Comprehensive processing, display and analysis for in vivo MR spectroscopic imaging

Use of high-resolution volumetric MR spectroscopic imaging in assessing treatment response of glioblastoma to an HDAC inhibitor

OBJECTIVE

Improved predictive imaging would enable personalization and adjustment of treatment, which are critical for patients with glioblastomain whom therapy is likely to fail. This article describes the use of MR spectroscopic imaging (MRSI) to predict early clinical and behavioral response to a therapy and an effort to develop high-resolution, volumetric MRSI to improve its clinical application.

CONCLUSION

MRSI may enable quantitative analysis of brain tumor response, offering a precise tool for monitoring of patients in clinical trials.

Volumetric spectroscopic imaging of glioblastoma multiforme radiation treatment volumes

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.

Prebiopsy multiparametric 3T prostate MRI in patients with elevated PSA, normal digital rectal examination, and no previous biopsy

PURPOSE

To find the diagnostic accuracy of 3T multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted transrectal ultrasound (TRUS)-guided biopsy using visual coregistration (TB) in patients with elevated prostate-specific antigen (PSA), normal digital rectal examination, and no previous biopsy.

MATERIALS AND METHODS

Fifty-five patients at two institutions underwent mpMRI, consisting of anatomical T2 -weighted imaging (T2 W), diffusion-weighted imaging (DWI), proton magnetic resonance spectroscopy ((1) H-MRS), and dynamic contrast-enhanced MRI (DCE-MRI), followed by TB in addition to 12 core systematic TRUS-guided biopsy (SB). Histopathological scorings of biopsy (n = 38) and prostatectomy (n = 17) specimens were used as the reference standard for calculation of diagnostic accuracy values. Clinically significant prostate cancer (SPCa) was defined as 3 mm core length of Gleason score 3+3 or any Gleason grade 4.

RESULTS

The sensitivity, specificity, accuracy, and area under the curve (AUC) values for the detection of SPCa on the sextant level for T2 W+DWI+(1) H-MRS+DCE-MRI were 72%, 89%, 85%, and 0.81, respectively. The corresponding values for T2 wi+DWI were 61%, 96%, 87%, and 0.79, respectively. The overall PCa detection rate per core in 53 patients was 21% (138 of 648 cores) for SB and 43% (33 of 77 cores) for TB (P < 0.001).

CONCLUSION

Prebiopsy mpMRI is an accurate tool for PCa detection and biopsy targeting in patients with elevated PSA.

Fast water concentration mapping to normalize (1)H MR spectroscopic imaging

OBJECT

To propose a fast and robust acquisition and post-processing pipeline that is time-compatible with clinical explorations to obtain a proton density (ρ) map used as a reference for metabolic map normalization. This allows inter-subject and inter-group comparisons of magnetic resonance spectroscopic imaging (MRSI) data and longitudinal follow-up for single subjects.

MATERIALS AND METHODS

A multi-echo T 2 (*) mapping sequence, the XEP sequence for B 1 (+) -mapping and Driven Equilibrium Single Pulse Observation of T 1-an optimized variable flip angle method for T 1 mapping used for both B 1 (-) -mapping and M 0 calculation-were used to determine correction factors leading to quantitative water proton density maps at 3T. Normalized metabolite maps were obtained on a phantom and nine healthy volunteers. To show the potential use of this technique at the individual level, we also explored one patient with low-grade glioma.

RESULTS

Accurate ρ maps were obtained both on phantom and volunteers. After signal normalization with the generated ρ maps, metabolic concentrations determined by the present method differed from theory by <7 % in the phantom and were in agreement with data from the literature for the healthy controls. Using these normalized metabolic values, it was possible to demonstrate in the patient with brain glioma, metabolic abnormalities in normalized N-acetyl aspartate, choline and creatine levels; illustrating the potential for direct use of this technique in clinical studies.

CONCLUSION

The proposed combination of sequences provides a robust ρ map that can be used to normalize metabolic maps in clinical MRSI studies.

Reproducibility and reliability of short-TE whole-brain MR spectroscopic imaging of human brain at 3T

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.

Magnetic resonance spectroscopy investigations of functionally defined language areas in schizophrenia patients with and without auditory hallucinations

BACKGROUND

Cerebral dysfunction occurring in mental disorders can show metabolic disturbances which are limited to circumscribed brain areas. Auditory hallucinations have been shown to be related to defined cortical areas linked to specific language functions. Here, we investigated if the study of metabolic changes in auditory hallucinations requires a functional rather than an anatomical definition of their location and size to allow a reliable investigation by magnetic resonance spectroscopy (MRS).

