Improved analysis of 1H-MR spectra in the presence of mobile lipids

Lactate as clinical tumour biomarker: Optimization of lactate detection and quantification in MR spectroscopic imaging of glioblastomas

PURPOSE

Increased lactate (Lac) level in brain tumours is in vivo detectable by ¹H MR spectroscopy (MRS) but is frequently overlapped by strong lipid signals, which either leads to a weak quality of the Lac signal or even inhibit its detection. We sought to optimize the separation of Lac from lipid signals in intermediate-echo time MRS acquisitions thus allowing its applicability as clinical biomarker in glioblastomas.

METHODS

Data of 27 patients with glioblastoma multiforme (GBM) were analysed using standard post-processing software as well as in-house modified technique based on the same commercially available software. The patients' Lac concentration values provided by the MRS post-processing technique were converted to realistic concentrations by using an appropriately calibrated phantom. The Cramér-Rao lower bound (%CR) was the principal criterion for estimating the quality of the MRS post-processing results.

RESULTS

Based on the ex vivo calibration, the analysis of the in vivo MR spectroscopy measurements led to an improvement of the %CR(Lac) value from 18 % to 8 %. In a single case, the detection of Lac was achievable only by the modified technique, as Lac signal was contaminated with lipids using the standard analysis. The resulting in vivo Lac values from the modified analysis (median: 4.77 mmol/l, range: 1.5-9.2) were considered as a realistic order of magnitude for the metabolite concentrations, whereas no Lac was identified in the normal appearing white matter. This qualified also Lac mapping as a biomarker for regional heterogeneity in GBM.

CONCLUSIONS

The proposed methodology is a promising first step for more reliable analysis of Lac signal, decontaminating it from lipid peaks in MRS, and may help to establish Lac as a biomarker for brain tumours in clinical routine.

In-Vivo Proton Magnetic Resonance Spectroscopy of 2-Hydroxyglutarate in Isocitrate Dehydrogenase-Mutated Gliomas: A Technical Review for Neuroradiologists

The diagnostic and prognostic potential of an onco-metabolite, 2-hydroxyglutarate (2HG) as a proton magnetic resonance spectroscopy (1H-MRS) detectable biomarker of the isocitrate dehydrogenase (IDH)-mutated (IDH-MT) gliomas has drawn attention of neuroradiologists recently. However, due to severe spectral overlap with background signals, quantification of 2HG can be very challenging. In this technical review for neuroradiologists, first, the biochemistry of 2HG and its significance in the diagnosis of IDH-MT gliomas are summarized. Secondly, various 1H-MRS methods used in the previous studies are outlined. Finally, wereview previous in vivo studies, and discuss the current status of 1H-MRS in the diagnosis of IDH-MT gliomas.

On the Utility of Short Echo Time (TE) Single Voxel 1H-MRS in Non-Invasive Detection of 2-Hydroxyglutarate (2HG); Challenges and Potential Improvement Illustrated with Animal Models Using MRUI and LCModel

Mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2) are frequently found in brain tumors, and the resulting onco–metabolite, 2–hydroxyglutarate (2HG), has been suggested to be a potential diagnostic and prognostic biomarker of the diseases. Indeed, recent studies have demonstrated the feasibility of non–invasively detecting 2HG by using proton magnetic resonance spectroscopy (1H–MRS). Due to severe spectral overlaps of 2HG with its background metabolites and spectral baselines, however, the majority of those previous studies employed spectral editing methods with long echo times (TEs) instead of the most commonly used short TE approach with spectral fitting. Consequently, the results obtained with spectral editing methods may potentially be prone to errors resulting from substantial signal loss due to relaxation. Given that the spectral region where the main signal of 2HG resides is particularly sensitive to spectral baseline in metabolite quantification, we have investigated the impact of incorporating voxel–specifically measured baselines into the spectral basis set on the performance of the conventional short TE approach in 2HG detection in rodent models (Fisher 344 rats; n = 19) of IDH1/2 mutant–overexpressing F98 glioma at 9.4T. Metabolite spectra were acquired (SPECIAL sequence) for a tumor region and the contralateral normal region of the brain for each animal. For the estimation of spectral baselines metabolite–nulled spectra were obtained (double–inversion–recovery SPECIAL sequence) for each individual voxels. Data were post–processed with and without the measured baselines using MRUI and LCModel—the two most widely used data post–processing packages. Our results demonstrate that in–vivo detection of 2HG using the conventional short TE approach is challenging even at 9.4T. However, incorporation of voxel–specifically measured spectral baselines may potentially improve its performance. Upon more thorough validation in a larger number of animals and more importantly in human patients, the potential utility of the proposed short TE acquisition with voxel–specific baseline measurement approach in 2HG detection may need to be considered in the study design.

