QUALITY: quantification improvement by converting lineshapes to the Lorentzian type

Magnetic resonance spectroscopy in the hippocampus of adult APP/PS1 mice following chronic vitamin D deficiency

Vitamin D (VitD) deficiency can exacerbate AD progression and may cause changes in brain metabolite levels that can be detected by magnetic resonance spectroscopy (MRS). The purpose of this study was to determine whether chronic VitD deficiency in an AD mouse model caused persistent metabolite levels changes in the hippocampus associated with memory performance. Six-month-old APPSwe/PS1ΔE9 (APP/PS1) mice (N = 14 mice/group) were fed either a VitD deficient (VitD-) diet or a control diet. Metabolite level changes in the hippocampus were evaluated by 1H MRS using a 9.4 T MRI. Ventricle volume was assessed by imaging and spatial memory was evaluated using the Barnes maze. All measurements were made at 6, 9, 12, and 15 months of age. At 15 months of age, amyloid plaque load and astrocyte number were evaluated histologically (N = 4 mice/group). Levels of N-acetyl aspartate and creatine were lower in VitD- mice compared to control diet mice at 12 months of age. VitD deficiency did not change ventricle volume. Lactate levels increased over time in VitD- mice and increases from 12 to 15 months were negatively correlated with changes in primary latency to the target hole in the Barns Maze. VitD- mice showed improved spatial memory performance compared to control diet mice. VitD- mice also had more astrocytes in the cortex and hippocampus at 15 months than control diet mice. This study suggests that severe VitD deficiency in APP/PS1 mice may lead to compensatory changes in metabolite and astrocyte levels that contribute to improved performance on spatial memory tasks.

Vespa: Integrated applications for RF pulse design, spectral simulation and MRS data analysis

PURPOSE

The Vespa package (Versatile Simulation, Pulses, and Analysis) is described and demonstrated. It provides workflows for developing and optimizing linear combination modeling (LCM) fitting for ¹ H MRS data using intuitive graphical user interface interfaces for RF pulse design, spectral simulation, and MRS data analysis. Command line interfaces for embedding workflows in MR manufacturer platforms and utilities for synthetic dataset creation are included. Complete provenance is maintained for all steps in workflows.

THEORY AND METHODS

Vespa is written in Python for compatibility across operating systems. It embeds the PyGAMMA spectral simulation library for spectral simulation. Multiprocessing methods accelerate processing and visualization. Applications use the Vespa database for results storage and cross-application access. Three projects demonstrate pulse, sequence, simulation, and data analysis workflows: (1) short TE semi-LASER single-voxel spectroscopy (SVS) LCM fitting, (2) optimizing MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) flip angle and LCM fitting, and (3) creating a synthetic short TE dataset.

RESULTS

The LCM workflows for in vivo basis set creation and spectral analysis showed reasonable results for both the short TE semi-LASER and MEGA-PRESS. Examples of pulses, simulations, and data fitting are shown in Vespa application interfaces for various steps to demonstrate the interactive workflow.

CONCLUSION

Vespa provides an efficient and extensible platform for characterizing RF pulses, pulse design, spectral simulation optimization, and automated LCM fitting via an interactive platform. Modular design and command line interface make it easy to embed in other platforms. As open source, it is free to the MRS community for use and extension. Vespa source code and documentation are available through GitHub.

Post-acquisition water-signal removal in 3D water-unsuppressed 1 H-MR spectroscopic imaging of the prostate

PURPOSE

To develop a robust processing procedure of raw signals from water-unsuppressed MRSI of the prostate for the mapping of absolute tissue concentrations of metabolites.

METHODS

Water-unsuppressed 3D MRSI data were acquired from a phantom, from healthy volunteers, and a patient with prostate cancer. Signal processing included sequential computation of the modulus of the FID to remove water sidebands, a Hilbert transformation, and k-space Hamming filtering. For the removal of the water signal, we compared Löwner tensor-based blind source separation (BSS) and Hankel Lanczos singular value decomposition techniques. Absolute metabolite levels were quantified with LCModel and the results were statistically analyzed to compare the water removal methods and conventional water-suppressed MRSI.

RESULTS

The post-processing algorithms successfully removed the water signal and its sidebands without affecting metabolite signals. The best water removal performance was achieved by Löwner tensor-based BSS. Absolute tissue concentrations of citrate in the peripheral zone derived from water-suppressed and unsuppressed ¹ H MRSI were the same and as expected from the known physiology of the healthy prostate. Maps for citrate and choline from water-unsuppressed 3D ¹ H-MRSI of the prostate showed expected spatial variations in metabolite levels.

CONCLUSION

We developed a robust relatively simple post-processing method of water-unsuppressed MRSI of the prostate to remove the water signal. Absolute quantification using the water signal, originating from the same location as the metabolite signals, avoids the acquisition of additional reference data.

Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer's Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study

Identification of biological changes underlying the early symptoms of Alzheimer's disease (AD) will help to identify and stage individuals prior to symptom onset. The limbic system, which supports episodic memory and is impaired early in AD, is a primary target. In this study, brain metabolism and microstructure evaluated by high field (7 Tesla) proton magnetic resonance spectroscopy (1H-MRS) and diffusion tensor imaging (DTI) were evaluated in the limbic system of eight individuals with mild cognitive impairment (MCI), nine with AD, and sixteen normal elderly controls (NEC). Left hippocampal glutamate and posterior cingulate N-acetyl aspartate concentrations were reduced in MCI and AD compared to NEC. Differences in DTI metrics indicated volume and white matter loss along the cingulum in AD compared to NEC. Metabolic and microstructural changes were associated with episodic memory performance assessed using Craft Story 21 Recall and Benson Complex Figure Copy. The current study suggests that metabolite concentrations measured using 1H-MRS may provide insight into the underlying metabolic and microstructural processes of episodic memory impairment.

Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations

Once an MRS dataset has been acquired, several important steps must be taken to obtain the desired metabolite concentration measures. First, the data must be preprocessed to prepare them for analysis. Next, the intensity of the metabolite signal(s) of interest must be estimated. Finally, the measured metabolite signal intensities must be converted into scaled concentration units employing a quantitative reference signal to allow meaningful interpretation. In this paper, we review these three main steps in the post-acquisition workflow of a single-voxel MRS experiment (preprocessing, analysis and quantification) and provide recommendations for best practices at each step.

Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations

With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.

Optimizing acquisition and fitting conditions for 1 H MR spectroscopy investigations in global brain pathology

PURPOSE

To optimize acquisition and fitting conditions for nonfocal disease in terms of voxel size and use of individual coil element data. Increasing the voxel size yields a higher signal-to-noise ratio, but leads to larger linewidths and more artifacts. Several ways to improve the spectral quality for large voxels are exploited and the optimal use of individual coil signals investigated.

METHODS

Ten human subjects were measured at 3 T using a 64-channel receive head coil with a semi-LASER localization sequence under optimized and deliberately mis-set field homogeneity. Eight different voxel sizes (8 to 99 cm³ ) were probed. Spectra were fitted either as weighted sums of the individual coil elements or simultaneously without summation. Eighteen metabolites were included in the fit model that also included the lineshapes from all coil elements as reflected in water reference data. Fitting errors for creatine, myo-Inositol and glutamate are reported as representative parameters to judge optimal acquisition and evaluation conditions.

RESULTS

Minimal Cramér-Rao lower bounds and thus optimal acquisition conditions were found for a voxel size of ~ 70 cm³ for the representative upfield metabolites. Spectral quality in terms of lineshape and artifact appearance was determined to differ substantially between coil elements. Simultaneous fitting of spectra from individual coil elements instead of traditional fitting of a weighted sum spectrum reduced Cramer-Rao lower bounds by up to 17% for large voxel sizes.

CONCLUSION

The optimal voxel size for best precision in determined metabolite content is surprisingly large. Such an acquisition condition is most relevant for detection of low-concentration metabolites, like NAD⁺ or phenylalanine, but also for longitudinal studies where very small alterations in metabolite content are targeted. In addition, simultaneous fitting of single channel spectra enforcing lineshape and coil sensitivity information proved to be superior to traditional signal combination with subsequent fitting.

Effect of linewidth on estimation of metabolic concentration when using water lineshape spectral model fitting for single voxel proton spectroscopy at 7 T

Good B₀ field homogeneity is considered an essential requirement to obtain high-quality MRS data. Many commonly used spectral fitting methods assume that all metabolite signals have Lorentzian or Gaussian shapes. However, B₀ inhomogeneity can both broaden the linewidth and modify the lineshape. In this study, it is hypothesized that a realistic metabolite fitting model, which accounts for B₀ homogeneity on the basis of the water lineshape, will improve the accuracy of estimation of metabolite concentrations. In-vivo water suppressed/unsuppressed single voxel spectroscopy signals were acquired under three different B₀ field homogeneity regimes. Individual realistic basis sets were created for each acquisition. Frequency-domain spectral fitting with LCModel was used to quantify the metabolite concentrations with fitting uncertainties given in terms of the Cramer-Rao lower bound. The quantification results obtained using the water lineshape basis set yielded similar concentrations independent of linewidth and showed a larger fitting error as the linewidth increased. The conventional approach, however quantifies metabolite concentrations with greater variations despite showing a supposedly improved fitting quality. The water lineshape basis set achieved single voxel spectroscopy accuracy that is less sensitive to the linewidth compared to the conventional spectral fitting method for the range of linewidths used in this study, but the precision deteriorated with worsening B₀ field inhomogeneity. The beneficial effect was ascribed to a reduction in the number of degrees of freedom when using the water lineshape to generate the basis set.

Solid-state 23Na NMR spectroscopy studies of ordered and disordered cellulose nanocrystal films

Cellulose nanocrystal films with either disordered or chiral nematic structures of varying helical pitch were investigated using ²³Na solid-state nuclear magnetic resonance (NMR) spectroscopy. Spin lattice relaxation of ¹H correlated with ²³Na analyzed by indirect observation using polarization transfer from ¹H nuclei to ²³Na nuclei showed that the Na⁺ cations are well hydrated in the cellulose nanocrystal films. Linewidth analysis in solid-state ²³Na NMR showed that the Na⁺ cations move in confined spaces, and that the Na⁺ cations in the film having disordered structure are more dynamic than in the films having ordered structure. From lineshape analysis of the ²³Na 2D nutation NMR spectra, we can distinguish the Na⁺ environments within the ordered and disordered films, and find trends in anisotropic interaction parameters between ordered samples with different pitches. These are the first detailed ²³Na NMR spectroscopic studies of CNC-Na⁺ films, and they show that this technique may be a powerful probe for characterizing the extent of order in nanocellulose samples.

Metabolite and functional profile of patients with cervical spondylotic myelopathy

OBJECTIVE

The goal of this study was to compare the recovery of neuronal metabolism and functional reorganization in the primary motor cortex (M1) between mild and moderate cervical spondylotic myelopathy (CSM) following surgical intervention.

METHODS

Twenty-eight patients with CSM underwent 3-T MRI scans that included spectroscopy and functional MRI, before surgery and 6 months postsurgery. The classification of severity was based on the modified Japanese Orthopaedic Association questionnaire. Mild and moderate myelopathy were defined by modified Japanese Orthopaedic Association scores > 12 of 18 (n = 15) and 9–12 (n = 13), respectively. Ten healthy control subjects underwent 2 MRI scans 6 months apart. Metabolite levels were measured in the M1 contralateral to the greater deficit side in patients with CSM and on both sides in the controls. Motor function was assessed using a right finger–tapping paradigm and analyzed with BrainVoyager QX.

RESULTS

Patients with mild CSM had a lower preoperative N-acetylaspartate to creatine (NAA/Cr) ratio compared with moderate CSM, suggesting mitochondrial dysfunction. Postsurgery, NAA/Cr in moderate CSM decreased to the levels observed in mild CSM. Preoperatively, patients with mild CSM had a larger volume of activation (VOA) in the M1 than those with moderate CSM. Postoperatively, the VOAs were comparable between the mild and moderate CSM groups and had shifted toward the primary sensory cortex.