METHODS

Schizophrenia patients with (AH; n=12) and without hallucinations (NH; n=8) and healthy controls (HC; n=11) underwent a verbal fluency task in functional MRI (fMRI) to functionally define Broca's and Wernicke's areas. Left and right Heschl's gyri were defined anatomically.

RESULTS

The mean distances in native space between the fMRI-defined regions and a corresponding anatomically defined area were 12.4±6.1 mm (range: 2.7-36.1 mm) for Broca's area and 16.8±6.2 mm (range: 4.5-26.4 mm) for Wernicke's area, respectively. Hence, the spatial variance was of similar extent as the size of the investigated regions. Splitting the investigations into a single voxel examination in the frontal brain and a spectroscopic imaging part for the more homogeneous field areas led to good spectral quality for almost all spectra. In Broca's area, there was a significant group effect (p=0.03) with lower levels of N-acetyl-aspartate (NAA) in NH compared to HC (p=0.02). There were positive associations of NAA levels in the left Heschl's gyrus with total (p=0.03) and negative (p=0.006) PANSS scores. In Broca's area, there was a negative association of myo-inositol levels with total PANSS scores (p=0.008).

CONCLUSION

This study supports the neurodegenerative hypothesis of schizophrenia only in a frontal region whereas the results obtained from temporal regions are in contrast to the majority of previous studies. Future research should test the hypothesis raised by this study that a functional definition of language regions is needed if neurochemical imbalances are expected to be restricted to functional foci.

Comparison of sagittal and transverse echo planar spectroscopic imaging on the quantification of brain metabolites

PURPOSE

We quantitatively compared sagittal and transverse echo planar spectroscopic imaging (EPSI) on the quantification of metabolite concentrations with consideration of tissue variation. A quantification strategy is proposed to collect the necessary information for quantification of concentrations in a minimized acquisition time.

METHODS

Six transverse and six sagittal EPSI data were collected on healthy volunteers. Metabolite concentrations of N-acetyl-aspartate (NAA), total creatine (tCr), total choline (tCho), myo-inositol (mI), and glutamate and glutamine complex (Glx) were quantified using water scaling with partial volume and relaxation correction. Linear regression analysis was performed to extract concentrations in gray matter (GM) and white matter (WM). The inter- and intrasubject coefficients of variance (CV) were estimated.

RESULTS

Concentrations and fitting errors of sagittal and transverse EPSI were at same level. GM to WM contrast of concentrations was found in NAA, tCr, and tCho. The intersubject CVs revealed greater variability in the sagittal EPSI than in the transverse EPSI. The intrasubject CVs of the transverse EPSI were below 5% for NAA, tCr, and tCho.

CONCLUSION

We showed that quantified concentrations of sagittal and transverse EPSI after partial volume correction are comparable and reproducible. The proposed quantification strategy can be conveniently adapted into various MRI protocols.

Peak-specific phase correction for automated spectrum processing of in vivo magnetic resonance spectroscopic imaging by using the multiscale approach

Automatic metabolite quantification with curve fitting is essential in analyzing large amount of in vivo magnetic resonance spectroscopic imaging (MRSI) data. However, such data analysis is usually hindered by distorted metabolite peaks and baselines normally seen in in vivo MRS. In the present study, a multiscale approach was utilized for peak-specific automatic phase correction in multi-slice MRSI data of human brain. The results suggest that this novel approach can improve the robustness and efficiency of metabolite quantification and facilitate automatic analysis of multi-slice in vivo MRSI data in human brain.

Ligand-based molecular MRI: O-17 JJVCPE amyloid imaging in transgenic mice

BACKGROUND

Development of molecular MR imaging (MRI) similar to PET imaging using contrast agents such as gadolinium as probe have been inherently hampered by incompatibility between potential probe (charged molecules) and membrane permeability. Nevertheless, considering the inherent spatial resolution limit for PET of 700μ, the superior microscopic resolution of MRI of 4 μ presents a strong incentive for research into ligand-based molecular MRI.