Reduced frontal glutamate + glutamine and N-acetylaspartate levels in patients with chronic schizophrenia but not in those at clinical high risk for psychosis or with first-episode schizophrenia

Changes in brain pathology as schizophrenia progresses have been repeatedly suggested by previous studies. Meta-analyses of previous proton magnetic resonance spectroscopy ((1)H MRS) studies at each clinical stage of schizophrenia indicate that the abnormalities of N-acetylaspartate (NAA) and glutamatergic metabolites change progressively. However, to our knowledge, no single study has addressed the possible differences in (1)H MRS abnormalities in subjects at 3 different stages of disease, including those at ultrahigh risk for psychosis (UHR), with first-episode schizophrenia (FES), and with chronic schizophrenia (ChSz). In the current study, 24 patients with UHR, 19 FES, 25 ChSz, and their demographically matched 3 independent control groups (n = 26/19/28 for the UHR, FES, and ChSz control groups, respectively) underwent (1)H MRS in a 3-Tesla scanner to examine metabolites in medial prefrontal cortex. The analysis revealed significant decreases in the medial prefrontal NAA and glutamate + glutamine (Glx) levels, specifically in the ChSz group as indexed by a significant interaction between stage (UHR/FES/ChSz) and clinical status (patients/controls) (P = .008). Furthermore, the specificity of NAA and Glx reductions compared with the other metabolites in the patients with ChSz was also supported by a significant interaction between the clinical status and types of metabolites that only occurred at the ChSz stage (P = .001 for NAA, P = .004 for Glx). The present study demonstrates significant differences in (1)H MRS abnormalities at different stages of schizophrenia, which potentially correspond to changes in glutamatergic neurotransmission, plasticity, and/or excitotoxicity and regional neuronal integrity with relevance for the progression of schizophrenia.

Longitudinal evaluation of the metabolic response of a tumor xenograft model to single fraction radiation therapy using magnetic resonance spectroscopy

Proton magnetic resonance spectroscopy (MRS) was used to evaluate the metabolic profile of human glioblastoma multiform brain tumors grown as xenografts in nude mice before, and at multiple time points after single fraction radiation therapy. Tumors were grown over the thigh in 16 mice in this study, of which 5 served as untreated controls and 11 had their tumors treated to 800 cGy with 200 kVp x-rays. Spectra were acquired within 24 h pre-treatment, and then at 3, 7 and 14 d post-treatment using a 9.4 T animal magnetic resonance (MR) system. For the untreated control tumors, spectra (1-2 per mouse) were acquired at different stages of tumor growth. Spectra were obtained with the PRESS pulse sequence using a 3  ×  3 × 3 mm(3) voxel. Analysis was performed with the LCModel software platform. Six metabolites were profiled for this analysis: alanine (Ala), myo-inositol (Ins), taurine (Tau), creatine and phosphocreatine (Cr + PCr), glutamine and glutamate (Glu + Gln), and total choline (glycerophosphocholine + phosphocholine) (GPC + PCh). For the treated cohort, most metabolite/water concentration ratios were found to decrease in the short term at 3 and 7 d post-treatment, followed by an increase at 14 d post-treatment toward pre-treatment values. The lowest concentrations were observed at 7 d post-treatment, with magnitudes (relative to pre-treatment concentration ratios) of: 0.42  ±  24.6% (Ala), 0.43  ±  15.3% (Ins), 0.68  ±  27.9% (Tau), 0.52  ±  14.6% (GPC+PCh), 0.49  ±  21.0% (Cr + PCr) and 0.78  ±  24.5% (Glu + Gln). Control animals did not demonstrate any significant correlation between tumor volume and metabolite concentration, indicating that the observed kinetics were the result of the therapeutic intervention. We have demonstrated the feasibility of using MRS to follow multiple metabolic markers over time for the purpose of evaluating therapeutic response of tumors to radiation therapy. This study provides supporting evidence that metabolite/water concentration ratios have the potential to be used as biomarkers for the assessment of the response to therapy.