CONCLUSIONS

The NAA/Cr ratio and VOA size in the M1 can be used to discriminate between mild and moderate CSM. Postsurgery, the metabolite profile of the M1 did not recover in either group, despite significant clinical improvement. The authors proposed that metabolic impairment in the M1 may trigger the recruitment of adjacent healthy cortex to achieve functional recovery.

Illness versus substance use effects on the frontal white matter in early phase schizophrenia: A 4Tesla (1)H-MRS study

OBJECTIVE

Young adults with early phase schizophrenia often report a past or current pattern of illicit substance use and/or alcohol misuse. Still, little is known about the cumulative and separate effects of each stressor on white matter tissue, at this vulnerable period of brain development.

METHODS

Participants involved 24 healthy controls with a past or current history of sustained illicit drug use and/or alcohol misuse (users), 23 healthy controls without such history (normative data), and 27 users with early phase schizophrenia. (1)H-MRS data were acquired from a large frontal volume encompassing 95% of white matter, using a 4Tesla scanner (LASER sequence, TR/TE 3200/46ms).

RESULTS

Reduced levels of choline-containing compounds (Cho) were specific to the effect of illness (Cohen's d=0.68), with 22% of the variance in Cho levels accounted for by duration of illness. Reduced levels of myoInositol (d=1.10) and creatine plus phosphocreatine (d=1.07) were specific to the effects of illness plus substance use. Effect of substance use on its own was revealed by reductions in levels of glutamate plus glutamine (d=0.83) in control users relative to normative data.

CONCLUSIONS

The specific effect of illness on white matter might indicate a decreased synthesis of membrane phospholipids or alternatively, reduced membrane cellular density. In terms of limitations, this study did not include patients without a lifetime history of substance use (non-users), and the specific effect of each substance used could not be studied separately.

ProFit revisited

PURPOSE

An enhanced version of the ProFit fitting tool was developed and validated to improve the quantification of two-dimensional JRPESS spectroscopic data.

METHODS

The proposed enhancements were achieved by flexible organization of prior knowledge, configurations for different situations, the inclusion of measured macromolecular baseline contribution, additional baseline splines and a model-free lineshape based on self-deconvolution. The new software was tested and tuned on simulated data and subsequently applied to in vivo intrasubject and intersubject data.

RESULTS

Fit results of simulated and acquired spectra show good overall quality suggesting the potential reliable detection of up to 18 metabolites on a 3T system yielding Cramer-Lower-Bounds below 20%.

CONCLUSION

The proposed enhanced version of ProFit together with two-dimensional J-resolved spectroscopy offers the opportunity to reliably detect a wide selection of important brain metabolites on 3T.

Spectral fitting using basis set modified by measured B0 field distribution

This study sought to demonstrate and evaluate a novel spectral fitting method to improve quantification accuracy in the presence of large magnetic field distortion, especially with high fields. MRS experiments were performed using a point-resolved spectroscopy (PRESS)-type sequence at 7 T. A double-echo gradient echo (GRE) sequence was used to acquire B0 maps following MRS experiments. The basis set was modified based on the measured B0 distribution within the MRS voxel. Quantification results were obtained after fitting the measured MRS data using the modified basis set. The proposed method was validated using numerical Monte Carlo simulations, phantom measurements, and comparison of occipital lobe MRS measurements under homogeneous and inhomogeneous magnetic field conditions. In vivo results acquired from voxels placed in thalamus and prefrontal cortex regions close to the frontal sinus agreed well with published values. Instead of noise-amplifying complex division, the proposed method treats field variations as part of the signal model, thereby avoiding inherent statistical bias associated with regularization. Simulations and experiments showed that the proposed approach reliably quantified results in the presence of relatively large magnetic field distortion. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

N-acetyl-aspartyl-glutamate detection in the human brain at 7 Tesla by echo time optimization and improved Wiener filtering

PURPOSE

To report enhanced signal detection for measuring N-acetyl-aspartyl-glutamate (NAAG) in the human brain at 7 Tesla by echo time (TE) -optimized point-resolved spectroscopy (PRESS) and improved Wiener filtering.

METHODS

Using a highly efficient in-house developed numerical simulation program, a PRESS sequence with (TE1 , TE2 ) = (26, 72) ms was found to maximize the NAAG signals relative to the overlapping Glu signals. A new Wiener filtering water reference deconvolution method was developed to reduce broadening and distortions of metabolite peaks caused by B0 inhomogeneity and eddy currents.

RESULTS

Monte Carlo simulation results demonstrated that the new Wiener filtering method offered higher spectral resolution, reduced spectral artifacts, and higher accuracy in NAAG quantification compared with the original Wiener filtering method. In vivo spectra and point spread functions of signal distortion confirmed that the new Wiener filtering method lead to improved spectral resolution and reduced spectral artifacts.

CONCLUSION

TE-optimized PRESS in combination with a new Wiener filtering method made it possible to fully use both the NAAG singlet signal at 2.05 ppm and the NAAG multiplet signal at 2.18 ppm in the quantification of NAAG. A more accurate characterization of lineshape distortion for Wiener filtering needs B0 field maps and segmented anatomical images to exclude contribution from cerebral spinal fluid.

Semi-LASER 1 H MR spectroscopy at 7 Tesla in human brain: Metabolite quantification incorporating subject-specific macromolecule removal

PURPOSE

To develop an in vivo ¹ H short-echo-time semi-LASER spectroscopy protocol at 7 Tesla (T) incorporating subject-specific macromolecule removal.

METHODS

T₁ constants of the major metabolites were measured with little macromolecule contribution in seven healthy volunteers and used to optimize double inversion metabolite nulling. Spectra were acquired from parietal-occipital cortex of five healthy volunteers. Metabolite-nulled macromolecule spectra were subtracted from the metabolite spectra before fitting in the time domain with prior-knowledge templates. Absolute metabolite concentrations were determined by referencing to the water signal, following partial volume and relaxation corrections.