METHODS

¹⁷O exhibits JJ vicinal coupling with a covalently bound proton in a hydroxyl group. This ¹⁷O coupled proton can be ionized in water solution and interexchange with other water protons. This property can be utilized as “probe” in T2-weighted imaging and developed into ligand-based molecular MRI. We examined β-amyloid distribution in human APP overexpressed transgenic mice in vivo following injection of ¹⁷O labeled Pittsburg compound B (¹⁷O-PiB).

RESULTS

JJVCPE imaging successfully imaged ¹⁷O-PiB, unequivocally establishing that ¹⁷O JJVCPE imaging can be developed into PET-like molecular MRI in clinical medicine.

CONCLUSIONS

The study represents the first successful ligand-based molecular MRI in vivo. This is also the first in vivo amyloid imaging using MRI. High-resolution molecular MRI with high specificity under clinical settings, such as in vivo microscopic imaging of senile plaque, is a foreseeable aim.

Mapping of glycine distributions in gliomas

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.

High-resolution echo-planar spectroscopic imaging of the human calf

Background

This study exploits the speed benefits of echo-planar spectroscopic imaging (EPSI) to acquire lipid spectra of skeletal muscle. The main purpose was to develop a high-resolution EPSI technique for clinical MR scanner, to visualise the bulk magnetic susceptibility (BMS) shifts of extra-myocellular lipid (EMCL) spectral lines, and to investigate the feasibility of this method for the assessment of intra-myocellular (IMCL) lipids.

Methods

The study group consisted of six healthy volunteers. A two dimensional EPSI sequence with point-resolved spectroscopy (PRESS) spatial localization was implemented on a 3T clinical MR scanner. Measurements were performed by means of 64×64 spatial matrix and nominal voxel size 3×3×15 mm³. The total net measurement time was 3 min 12 sec for non-water-suppressed (1 acquisition) and 12 min 48 sec for water-suppressed scans (4 acquisitions).

Results

Spectra of the human calf had a very good signal-to-noise ratio and linewidths sufficient to differentiate IMCL resonances from EMCL. The use of a large spatial matrix reduces inter-voxel signal contamination of the strong EMCL signals. Small voxels enabled visualisation of the methylene EMCL spectral line splitting and their BMS shifts up to 0.5 ppm relative to the correspondent IMCL line. The mean soleus muscle IMCL content of our six volunteers was 0.30±0.10 vol% (range 0.18–0.46) or 3.6±1.2 mmol/kg wet weight (range: 2.1–5.4).

Conclusion

This study demonstrates that high-spatial resolution PRESS EPSI of the muscle lipids is feasible on standard clinical scanners.

Association of metabolite concentrations and water diffusivity in normal appearing brain tissue with glioma grade

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.

jSIPRO - analysis tool for magnetic resonance spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) involves a huge number of spectra to be processed and analyzed. Several tools enabling MRSI data processing have been developed and widely used. However, the processing programs primarily focus on sophisticated spectra processing and offer limited support for the analysis of the calculated spectroscopic maps. In this paper the jSIPRO (java Spectroscopic Imaging PROcessing) program is presented, which is a java-based graphical interface enabling post-processing, viewing, analysis and result reporting of MRSI data. Interactive graphical processing as well as protocol controlled batch processing are available in jSIPRO. jSIPRO does not contain a built-in fitting program. Instead, it makes use of fitting programs from third parties and manages the data flows. Currently, automatic spectra processing using LCModel, TARQUIN and jMRUI programs are supported. Concentration and error values, fitted spectra, metabolite images and various parametric maps can be viewed for each calculated dataset. Metabolite images can be exported in the DICOM format either for archiving purposes or for the use in neurosurgery navigation systems.

Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate

The investigation of metabolic pathways disturbed in isocitrate dehydrogenase (IDH) mutant tumors revealed that the hallmark metabolic alteration is the production of D-2-hydroxyglutarate (D-2HG). The biological impact of D-2HG strongly suggests that high levels of this metabolite may play a central role in propagating downstream the effects of mutant IDH, leading to malignant transformation of cells. Hence, D-2HG may be an ideal biomarker for both diagnosing and monitoring treatment response targeting IDH mutations. Magnetic resonance spectroscopy (MRS) is well suited to the task of noninvasive D-2HG detection, and there has been much interest in developing such methods. Here, we review recent efforts to translate methodology using MRS to reliably measure in vivo D-2HG into clinical research.