Proton T2 measurement and quantification of lactate in brain tumors by MRS at 3 Tesla in vivo

PURPOSE

To evaluate the T2 relaxation time of lactate (Lac) in brain tumors and the correlation of the T2 and concentration with tumor grades.

METHODS

Eight pairs of the subecho time sets of point-resolved spectroscopy were selected between 58 and 268 ms, with numerical and phantom analyses, for Lac T2 measurement. In vivo spectra were acquired from 24 subjects with gliomas (13 low grade and 11 high grade) and analyzed with LCModel using numerically-calculated basis spectra. The metabolite T2 relaxation time was obtained from monoexponential fitting of the multi-echo time (TE) signal estimates versus TE. The metabolite concentration was estimated from the zero-TE extrapolation of the T2 fits.

RESULTS

The Lac T2 was estimated to be approximately 240 ms, without a significant difference between low and high grade tumors. The Lac concentration was estimated to be 4.1 ± 3.4 and 7.0 ± 4.7 mM for low and high grades respectively, but the difference was not significant.

CONCLUSION

The Lac T2 was similar among gliomas regardless of their tumor grades. This suggests that the T2 value from this study may be applicable to obtain the T2 relaxation-free estimates of Lac in a subset of brain tumors.

Contributions of magnetic resonance spectroscopy to understanding development: potential applications in the study of adolescent alcohol use and abuse

A growing body of research has documented structural and functional brain development during adolescence, yet little is known about neurochemical changes that occur during this important developmental period. Magnetic resonance spectroscopy (MRS) is a well-developed technology that permits the in vivo quantification of multiple brain neurochemicals relevant to neuronal health and functioning. However, MRS technology has been underused in exploring normative developmental changes during adolescence and the onset of alcohol and drug use and abuse during this developmental period. This review begins with a brief overview of normative cognitive and neurobiological development during adolescence, followed by an introduction to MRS principles. The subsequent sections provide a comprehensive review of the existing MRS studies of development and cognitive functioning in healthy children and adolescents. The final sections of this article address the potential application of MRS in identifying neurochemical predictors and consequences of alcohol use and abuse in adolescence. MRS studies of adolescent populations hold promise for advancing our understanding of neurobiological risk factors for psychopathology by identifying the biochemical signatures associated with healthy brain development, as well as neurobiological and cognitive correlates of alcohol and substance use and abuse.

Lipid and macromolecules quantitation in differentiating glioblastoma from solitary metastasis: a short-echo time single-voxel magnetic resonance spectroscopy study at 3 T

OBJECTIVE

The differentiation between solitary metastasis (MET) and glioblastoma (GBM) is difficult using only magnetic resonance imaging techniques. Magnetic resonance spectroscopy (MRS) lipid signal indicates cellular necrosis both in GBMs and METs. The purpose of this prospective study was to determine whether a class of lipids and/or macromolecules (MMs), able to efficiently discriminate between these two types of lesions, exists.