RESULTS

The average signal to noise ratio, N-acetylaspartate peak height divided by the baseline noise standard deviation, was 48 ± 6. T₁ constants for N-acetylaspartate, glutamate, creatine, and choline were 1.71 ± 0.15 s, 1.68 ± 0.19 s, 1.63 ± 0.10 s, and 1.41 ± 0.09 s, respectively. The optimal double inversion times for metabolite suppression were TI₁  = 2.09 s and TI₂  = 0.52 s. The coefficient of variation was less than 10% for N-acetylaspartate, creatine, choline, and myo-inositol, and less than 20% for glutamate and glutamine.

CONCLUSION

Short echo-time ¹ H semi-LASER spectroscopy at 7T incorporating subject-specific macromolecule removal yielded reproducible brain metabolite concentrations ideal for applications in disease conditions where macromolecule contributions may deviate from the norm. Magn Reson Med 74:4-12, 2015. © 2014 Wiley Periodicals, Inc.

Optimized quantitative magnetic resonance spectroscopy for clinical routine

Several practical obstacles in data handling and evaluation complicate the use of quantitative localized magnetic resonance spectroscopy (qMRS) in clinical routine MR examinations. To overcome these obstacles, a clinically feasible MR pulse sequence protocol based on standard available MR pulse sequences for qMRS has been implemented along with newly added functionalities to the free software package jMRUI-v5.0 to make qMRS attractive for clinical routine. This enables (a) easy and fast DICOM data transfer from the MR console and the qMRS-computer, (b) visualization of combined MR spectroscopy and imaging, (c) creation and network transfer of spectroscopy reports in DICOM format, (d) integration of advanced water reference models for absolute quantification, and (e) setup of databases containing normal metabolite concentrations of healthy subjects. To demonstrate the work-flow of qMRS using these implementations, databases for normal metabolite concentration in different regions of brain tissue were created using spectroscopic data acquired in 55 normal subjects (age range 6-61 years) using 1.5T and 3T MR systems, and illustrated in one clinical case of typical brain tumor (primitive neuroectodermal tumor). The MR pulse sequence protocol and newly implemented software functionalities facilitate the incorporation of qMRS and reference to normal value metabolite concentration data in daily clinical routine.

Soft constraints in nonlinear spectral fitting with regularized lineshape deconvolution

This article presents a novel method for incorporating a priori knowledge into regularized nonlinear spectral fitting as soft constraints. Regularization was recently introduced to lineshape deconvolution as a method for correcting spectral distortions. Here, the deconvoluted lineshape was described by a new type of lineshape model and applied to spectral fitting. The nonlinear spectral fitting was carried out in two steps that were subject to hard constraints and soft constraints, respectively. The hard constraints step provided a starting point and, therefore, only the changes of the relevant variables were constrained in the soft constraints step and incorporated into the linear substeps of the Levenberg-Marquardt algorithm. The method was demonstrated using localized averaged echo time point resolved spectroscopy proton spectroscopy of human brains.

Quantitative measurement of N-acetyl-aspartyl-glutamate at 3 T using TE-averaged PRESS spectroscopy and regularized lineshape deconvolution

This article introduces regularized lineshape deconvolution in conjunction with TE-averaged PRESS spectroscopy to measure N-acetyl-aspartyl-glutamate (NAAG). Averaging different echo times suppressed the signals of multiplets from strongly coupled spin systems near 2 ppm; thus, minimizing the interfering signals to detect the acetyl proton signal of NAAG. Signal distortion was corrected by lineshape deconvolution, and Tikhonov regularization was introduced to reduce noise amplification arising from deconvolution; as a result, spectral resolution was enhanced without significantly sacrificing signal-to-noise ratio (SNR). This new approach was used to measure NAAG in the two regions of interest of healthy volunteers, dominated by gray matter and white matter, respectively. The acetyl proton signal of NAAG was directly quantified by fitting the deconvoluted spectra to a Voigt-lineshape spectral model function, yielding the NAAG-N-acetyl-aspartate (NAA) ratios of 0.11±0.02 for the gray matter voxels (n=8) and 0.18±0.02 for the white matter voxels (n=12).

A constrained least-squares approach to the automated quantitation of in vivo ¹H magnetic resonance spectroscopy data

Totally Automatic Robust Quantitation in NMR (TARQUIN), a new method for the fully automatic analysis of short echo time in vivo (1)H Magnetic resonance spectroscopy is presented. Analysis is performed in the time domain using non-negative least squares, and a new method for applying soft constraints to signal amplitudes is used to improve fitting stability. Initial point truncation and Hankel singular value decomposition water removal are used to reduce baseline interference. Three methods were used to test performance. First, metabolite concentrations from six healthy volunteers at 3 T were compared with LCModel™. Second, a Monte-Carlo simulation was performed and results were compared with LCModel™ to test the accuracy of the new method. Finally, the new algorithm was applied to 1956 spectra, acquired clinically at 1.5 T, to test robustness to noisy, abnormal, artifactual, and poorly shimmed spectra. Discrepancies of less than approximately 20% were found between the main metabolite concentrations determined by TARQUIN and LCModel™ from healthy volunteer data. The Monte-Carlo simulation revealed that errors in metabolite concentration estimates were comparable with LCModel™. TARQUIN analyses were also found to be robust to clinical data of variable quality. In conclusion, TARQUIN has been shown to be an accurate and robust algorithm for the analysis of magnetic resonance spectroscopy data making it suitable for use in a clinical setting.

13C MRS of occipital and frontal lobes at 3 T using a volume coil for stochastic proton decoupling

Previously, we devised a novel strategy for in vivo 13C MRS using [2-13C]glucose infusion and low-power proton decoupling, and proposed that this strategy could be used to acquire 13C MR spectra from the frontal lobe of the human brain. Here, we demonstrate, for the first time, in vivo 13C MRS of human frontal lobe acquired at 3 T. Because the primary metabolites of [2-13C]glucose can be decoupled using very-low-radiofrequency power, we used a volume coil for proton decoupling in this study. The homogeneous B(1) field of the volume coil was found to significantly enhance the decoupling efficiency of the stochastic decoupling sequence. Detailed specific absorption rates inside the human head were analyzed using the finite difference time domain method to ensure experimental safety. In vivo 13C spectra from the occipital and frontal lobes of the human brain were obtained. At a decoupling power of 30 W (time-averaged power, 2.45 W), the spectra from the occipital lobe showed well-resolved spectral resolution and excellent signal-to-noise ratio. Although frontal lobe 13C spectra were affected by local B(0) field inhomogeneity, we demonstrated that the spectral quality could be improved using post-acquisition data processing. In particular, we showed that the frontal lobe glutamine C5 at 178.5 ppm and aspartate C4 at 178.3 ppm could be spectrally resolved with effective proton decoupling and B(0) field correction. Because of its large spatial coverage, volume coil decoupling provides the potential to acquire 13C MRS from more than one brain region simultaneously.