High-field MRS in clinical drug development

INTRODUCTION

Magnetic resonance spectroscopy (MRS) will continue to play an ever increasing role in drug discovery because MRS does readily define biomarkers for several hundreds of clinically distinct diseases. Published evidence based medicine (EBM) surveys, which generally conclude the opposite, are seriously flawed and do a disservice to the field of drug discovery.

AREAS COVERED

This article presents MRS and how it has guided several hundreds of practical human 'drug discovery' endeavors since its development. Specifically, the author looks at the process of 'reverse-translation' and its influence in the expansion of the number of preclinical drug discoveries from in vivo MRS. The author also provides a structured approach of eight criteria, including EBM acceptance, which could potentially re-open the field of MRS for productive exploration of existing and repurposed drugs and cost-effective drug-discovery.

EXPERT OPINION

MRS-guided drug discovery is poised for future expansion. The cost of clinical trials has escalated and the use of biomarkers has become increasingly useful in improving patient selection for drug trials. Clinical MRS has uncovered a treasure-trove of novel biomarkers and clinical MRS itself has become better standardized and more widely available on 'routine' clinical MRI scanners. When combined with available new MRI sequences, MRS can provide a 'one stop shop' with multiple potential outcome measures for the disease and the drug in question.

Spin-echo magnetic resonance spectroscopic imaging at 7 T with frequency-modulated refocusing pulses

Two approaches to high-resolution SENSE-encoded magnetic resonance spectroscopic imaging (MRSI) of the human brain at 7 Tesla (T) with whole-slice coverage are described. Both sequences use high-bandwidth radiofrequency pulses to reduce chemical shift displacement artifacts, SENSE-encoding to reduce scan time, and dual-band water and lipid suppression optimized for 7 T. Simultaneous B0 and transmit B1 mapping was also used for both sequences to optimize field homogeneity using high-order shimming and determine optimum radiofrequency transmit level, respectively. One sequence ("Hahn-MRSI") used reduced flip angle (90°) refocusing pulses for lower radiofrequency power deposition, while the other sequence used adiabatic fast passage refocusing pulses for improved sensitivity and reduced signal dependence on the transmit-B1 level. In four normal subjects, adiabatic fast passage-MRSI showed a signal-to-noise ratio improvement of 3.2±0.5 compared to Hahn-MRSI at the same spatial resolution, pulse repetition time, echo time, and SENSE-acceleration factor. An interleaved two-slice Hahn-MRSI sequence is also demonstrated to be experimentally feasible.

Utility of multiparametric 3-T MRI for glioma characterization

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.

Impact of reduced k-space acquisition on pathologic detectability for volumetric MR spectroscopic imaging

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.

Whole-brain magnetic resonance spectroscopic imaging measures are related to disability in ALS

OBJECTIVE

To demonstrate the sensitivity of a recently developed whole-brain magnetic resonance spectroscopic imaging (MRSI) sequence to cerebral pathology and disability in amyotrophic lateral sclerosis (ALS), and compare with measures derived from diffusion tensor imaging.

METHODS

Whole-brain MRSI and diffusion tensor imaging were undertaken in 13 patients and 14 age-similar healthy controls. Mean N-acetylaspartate (NAA), fractional anisotropy, and mean diffusivity were extracted from the corticospinal tract, compared between groups, and then in relation to disability in the patient group.

RESULTS

Significant reductions in NAA were found along the course of the corticospinal tracts on whole-brain MRSI. There were also significant changes in fractional anisotropy (decreased) and mean diffusivity (increased) in the patient group, but only NAA showed a significant relationship with disability (r = 0.65, p = 0.01).

CONCLUSION

Whole-brain MRSI has potential as a quantifiable neuroimaging marker of disability in ALS. It offers renewed hope for a neuroimaging outcome measure with the potential for harmonization across multiple sites in the context of a therapeutic trial.

Whole-brain analysis of amyotrophic lateral sclerosis by using echo-planar spectroscopic imaging

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.

Whole-brain proton MR spectroscopic imaging in Parkinson's disease

BACKGROUND AND PURPOSE

To examine the distributions of proton magnetic resonance spectroscopy (MRS) observed metabolites in Parkinson's disease (PD) throughout the whole brain.

METHODS

Twelve PD patients and 18 age-matched controls were studied using neuropsychological testing, MRI and volumetric MR spectroscopic imaging. Average values of signal normalized metabolite values for N-acetyl-aspartate, total-creatine, and total-choline (NAA, total-Cre, total-Cho, respectively) and their ratios were calculated for gray matter (GM) and white matter (WM) in each lobar brain region.

