Microstructural and Metabolic Changes in Normal Aging Human Brain Studied with Combined Whole-Brain MR Spectroscopic Imaging and Quantitative MR Imaging.

PURPOSE: This study aimed to detect age-related brain metabolic and microstructural changes in healthy human brains by the use of whole-brain proton magnetic resonance spectroscopic imaging (1H­MRSI) and quantitative MR imaging (qMRI). METHODS: In this study, 60 healthy participants with evenly distributed ages (between 21 and 69 years) and sex underwent MRI examinations at 3T including whole-brain 1H­MRSI. The concentrations of the metabolites N­acetylaspartate (NAA), choline-containing compounds (Cho), total creatine and phosphocreatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI), as well as the brain relaxation times T2, T2' and T1 were measured in 12 regions of interest (ROI) in each hemisphere. Correlations between measured parameters and age were estimated with linear regression analysis and Pearson's correlation test. RESULTS: Significant age-related changes of brain regional metabolite concentrations and tissue relaxation times were found: NAA decreased in eight of twelve ROIs, Cho increased in three ROIs, tCr in four ROIs, and mI in three ROIs. Glx displayed a significant decrease in one ROI and an increase in another ROI. T1 increased in four ROIs and T2 in one ROI, while T2' decreased in two ROIs. A negative correlation of tCr concentrations with T2' relaxation time was found in one ROI as well as the positive correlations of age-related T1 relaxation time with concentrations of tCr, mI, Glx and Cho in another ROI. CONCLUSION: Normal aging in human brain is associated with coexistent brain regional metabolic alterations and microstructural changes, which may be related to age-related decline in cognitive, affective and psychomotor domains of life in the older population.

Detection of Normal Aging Effects on Human Brain Metabolite Concentrations and Microstructure with Whole-Brain MR Spectroscopic Imaging and Quantitative MR Imaging.

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

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.

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.

Comparison of spectral fitting methods for overlapping J-coupled metabolite resonances.

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

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.

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.

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

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

Accurate template-based correction of brain MRI intensity distortion with application to dementia and aging.

This paper examines an alternative approach to separating magnetic resonance imaging (MRI) intensity inhomogeneity from underlying tissue-intensity structure using a direct template-based paradigm. This permits the explicit spatial modeling of subtle intensity variations present in normal anatomy which may confound common retrospective correction techniques using criteria derived from a global intensity model. A fine-scale entropy driven spatial normalisation procedure is employed to map intensity distorted MR images to a tissue reference template. This allows a direct estimation of the relative bias field between template and subject MR images, from the ratio of their low-pass filtered intensity values. A tissue template for an aging individual is constructed and used to correct distortion in a set of data acquired as part of a study on dementia. A careful validation based on manual segmentation and correction of nine datasets with a range of anatomies and distortion levels is carried out. This reveals a consistent improvement in the removal of global intensity variation in terms of the agreement with a global manual bias estimate, and in the reduction in the coefficient of intensity variation in manually delineated regions of white matter.

An intensity consistent filtering approach to the analysis of deformation tensor derived maps of brain shape.

Deformation tensor morphometry makes use of the derivatives of spatial transformations between anatomies, to provide highly localized volumetric maps of relative anatomical size. The analysis of such maps, however, has the challenge of describing the data in a way that allows the spatial scale and extent of the local shape properties to match those induced by the disease process being studied. This study examines an approach to the spatial filtering of transformation Jacobian maps created in multisubject studies of brain anatomy, which constrains the filter neighborhood within common structural boundaries present in the spatially normalized image data. The filtering incorporates information derived from the spatial normalization process, using a statistical framework to introduce a measure of uncertainty in local regional intensity correspondence following spatial normalisation. The proposed filtering approach is compared to the use of spatially invariant Gaussian filtering in the analysis of Jacobian determinant maps of brain shape and shape change in Alzheimer's disease and normal aging. Results show significantly improved delineation of fine scale patterns of shape difference (in cross-sectional studies) and shape change (from multiple serial magnetic resonance imaging studies).

[Monitoring of irradiated brain metastases using MR perfusion imaging and 1H MR spectroscopy]. / Verlaufsbeobachtung bestrahlter Hirnmetastasen mittels MR-Perfusionsbildgebung und 1H-MR-Spektroskopie.

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

Early detection and longitudinal changes in amyotrophic lateral sclerosis by (1)H MRSI.

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

Assessment of 3D proton MR echo-planar spectroscopic imaging using automated spectral analysis.

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

Short echo time multislice proton magnetic resonance spectroscopic imaging in human brain: metabolite distributions and reliability.

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

Comparison of methods for reduction of lipid contamination for in vivo proton MR spectroscopic imaging of the brain.