Pitfalls and advantages of different strategies for the absolute quantification of N-acetyl aspartate, creatine and choline in white and grey matter by 1H-MRS

This study extensively investigates different strategies for the absolute quantitation of N-acetyl aspartate, creatine and choline in white and grey matter by (1)H-MRS at 1.5 T. The main focus of this study was to reliably estimate metabolite concentrations while reducing the scan time, which remains as one of the main problems in clinical MRS. Absolute quantitation was based on the water-unsuppressed concentration as the internal standard. We compared strategies based on various experimental protocols and post-processing strategies. Data were obtained from 30 control subjects using a PRESS sequence at several TE to estimate the transverse relaxation time, T(2), of the metabolites. Quantitation was performed with the algorithm QUEST using two different metabolite signal basis sets: a whole-metabolite basis set (WhoM) and a basis set in which the singlet signals were split from the coupled signals (MSM). The basis sets were simulated in vivo for each TE used. Metabolites' T(2)s were then determined by fitting the estimated signal amplitudes of the metabolites obtained at different TEs. Then the absolute concentrations (mM) of the metabolites were assessed for each subject using the estimated signal amplitudes and either the mean estimated relaxation times of all subjects (mean protocol, MP) or the T(2) estimated from the spectra derived from the same subject (individual protocol, IP). Results showed that MP represents a less time-consuming alternative to IP in the quantitation of brain metabolites by (1)H-MRS in both grey and white matter, with a comparable accuracy when performed by MSM. It was also shown that the acquisition time might be further reduced by using a variant of MP, although with reduced accuracy. In this variant, only one water-suppressed and one water-unsuppressed spectra were acquired, drastically reducing the duration of the entire MRS examination. However, statistical analysis highlights the reduced accuracy of MP when performed using WhoM, particularly at longer echo times.

Spectral resolution amelioration by deconvolution (SPREAD) in MR spectroscopic imaging

PURPOSE

To develop, implement, and evaluate a novel postprocessing method for enhancing the spectral resolution of in vivo MR spectroscopic imaging (MRSI) data.

MATERIALS AND METHODS

Magnetic field inhomogeneity across the imaging volume was determined by acquiring MRI datasets with two differing echo times. The lineshapes of the MRSI spectra were derived from these field maps by simulating an MRSI scan of a virtual sample whose resonance frequencies varied according to the observed variations in the magnetic field. By deconvolving the lineshapes from the measured MRSI spectra, the linebroadening effects of the field inhomogeneities were reduced significantly.

RESULTS

Both phantom and in vivo proton MRSI spectra exhibited significantly enhanced spectral resolutions and improved spectral lineshapes following application of our method. Quantitative studies on a phantom show that, on average, the full width at half maximum of water peaks was reduced 42%, the full width at tenth maximum was reduced 38%, and the asymmetries of the peaks were reduced 86%.

CONCLUSION

Our method reduces the linebroadening and lineshape distortions caused by magnetic field inhomogeneities. It substantially improves the spectral resolution and lineshape of MRSI data.

Reduced hippocampal glutamate in Alzheimer disease

Altered neurometabolic profiles have been detected in Alzheimer disease (AD) using (1)H magnetic resonance spectroscopy (MRS), but no definitive biomarker of mild cognitive impairment (MCI) or AD has been established. This study used MRS to compare hippocampal metabolite levels between normal elderly controls (NEC) and subjects with MCI and AD. Short echo-time (TE=46 ms) (1)H spectra were acquired at 4T from the right hippocampus of 23 subjects with AD, 12 subjects with MCI and 15 NEC. Absolute metabolite levels and metabolite ratios were compared between groups using a multivariate analysis of covariance (covariates: age, sex) followed by post hoc Tukey's test (p<0.05 significant). Subjects with AD had decreased glutamate (Glu) as well as decreased Glu/creatine (Cr), Glu/myo-inositol (mI), Glu/N-acetylaspartate (NAA), and NAA/Cr ratios compared to NEC. Subjects with AD also had decreased Glu/mI ratio compared to MCI. There were no differences between subjects with MCI and NEC. Therefore, in addition to NAA/Cr, decreased hippocampal Glu may be an indicator of AD.

Ultrashort TE spectroscopic imaging (UTESI): application to the imaging of short T2 relaxation tissues in the musculoskeletal system

PURPOSE

To investigate ultrashort TE spectroscopic imaging (UTESI) of short T2 tissues in the musculoskeletal (MSK) system.

MATERIALS AND METHODS

Ultrashort TE pulse sequence is able to detect rapidly decaying signals from tissues with a short T2 relaxation time. Here a time efficient spectroscopic imaging technique based on a multiecho interleaved variable TE UTE acquisition is proposed for high-resolution spectroscopic imaging of the short T2 tissues in the MSK system. The projections were interleaved into multiple groups with the data for each group being collected with progressively increasing TEs. The small number of projections in each group sparsely but uniformly sampled k-space. Spectroscopic images were generated through Fourier transformation of the time domain images at variable TEs. T2* was quantified through exponential fitting of the time domain images or line shape fitting of the magnitude spectrum. The feasibility of this technique was demonstrated in volunteer and cadaveric specimen studies on a clinical 3T scanner.

RESULTS

UTESI was applied to six cadaveric specimens and four human volunteers. High spatial resolution and contrast images were generated for the deep radial and calcified layers of articular cartilage, menisci, ligaments, tendons, and entheses, respectively. Line shape fitting of the UTESI magnitude spectroscopic images show a short T2* of 1.34 +/- 0.56 msec, 4.19 +/- 0.68 msec, 3.26 +/- 0.34 msec, 1.96 +/- 0.47 msec, and 4.21 +/- 0.38 msec, respectively.