RESULTS

Analyses revealed altered metabolite values in PD subjects relative to controls within the GM of the temporal lobe (right: elevated Cre, P = .027; decreased NAA/Cre, P = .019; decreased Cho/Cre, P = .001 and left: decreased NAA/Cre; P = .001, decreased Cho/Cre, P = .007); the right occipital lobe (decreased NAA, P = .032 and NAA/Cre, P = .016); and the total cerebrum GM (decreased NAA/Cre, P = .029). No meaningful correlations were obtained between abnormal metabolite values and the neuropsychological measures.

CONCLUSIONS

PD is associated with widespread alterations of brain metabolite concentrations, with a primary finding of increased creatine. Higher creatine values in our PD sample may reflect greater neuronal energy expenditure early in the disease process that is compensatory. This is the first whole brain MRS study of PD that has examined metabolite changes across a large fraction of the brain volume, including the cortical mantle.

Frontal lobe abnormalities on MRS correlate with poor letter fluency in ALS

OBJECTIVE

To examine whether frontal lobe abnormalities on magnetic resonance spectroscopy (MRS) in amyotrophic lateral sclerosis (ALS) correlate with poor letter fluency (LF).

METHODS

Twenty-five patients with ALS (20 with definite, probable, or possible ALS and 5 with progressive muscular atrophy) performed an LF task, involving F word generation in 1 minute, and underwent MRS. Comparisons were made between patients with ALS with impaired LF and unimpaired LF based on an empirically derived cutoff score. A Spearman correlation was performed between the patient's N-acetyl acetate/creatinine-phosphocreatinine ratio (NAA/Cr) and the number of F words generated.

RESULTS

LF was impaired in 50% of patients with ALS. Patients with impaired LF had reduced NAA/Cr in the DLPFC compared with those with unimpaired LF (p = 0.007). There was a significant correlation between LF and NAA/Cr in the DLPFC (r = 0.51, p = 0.0009). The ALS Functional Rating Scale score, clinical region of motor onset, and disease category had no effect on LF or NAA/Cr in the DLPFC.

CONCLUSIONS

A reduced NAA/Cr in the DLPFC of patients with ALS is a marker of neuronal dysfunction and correlates with impaired performance on a clinical measure of executive function.

Comprehensive evaluation of corticospinal tract metabolites in amyotrophic lateral sclerosis using whole-brain 1H MR spectroscopy

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.

Associations of age, gender and body mass with 1H MR-observed brain metabolites and tissue distributions

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.

Emerging imaging tools for use with traumatic brain injury research

This article identifies emerging neuroimaging measures considered by the inter-agency Pediatric Traumatic Brain Injury (TBI) Neuroimaging Workgroup. This article attempts to address some of the potential uses of more advanced forms of imaging in TBI as well as highlight some of the current considerations and unresolved challenges of using them. We summarize emerging elements likely to gain more widespread use in the coming years, because of 1) their utility in diagnosis, prognosis, and understanding the natural course of degeneration or recovery following TBI, and potential for evaluating treatment strategies; 2) the ability of many centers to acquire these data with scanners and equipment that are readily available in existing clinical and research settings; and 3) advances in software that provide more automated, readily available, and cost-effective analysis methods for large scale data image analysis. These include multi-slice CT, volumetric MRI analysis, susceptibility-weighted imaging (SWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), arterial spin tag labeling (ASL), functional MRI (fMRI), including resting state and connectivity MRI, MR spectroscopy (MRS), and hyperpolarization scanning. However, we also include brief introductions to other specialized forms of advanced imaging that currently do require specialized equipment, for example, single photon emission computed tomography (SPECT), positron emission tomography (PET), encephalography (EEG), and magnetoencephalography (MEG)/magnetic source imaging (MSI). Finally, we identify some of the challenges that users of the emerging imaging CDEs may wish to consider, including quality control, performing multi-site and longitudinal imaging studies, and MR scanning in infants and children.

1H MRS of basal ganglia and thalamus in amyotrophic lateral sclerosis

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.

Anterior cingulate cortex γ-aminobutyric acid in depressed adolescents: relationship to anhedonia

CONTEXT

Anhedonia, a core symptom of major depressive disorder (MDD) and highly variable among adolescents with MDD, may involve alterations in the major inhibitory amino acid neurotransmitter system of γ-aminobutyric acid (GABA).

