125% of parietal gray matter and 59% of white matter and Cho of parietal gray matter was 47% of white matter. Cr of parietal gray matter was 113% of white matter. Reliability was relatively high (ICC from.70 to.93) for all metabolites in white matter and for NAA and Cr in gray matter, though limited (ICC less than.63) for mI and Cho in gray matter. These findings indicate that voxel gray/white matter contributions, regional variations in metabolite concentrations, and reliability limitations must be considered when interpreting 1H MR spectra of the brain.