CONCLUSION

UTESI is a time-efficient method to image and characterize the short T2 tissues in the MSK system with high spatial resolution and high contrast.

MRS signal quantitation: a review of time- and frequency-domain methods

In this paper an overview of time-domain and frequency-domain quantitation methods is given. Advantages and drawbacks of these two families of quantitation methods are discussed. An overview of preprocessing methods, such as lineshape correction methods or unwanted component removal methods, is also given. The choice of the quantitation method depends on the data under investigation and the pursued objectives.

Influence of measured and simulated basis sets on metabolite concentration estimates

By quantification of brain metabolites, localized brain proton MRS can non-invasively provide biochemical information from distinct regions of the brain. Quantification of short-TE signals is usually based on a metabolite basis set. The basis set can be obtained by two approaches: (1) by measuring the signals of metabolites in aqueous solution; (2) by quantum-mechanically simulating the theoretical metabolite signals. The purpose of this study was to compare the effect of these two approaches on metabolite concentration estimates. Metabolite concentrations were quantified with the QUEST method, using both approaches. A comparison was performed with the aid of Monte Carlo studies, by using signals simulated from both basis sets. The best results were obtained when the basis set used for the fit was the same as that used to simulate the Monte Carlo signals. This comparison was also performed using in vivo short-TE signals acquired at 7 T from the central region of rat brains. The concentration estimates, with confidence intervals, obtained using both basis sets were in good agreement with values from the literature. The in vivo study showed that, in general, the differences between the estimates obtained with the two basis sets were not statistically significant or scientifically important. Consequently, a simulated basis set can be used in place of a measured basis set.

High field (1)H MRS of the hippocampus after donepezil treatment in Alzheimer disease

The purpose of this study was to measure metabolite level changes in patients with newly diagnosed Alzheimer Disease (AD) following four months of donepezil treatment. A small number of cognitively normal elderly subjects were also scanned longitudinally (twice within one year) to assess the reproducibility. Short echo-time (1)H magnetic resonance spectra were acquired at 4.0 T in the right hippocampus. Subjects were scanned at the time of first diagnosis (prior to receiving donepezil) and then following four months of donepezil treatment (5 mg/day for the first month, 10 mg/day thereafter). Changes in absolute metabolite levels and metabolite ratios were quantified and compared. There was no change in measured cognitive function following four months of donepezil treatment in the AD patients. Decreased levels of N-acetylaspartate, choline, N-acetylaspartate/creatine, choline/creatine, and myo-inositol/creatine were observed in AD patients after four months of treatment. Cognitively normal elderly subjects showed an increase in myo-inositol/choline ratio following one year. The reduced levels of N-acetylaspartate in AD patients indicates continued decline in neuronal function and/or integrity. However decreased levels of choline and myo-inositol/creatine ratio may indicate a positive treatment effect.

Ultrashort echo time spectroscopic imaging (UTESI) of cortical bone

Cortical bone in the mature skeleton has a short T(2)* and produces no detectable signal with conventional MR sequences. A two-dimensional ultrashort echo time (UTE) sequence employing half radio frequency (RF) pulse excitations and radial ramp sampling reduces the effective TE to 8 micros and is capable of detecting signals from cortical bone. We propose a time-efficient UTE spectroscopic imaging (UTESI) technique based on an interleaved variable TE acquisition, preceded by long T(2)* signal suppression using either a 90 degrees pulse and gradient dephasing or an inversion pulse and nulling. The projections were divided into multiple groups with the data for each group being collected with progressively increasing TE and interleaved projection angles. The undersampled projections within each group sparsely covered k-space. A view sharing and sliding window reconstruction algorithm was implemented to reconstruct images at each TE, followed by Fourier transformation in the time domain to generate spectroscopic images. T(2)* was quantified through either exponential fitting of the time domain images or line fitting of the magnitude spectrum. Relative water content and the resonance frequency shift due to bulk susceptibility were also evaluated. The feasibility of this technique was demonstrated with phantom and volunteer studies on a clinical 3T scanner.

Correction of frequency and phase variations induced by eddy currents in localized spectroscopy with multiple echo times

As a consequence of the time-varying magnetic field induced by eddy currents, frequency drifting occurs when the sampling window of localized spectroscopy continuously shifts. The frequency drifting and the concomitant phase variations can severely affect spectroscopy results when data are acquired with multiple echo times (TEs), such as in the measurement of glutamate (Glu) concentration using the TE-averaged method. Specifically, the averaged spectra are further broadened and distorted in the presence of residual eddy currents, and editing of the coupled spins of Glu C4 protons is affected, resulting in errors in the measured relative intensity ratio. Postacquisition correction using unsuppressed water as reference can effectively minimize this detrimental effect, as manifested by the significantly enhanced signal intensity. Also, it is demonstrated that the methyl signals of creatine (Cr) at 3.0 ppm and choline (Cho) at 3.2 ppm can be used as internal references in finding frequency and phase disparities between different TEs.

Effect of signal-to-noise ratio and spectral linewidth on metabolite quantification at 4 T

The accuracy and precision of measurements of metabolite concentrations from short echo-time spectra has previously been characterized at l.5 T as a function of signal-to-noise ratio (SNR) and peak linewidth. The purpose of this study was to characterize the systematic error in quantification of metabolite concentrations associated with linewidth and SNR for the major metabolites of interest in the short echo-time 1H-MR spectrum at 4 T. Simulated 4 T LASER localized spectra (TE = 46 ms) were generated with full width at half maximum (FWHM) over the range 4-14 Hz, and SNR over the range 5-500 by adding 100 Gaussian-distributed noise realizations at each combination of SNR and linewidth. Linewidth and SNR were treated as independent parameters, and therefore an increase in linewidth at a constant SNR resulted in increased metabolite areas. All spectra were fitted in the time domain using identical prior-knowledge and relative parameter starting values. Six metabolites (N-acetylaspartate, glutamate, creatine, myo-inositol, glycerophosphocholine, phosphocholine) were quantified with >90% accuracy and <10% standard deviation at SNR = 10 for linewidths ranging from 8 to 14 Hz FWHM. These simulations did not consider additional sources of variation, including eddy current artifacts, incomplete macromolecule baseline removal, and incomplete water suppression. Regardless, the results show that metabolite quantification from 4 T short echo-time 1H-MRS is sensitive to SNR and linewidth.