OBJECTIVE

To test whether anterior cingulate cortex (ACC) GABA levels, measured by proton magnetic resonance spectroscopy, are decreased in adolescents with MDD. The associations of GABA alterations with the presence and severity of anhedonia were explored.

DESIGN

Case-control, cross-sectional study using single-voxel proton magnetic resonance spectroscopy at 3 T.

SETTING

Two clinical research divisions at 2 teaching hospitals.

PARTICIPANTS

Twenty psychotropic medication-free adolescents with MDD (10 anhedonic, 12 female, aged 12-19 years) with episode duration of 8 weeks or more and 21 control subjects group matched for sex and age.

MAIN OUTCOME MEASURES

Anterior cingulate cortex GABA levels expressed as ratios relative to unsuppressed voxel tissue water (w) and anhedonia scores expressed as a continuous variable.

RESULTS

Compared with control subjects, adolescents with MDD had significantly decreased ACC GABA/w (t = 3.2; P < .003). When subjects with MDD were categorized based on the presence of anhedonia, only anhedonic patients had decreased GABA/w levels compared with control subjects (t = 4.08; P < .001; P(Tukey) < .001). Anterior cingulate cortex GABA/w levels were negatively correlated with anhedonia scores for the whole MDD group (r = -0.50; P = .02), as well as for the entire participant sample including the control subjects (r = -0.54; P < .001). Anterior cingulate cortex white matter was also significantly decreased in adolescents with MDD compared with controls (P = .04).

CONCLUSIONS

These findings suggest that GABA, the major inhibitory neurotransmitter in the brain, may be implicated in adolescent MDD and, more specifically, in those with anhedonia. In addition, use of a continuous rather than categorical scale of anhedonia, as in the present study, may permit greater specificity in evaluating this important clinical feature.

Quantitative proton magnetic resonance spectroscopy and spectroscopic imaging of the brain: a didactic review

This article presents background information related to methodology for estimating brain metabolite concentration from magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging measurements of living human brain tissue. It reviews progress related to this methodology, with emphasis placed on progress reported during the past 10 years. It is written for a target audience composed of radiologists and magnetic resonance imaging technologists. It describes in general terms the relationship between MRS signal amplitude and concentration. It then presents an overview of the many practical problems associated with deriving concentration solely from absolute measured signal amplitudes and demonstrates how a various signal calibration approaches can be successfully used. The concept of integrated signal amplitude is presented with examples that are helpful for qualitative reading of MRS data as well as for understanding the methodology used for quantitative measurements. The problems associated with the accurate measurement of individual signal amplitudes in brain spectra having overlapping signals from other metabolites and overlapping nuisance signals from water and lipid are presented. Current approaches to obtaining accurate amplitude estimates with least-squares fitting software are summarized.

Neuroimaging in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a motor neuron disease characterized by progressive degeneration of upper motor neurons (UMN) and lower motor neurons (LMN). While LMN dysfunction can be confirmed by electromyography (EMG) and muscle biopsy, UMN involvement is more difficult to detect, particularly in the early phase. Objective and sensitive measures of UMN dysfunction are needed for early diagnosis and monitoring of disease progression and therapeutic efficacy. Advanced magnetic resonance imaging (MRI) techniques, such as diffusion, perfusion, magnetization transfer imaging, functional MRI, and MR spectroscopy, provide insight into the pathophysiological processes of ALS and may have a role in the identification and monitoring of UMN pathology. This article provides an overview of these neuroimaging techniques and their potential roles in ALS.

Whole-brain proton MR spectroscopic imaging of mild-to-moderate traumatic brain injury and correlation with neuropsychological deficits

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.

Robust reconstruction of MRSI data using a sparse spectral model and high resolution MRI priors

We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed method combines the reconstruction and postprocessing steps into a unified algorithm. This integrated approach enables us to inject a range of prior information into the data processing scheme, thus constraining the reconstructions. We use high resolution, 3-D estimate of the magnetic field inhomogeneity map to generate an accurate forward model, while a high resolution estimate of the fat/water boundary is used to minimize spectral leakage artifacts. We parameterize the spectrum at each voxel as a sparse linear combination of spikes and polynomials to capture the metabolite and baseline components, respectively. The constrained model makes the problem better conditioned in regions with significant field inhomogeneity, thus enabling the recovery even in regions with high field map variations. To exploit the high resolution MR information, we formulate the problem as an anatomically constrained total variation optimization scheme on a grid with the same spacing as the magnetic resonance imaging data. We analyze the performance of the proposed scheme using phantom and human subjects. Quantitative and qualitative comparisons indicate a significant improvement in spectral quality and lower leakage artifacts.