In vivo proton MR spectroscopic imaging (MRSI) of human brain is complicated by the presence of a strong signal from subcutaneous lipids, which may result in signal contamination in metabolite images obtained following Fourier-transform reconstruction. In this study, two approaches for reduction of lipid contamination--using postprocessing and additional data acquisition--are compared. The first uses extrapolation of k-space information for subcutaneous lipid, which has been applied to data obtained using conventional fully phase-encoded MRSI with circularly sampled k-space or echo-planar spectroscopic imaging (EPSI). The second uses a dual EPSI technique that combines multiple-averaged central k-space data with a single EPSI acquisition of additional information that is used for improved lipid reconstruction. Comparisons are carried out with data obtained from human brain in vivo at 1.5 T with short and medium TEs. Results demonstrate that the performance of both methods for reducing the effects of lipid contamination is similar, and that both are limited by the effects of instrumental instabilities and subject motion, which also depend on the acquisition method used.

Representation of strong baseline contributions in 1H MR spectra.

A comparison is made between two optimization procedures and two data models for automated analysis of in vivo proton MR spectra of brain, typical of that obtained using MR spectroscopic imaging at 1.5 Tesla. First, a shift invariant wavelet filter is presented that provides improved performance over a conventional wavelet filter method for characterizing smoothly varying baseline signals. Next, two spectral fitting methods are described: an iterative spectral analysis method that alternates between optimizing a parametric description of metabolite signals and nonparametric characterization of baseline contributions, and a single-pass method that optimizes a complete spectral and baseline model. Both methods are evaluated using wavelet and spline models of the baseline function. Results are shown for Monte Carlo simulations of data representative of both long and short TE, in vivo 1H acquisitions.

Region and tissue differences of metabolites in normally aged brain using multislice 1H magnetic resonance spectroscopic imaging.

Quantitative measurements of regional and tissue specific concentrations of brain metabolites were measured in elderly subjects using multislice proton magnetic resonance spectroscopic imaging ((1)H MRSI). Selective k-space extrapolation and an inversion-recovery sequence were used to minimize lipid contamination and linear regression was used to account for partial volume problems. The technique was applied to measure the concentrations of N-acetyl aspartate (NAA), and creatine (Cr)- and choline (Cho)-containing compounds in cortical gray and white matter, and white matter lesions of the frontal and the parietal lobe in 40 normal elderly subjects (22 females and 18 males, 56-89 years old, mean age 74 +/- 8). NAA was about 15% lower in cortical gray matter and 23% lower in white matter lesions when compared to normal white matter. Cr was 11% higher in cortical gray matter than in white matter, and also about 15% higher in the parietal cortex than in the frontal cortex. Cho was 28% lower in cortical gray matter than in white matter. Furthermore, NAA and Cr changes correlated with age. In conclusion, regional and tissue differences of brain metabolites must be considered in addition to age-related changes when interpreting (1)H MRSI data.

Reanalysis of multislice (1)H MRSI in amyotrophic lateral sclerosis.

The goal of this work was to reexamine previously published (1) brain spectroscopy data of abnormal metabolite ratios in amyotrophic lateral sclerosis (ALS). Toward this goal, (1)H MR spectroscopic imaging data from 10 ALS and nine control subjects were reanalyzed using improved data analysis techniques, including automated curve fitting and tissue-volume correction. In the motor cortex of ALS, N-acetyl aspartate (NAA) was 23% (P = 0.004) lower than in controls, and in the posterior internal capsule of ALS choline compounds (Cho) were 20% (P = 0.02) higher. This demonstrates that the metabolite ratio changes in ALS were due to NAA loss in the motor cortex (as expected) and Cho increase in the posterior internal capsule (not expected). Magn Reson Med 45:513-516, 2001.

Temporal lobe epilepsy: qualitative reading of 1H MR spectroscopic images for presurgical evaluation.

PURPOSE: To study the feasibility and clinical potential of visual inspection of hydrogen 1 magnetic resonance (MR) spectroscopic metabolite images for the lateralization of unilateral nonlesional temporal lobe epilepsy (TLE). MATERIALS AND METHODS: MR imaging and 1H MR spectroscopic imaging were performed of the temporal lobes in 50 patients with TLE and 23 age-matched healthy volunteers. N-acetylaspartate (NAA) and creatine plus choline metabolite images were read by two neuroradiologists who determined lateralization according to the side of lower NAA signal intensity. Quantitative estimates of NAA were calculated by using an automated fitting program. RESULTS: Agreement in lateralization between readers was significant with a kappa score of 0.53 for all patients with TLE and 0.63 for patients displaying mild or marked NAA asymmetry. Among the 50 patients with TLE, lateralization was determined correctly by reader 1 in 38 (76%) patients and by reader 2 in 31 (62%) patients. If limited to patients with mild or marked NAA asymmetry, correct lateralization improved to 30 (77%) of 39 and 16 (80%) of 20 patients, respectively. Combined qualitative reading and quantitative spectral fitting enabled lateralization in 34 (85%) of 40 patients with TLE for reader 1 and 30 (77%) of 39 for reader 2, including nine of 14 patients with TLE with negative MR images. CONCLUSION: Reading of metabolite images is a feasible and fast means for noninvasive evaluation of patients with TLE who are candidates for surgery and enables lateralization in some patients with negative MR images.