Quantitative short echo-time 1H LASER-CSI in human brain at 4 T

A novel short echo-time (1)H chemical shift imaging (CSI) pulse sequence is presented that incorporates localization by adiabatic selective refocusing (LASER) for FOV-reduction, k-space weighted averaging and macromolecule subtraction, to obtain quantitative concentration measurements of N-acetyl-aspartate, glutamate, glucose, myo-inositol, creatine and choline using a nominal voxel size of 0.56 cm(3). A comparison of spectral quality and metabolite concentration measurements was made between LASER-CSI and LASER-single voxel spectroscopy (SVS) in a region of homogeneous parietal white matter (N = 8). No significant differences were found in linewidths, signal-to-noise ratios or the effectiveness of the macromolecule subtraction between SVS and CSI. Water suppression was 45% more effective in SVS than in CSI (p < 0.05). A linear regression of all paired metabolite measurements resulted in a slope = 1.01 +/- 0.03 (r(2) = 0.73). LASER-CSI concentration measurements of N-acetyl-aspartate, glutamate, glucose, myo-inositol, creatine and choline were in agreement (within standard deviations) with LASER-SVS measurements. LASER-CSI is, therefore, a viable and attractive option for future (1)H CSI investigations.

Muscle Metabolites: Functional MR Spectroscopy during Exercise Imposed by Tetanic Electrical Nerve Stimulation

Permission from the ethics committee and informed consent were obtained. The purpose of this study was to prospectively evaluate a method developed for the noninvasive assessment of muscle metabolites during exercise. Hydrogen 1 magnetic resonance (MR) spectroscopy peaks were measured during tetanic isometric muscle contraction imposed by supramaximal repetitive nerve stimulation. The kinetics of creatine-phosphocreatine and acetylcarnitine signal changes (P < .001) could be assessed continuously before, during, and after exercise. The control peak (trimethylammonium compounds), which served as an internal reference, did not change. This technique-that is, functional MR spectroscopy-opens the possibility for noninvasive diagnostic muscle metabolite testing in a clinical setting.

1H MR spectroscopy of the brain: absolute quantification of metabolites

Hydrogen 1 (1H) magnetic resonance (MR) spectroscopy enables noninvasive in vivo quantification of metabolite concentrations in the brain. Currently, metabolite concentrations are most often presented as ratios (eg, relative to creatine) rather than as absolute concentrations. Despite the success of this approach, it has recently been suggested that relative quantification may introduce substantial errors and can lead to misinterpretation of spectral data and to erroneous metabolite values. The present review discusses relevant methods to obtain absolute metabolite concentrations with a clinical MR system by using single-voxel spectroscopy or chemical shift imaging. Important methodological aspects in an absolute quantification strategy are addressed, including radiofrequency coil properties, calibration procedures, spectral fitting methods, cerebrospinal fluid content correction, macromolecule suppression, and spectral editing. Techniques to obtain absolute concentrations are now available and can be successfully applied in clinical practice. Although the present review is focused on 1H MR spectroscopy of the brain, a large part of the methodology described can be applied to other tissues as well.

Numerical simulation of PRESS localized MR spectroscopy

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.

Time-domain semi-parametric estimation based on a metabolite basis set

A novel and fast time-domain quantitation algorithm--quantitation based on semi-parametric quantum estimation (QUEST)--invoking optimal prior knowledge is proposed and tested. This nonlinear least-squares algorithm fits a time-domain model function, made up from a basis set of quantum-mechanically simulated whole-metabolite signals, to low-SNR in vivo data. A basis set of in vitro measured signals can be used too. The simulated basis set was created with the software package NMR-SCOPE which can invoke various experimental protocols. Quantitation of 1H short echo-time signals is often hampered by a background signal originating mainly from macromolecules and lipids. Here, we propose and compare three novel semi-parametric approaches to handle such signals in terms of bias-variance trade-off. The performances of our methods are evaluated through extensive Monte-Carlo studies. Uncertainty caused by the background is accounted for in the Cramér-Rao lower bounds calculation. Valuable insight about quantitation precision is obtained from the correlation matrices. Quantitation with QUEST of 1H in vitro data, 1H in vivo short echo-time and 31P human brain signals at 1.5 T, as well as 1H spectroscopic imaging data of human brain at 1.5 T, is demonstrated.

Quantitative magnetic resonance spectroscopy: Semi-parametric modeling and determination of uncertainties

A semi-parametric approach for the quantitative analysis of magnetic resonance (MR) spectra is proposed and an uncertainty analysis is given. Single resonances are described by parametric models or by parametrized in vitro spectra and the baseline is determined nonparametrically by regularization. By viewing baseline estimation in a reproducing kernel Hilbert space, an explicit parametric solution for the baseline is derived. A Bayesian point of view is adopted to derive uncertainties, and the many parameters associated with the baseline solution are treated as nuisance parameters. The derived uncertainties formally reduce to Cramér-Rao lower bounds for the parametric part of the model in the case of a vanishing baseline. The proposed uncertainty calculation was applied to simulated and measured MR spectra and the results were compared to Cramér-Rao lower bounds derived after the nonparametrically estimated baselines were subtracted from the spectra. In particular, for high SNR and strong baseline contributions the proposed procedure yields a more appropriate characterization of the accuracy of parameter estimates than Crémer-Rao lower bounds, which tend to overestimate accuracy.