Improving 1H MRSI measurement of cerebral lactate for clinical applications

Accurate measurement of cerebral lactate is critical to the understanding of brain function for psychiatric disorders such as panic disorder and bipolar disorder as well as mitochondrial dysfunction. Proton magnetic spectroscopic imaging (MRSI) techniques can be used to study lactate in vivo; however, accurate measurement of cerebral lactate, which is normally at low basal abundance, can be challenging. In this study, regional lactate measurements obtained with two different MRSI analytic approaches were evaluated using proton echo-planar spectroscopic imaging (PEPSI) data from 18 healthy adults participating in an in vivo sodium lactate infusion study. The results demonstrate that averaging data within a region of interest (ROI) before spectral fitting with LCModel results in significantly improved lactate measurement as compared to averaging chemical concentrations derived from the fitting of individual voxels in the ROI. Simulation results that confirm this finding are also presented. This study additionally outlines an atlas-based approach for the systematic computation of regional distributions of chemical concentrations in large MRSI data sets.

Reproducibility of serial whole-brain MR spectroscopic imaging

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.

Spatial spectral modeling for robust MRSI

We propose a novel spatial spectral model for the reconstruction of magnetic resonance spectroscopic imaging (MRSI) signal. We penalize the compartmentalized spatial total variation norm of the signal to exploit the spatial properties of the metabolite peaks. The spectral signal is modeled as a sparse linear combination of spikes and polynomials to capture the peaks and baseline induced by unsuppressed water and lipids. We also use the high-resolution map of the magnetic field distribution within the slice to model the image acquisition, thus correcting for intra-voxel line shape distortions. The spectral model enables the stable recovery of the signal even in challenging spatial regions, while the spatial model suppresses the spectral leakage from extra-cranial fat and inter-voxel crosstalk. We acquire the MRSI signal using EPSI, while the high-resolution 3-D MRI information is derived using Dixon scans. The reconstruction of phantom and in vivo MRSI data demonstrate a significant improvement in spectral quality and accuracy over classical MRSI schemes.

Multivariate statistical mapping of spectroscopic imaging data

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.

Visualization of image data from cells to organisms

Advances in imaging techniques and high-throughput technologies are providing scientists with unprecedented possibilities to visualize internal structures of cells, organs and organisms and to collect systematic image data characterizing genes and proteins on a large scale. To make the best use of these increasingly complex and large image data resources, the scientific community must be provided with methods to query, analyze and crosslink these resources to give an intuitive visual representation of the data. This review gives an overview of existing methods and tools for this purpose and highlights some of their limitations and challenges.

Linked Exploratory Visualizations for Uncertain MR Spectroscopy Data

We present a system for visualizing magnetic resonance spectroscopy (MRS) data sets. Using MRS, radiologists generate multiple 3D scalar fields of metabolite concentrations within the brain and compare them to anatomical magnetic resonance imaging. By understanding the relationship between metabolic makeup and anatomical structure, radiologists hope to better diagnose and treat tumors and lesions. Our system consists of three linked visualizations: a spatial glyph-based technique we call Scaled Data-Driven Spheres, a parallel coordinates visualization augmented to incorporate uncertainty in the data, and a slice plane for accurate data value extraction. The parallel coordinates visualization uses specialized brush interactions designed to help users identify nontrivial linear relationships between scalar fields. We describe two novel contributions to parallel coordinates visualizations: linear function brushing and new axis construction. Users have discovered significant relationships among metabolites and anatomy by linking interactions between the three visualizations.

Quantitative SENSE-MRSI of the human brain

PURPOSE

To develop a method for estimating metabolite concentrations using phased-array coils and sensitivity-encoded (SENSE) magnetic resonance spectroscopic images (MRSI) of the human brain.

MATERIALS AND METHODS

The method is based on the phantom replacement technique and uses receive coil sensitivity maps and body-coil loading factors to account for receive B(1) inhomogeneity and variable coil loading, respectively. Corrections for cerebrospinal fluid content from the MRSI voxel were also applied, and the total protocol scan time was less than 15 min. The method was applied to 10 normal human volunteers using a multislice 2D-MRSI sequence at 3 T, and seven different brain regions were quantified.

RESULTS

N-Acetyl aspartate (NAA) concentrations varied from 9.7 to 14.7 mM, creatine (Cr) varied from 6.6 to 10.6 mM and choline (Cho) varied from 1.6 to 3.0 mM, in good general agreement with prior literature values.

CONCLUSIONS

Quantitative SENSE-MRSI of the human brain is routinely possible using an adapted phantom-replacement technique. The method may also be applied to other MRSI techniques, including conventional phase encoding, with phased-array receiver coils, provided that coil sensitivity profiles can be measured.

Application of volumetric MR spectroscopic imaging for localization of neocortical epilepsy

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.

Grid-free interactive and automated data processing for MR chemical shift imaging data

PURPOSE

Today's available chemical shift imaging (CSI) analysis tools are based on Fourier transform of the entire data set prior to interactive display. This strategy is associated with limitations particularly when arbitrary voxel positions within a 3D spatial volume are needed by the user. In this work, we propose and demonstrate a processing-resource-efficient alternative strategy for both interactive and automated CSI data processing up to three spatial dimensions.

METHODS

This approach uses real-time voxel-shift by first-order phase manipulation as a basis and therefore allows grid-free voxel positioning within the 3D volume. The corresponding spectrum is extracted from the 4D data (3D spatial/1D spectral) at each time a voxel position is selected. The spatial response function and hence the exact voxel size and shape are calculated in parallel including the same processing parameters. Using this mechanism sequentially along with AMARES time-domain modeling, we also implemented automated quantitative and B (0)-insensitive metabolite mapping.

RESULTS

Metabolite maps of N-acetyl aspartate, choline and creatine were generated using (1)H-CSI data from the brain of healthy volunteers and patients with tumor and epilepsy. (31)P-3D-CSI of the heart of a healthy volunteer is also shown.

CONCLUSION

The calculated metabolite maps demonstrate good stability and accuracy of the algorithm in all situations tested. The suggested algorithm constitutes therefore an attractive alternative to existing CSI processing strategies.

Mapping of brain metabolite distributions by volumetric proton MR spectroscopic imaging (MRSI)

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.

Absolute metabolite concentrations calibrated using the total water signal in brain (1)H MRS

Magnetic resonance spectroscopy (MRS) has been coupled with a multi-echo imaging sequence to determine the relaxation corrected signal areas of the metabolites and the tissue water. Stimulated echo acquisition mode (STEAM) spectra (TE/TM/TR 30/13.7/5000 ms) acquired from gray and white matter voxels in 43 healthy volunteers were fit using LCModel. Corresponding water signals, measured using a multi-echo T(2) imaging sequence, were fit with a Non-Negative Least Squares algorithm. Using this approach the water area could be T(1) and T(2) corrected for all three water compartments: cerebrospinal fluid (CSF), intra- and extra-cellular water, and myelin water. The image-based water measurement is an improvement over spectroscopy methods because it can be more sensitive to water changes in diseased tissue. Metabolite areas were also corrected for relaxation losses. In occipital gray matter, the concentrations of Cho, Cr, and N-acetyl aspartate (NAA) were 1.27 (0.06), 8.9 (0.3), and 9.3 (0.3) mmol/L tissue, respectively and in parietal white matter they were 1.90 (0.05), 7.9 (0.2), and 9.8 (0.2) mmol/L tissue. The Cho and Cr concentrations were different in occipital gray compared to parietal white matter (p < 0.0001 and <0.005, respectively).

Proton magnetic resonance spectroscopy in multiple sclerosis

Proton magnetic resonance spectroscopy ((1)H-MRS) provides tissue metabolic information in vivo. This article reviews the role of MRS-determined metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord in advancing our knowledge of pathologic changes in multiple sclerosis (MS). In addition, the role of MRS in objectively evaluating therapeutic efficacy is reviewed. This potential metabolic information makes MRS a unique tool to follow MS disease evolution, understand its pathogenesis, evaluate the disease severity, establish a prognosis, and objectively evaluate the efficacy of therapeutic interventions.

A Scalable Framework For Segmenting Magnetic Resonance Images

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.