Automated classification of short echo time in in vivo 1H brain tumor spectra: a multicenter study

Automated pattern recognition techniques are needed to help radiologists categorize MRS data of brain tumors according to histological type and grade. A major question is whether a computer program "trained" on spectra from one hospital will be able to classify those from another, particularly if the acquisition protocol is different. A subset of 144 histopathologically validated brain tumor spectra in the INTERPRET database, obtained from three of the collaborating centers, was grouped into meningiomas, low-grade astrocytomas, and "aggressive tumors" (glioblastomas and metastases). Spectra from two centers formed the training set (94 spectra) while the third acted as the test set (50 spectra). Linear discriminant analysis successfully classified 48/50 in the test set; the remaining two were atypical cases. When the training and test sets were combined, 133 of the 144 spectra were correctly classified using the leave-one-out procedure. These spectra had been obtained using different sequences (STEAM and PRESS), different echo times (20, 30, 31, and 32 ms), different repetition times (1600 and 2000 ms), and different manufacturers' instruments (GE and Philips). Pattern recognition algorithms are less sensitive to acquisition parameters than had been expected.

Proton magnetic resonance spectroscopy in the brain: report of AAPM MR Task Group #9

AAPM Magnetic Resonance Task Group #9 on proton magnetic resonance spectroscopy (MRS) in the brain was formed to provide a reference document for acquiring and processing proton (1H) MRS acquired from brain tissue. MRS is becoming a common adjunct to magnetic resonance imaging (MRI), especially for the differential diagnosis of tumors in the brain. Even though MR imaging is an offshoot of MR spectroscopy, clinical medical physicists familiar with MRI may not be familiar with many of the common practical issues regarding MRS. Numerous research laboratories perform in vivo MRS on other magnetic nuclei, such as 31P, 13C, and 19F. However, most commercial MR scanners are generally only capable of spectroscopy using the signals from protons. Therefore this paper is of limited scope, giving an overview of technical issues that are important to clinical proton MRS, discussing some common clinical MRS problems, and suggesting how they might be resolved. Some fundamental issues covered in this paper are common to many forms of magnetic resonance spectroscopy and are written as an introduction for the reader to these methods. These topics include shimming, eddy currents, spatial localization, solvent saturation, and post-processing methods. The document also provides an extensive review of the literature to guide the practicing medical physicist to resources that may be useful for dealing with issues not covered in the current article.

Restoration of motion-related signal loss and line-shape deterioration of proton MR spectra using the residual water as intrinsic reference

A postprocessing method to restore motion-related signal loss and line-shape deterioration in single-volume proton MR spectroscopy (MRS) is presented. Each acquisition is corrected by its phase offset and frequency shift, extracted from the residual water signal prior to averaging. Requirements are good gradient selection and selective suppression of CSF in residual water. Stimulated echo acquisition mode (STEAM) spectra (TE = 30 ms) were analyzed using the LCModel program to study gains in metabolite signal and spectral quality in five brain regions. Increases of total N-acetyl-aspartate concentrations of up to 5% were observed. The method may be beneficial for clinical examinations of less compliant subjects and for dynamic spectroscopy.

MR spectroscopy quantitation: a review of frequency domain methods

There has been a vast increase in applications of magnetic resonance spectroscopy (MRS) in biomedical research during the last few years. This is not surprising since MRS provides both in vivo and in vitro a non-invasive tool for various biochemical and biomedical studies. There are also expectations that clinical MRS will have an important role as a diagnostic tool. An essential prerequisite for the future success of MRS for applicability in biomedical sciences will be accurate and biochemically relevant data analysis (at as high a level of automation as possible). This review briefly describes principles of the methodology available for advanced quantitative data analysis in the frequency domain. Various biomedical applications are discussed in order to illustrate the practical aspects of the analyses and to show the applicability and power of biochemical prior knowledge-based lineshape fitting analysis.

Common processing of in vivo MR spectra

This introductory article addresses approaches currently in use to process in vivo spectra. First, a brief overview is given of the information content represented by the parameters of MR signals. Subsequently, common steps in the processing of MR spectra such as pre-processing, normalisation and quantification and the use of prior knowledge are described. Finally, some prospects for more advanced processing are given.

MR spectroscopy quantitation: a review of time-domain methods

In this article an overview of time-domain quantitation methods is given. Advantages of processing the data in the measurement domain are discussed. The basic underlying principles of the methods are outlined and from them the situations under which these algorithms perform well are derived. Also an overview of methods to preprocess the data is given. In that respect, signal-to-noise and/or resolution enhancement, the removal of unwanted components and corrections for model imperfections are discussed.

Spectroscopic lineshape correction by QUECC: combined QUALITY deconvolution and eddy current correction

Lineshape distortion due to residual eddy currents and magnetic field inhomogeneities are often present in short echo time (1)H spectroscopic data. Lineshape correction methods such as QUALITY deconvolution and eddy current correction (ECC), which use a separate reference spectrum for lineshape correction, have shortcomings when unsuppressed water is chosen as the reference. This paper outlines a method of integrating both techniques to overcome these limitations while still using unsuppressed water as the reference signal. This hybrid lineshape correction technique (QUECC) is demonstrated in vivo using stimulated echo acquisition mode (STEAM) localized 4.0 Tesla data. Metabolite quantification precision increased by an average of 7%-46% compared to QUALITY deconvolution (depending on filtering) and by an average of 6% compared to ECC.

Comparison of the quantification precision of human short echo time (1)H spectroscopy at 1.5 and 4.0 Tesla

Precise quantification of human in vivo short echo time (1)H spectra remains problematic at clinical field strengths due to broad peak linewidths and low signal-to-noise ratio (SNR). In this study, multiple STEAM spectra (TE = 20 ms, volume = 8 cm(3)) were acquired in a single individual at 1.5 T and 4 T to compare quantification precision. Test-retest STEAM spectra (volume = 1.5 cm(3)) were also acquired from the anterior cingulate and thalamus of 10 individuals at 4.0 T. Metabolite levels were quantified using automated software that incorporated field strength-specific prior knowledge. With the distinct methods of data acquisition, processing, and fitting used in this study, peak height SNR increased approximately 80% while peak linewidth increased by approximately 50% in the 8 cm(3) volumes at 4.0 T compared to 1.5 T, resulting in an average increase in quantification precision of 39%. Metabolite levels from test-retest data (1.5 cm(3) voxels at 4.0 T) were quantified with similar inter- and intraindividual variability. Magn Reson Med 44:185-192, 2000. Published 2000 Wiley-Liss, Inc.