METHODS

Forty-one patients with solitary brain tumor (23 GBMs and 18 METs) underwent magnetic resonance imaging and single-voxel MRS. Short-echo time point resolved spectroscopy sequence acquisition with water suppression technique was used. Spectra were analyzed using LCModel. Absolute quantification was performed with "water-scaling" procedure. The analysis was focused on sums of lipid and macromolecular (LM) components at 0.9 and 1.3 ppm.

RESULTS

The LM13 absolute concentration was statistically different (P < 0.0001) between GBMs and METs. With a cutoff of 81 mM in LM13 absolute concentration, METs and GBMs can be distinguished with a 78% of specificity and an 81% of sensitivity. The presence of the MM12 peak, related to the fucose II complex, in tumors harboring a K-ras gene mutation has been investigated.

CONCLUSIONS

We exploited the performance of a clinically easily implementable method, such as short-echo time single-voxel MRS, for the differentiation between brain metastasis and primary brain tumors. The study showed that MRS absolute lipid and macromolecular signals could be helpful in differentiating GBM from metastasis. LM13 class was found to be a discriminant parameter with an accuracy of 85%. Detection of the MM12-fucose peak may also have a role in understanding molecular biology of brain metastasis and should be further investigated to address specific metabolic phenotypes.

Robust discrimination of glioblastomas from metastatic brain tumors on the basis of single-voxel (1)H MRS

This article investigates methods for the accurate and robust differentiation of metastases from glioblastomas on the basis of single-voxel (1)H MRS information. Single-voxel (1)H MR spectra from a total of 109 patients (78 glioblastomas and 31 metastases) from the multicenter, international INTERPRET database, plus a test set of 40 patients (30 glioblastomas and 10 metastases) from three different centers in the Barcelona (Spain) metropolitan area, were analyzed using a robust method for feature (spectral frequency) selection coupled with a linear-in-the-parameters single-layer perceptron classifier. For the test set, a parsimonious selection of five frequencies yielded an area under the receiver operating characteristic curve of 0.86, and an area under the convex hull of the receiver operating characteristic curve of 0.91. Moreover, these accurate results for the discrimination between glioblastomas and metastases were obtained using a small number of frequencies that are amenable to metabolic interpretation, which should ease their use as diagnostic markers. Importantly, the prediction can be expressed as a simple formula based on a linear combination of these frequencies. As a result, new cases could be straightforwardly predicted by integrating this formula into a computer-based medical decision support system. This work also shows that the combination of spectra acquired at different TEs (short TE, 20-32 ms; long TE, 135-144 ms) is key to the successful discrimination between glioblastomas and metastases from single-voxel (1)H MRS.

Metabolomics of human breast cancer: new approaches for tumor typing and biomarker discovery

Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.

In vivo characterization of several rodent glioma models by 1H MRS

The assessment of metabolites by (1)H MRS can provide information regarding glioma growth, and may be able to distinguish between different glioma models. Rat C6, 9 L/LacZ, F98 and RG2, and mouse GL261, cells were intracerebrally implanted into the respective rodents, and human U87 MG cells were implanted into athymic rats. Ethyl-nitrosourea induction was also used. Glioma metabolites [e.g. total choline (tCho), total creatine (tCr), N-acetylaspartate (NAA), lactate (Lac), glutamine (Gln), glutamate (Glu), aspartate (Asp), guanosine (Gua), mobile lipids and macromolecules (MMs)] were assessed from (1)H MRS using point-resolved spectroscopy (PRESS) [TE = 24 ms; TR = 2500 ms; variable pulse power and optimized relaxation delay (VAPOR) water suppression; 27-μL and 8-μL voxels in rats and mice, respectively] at 7 T. Alterations in metabolites (Totally Automatic Robust Quantitation in NMR, TARQUIN) in tumors were characterized by increases in lipids (Lip1.3: 8.8-54.5 mM for C6 and GL261) and decreases in NAA (1.3-2.0 mM for RG2, GL261 and C6) and tCr (0.8-4.0 mM for F98, RG2, GL261 and C6) in some models. F98, RG2, GL261 and C6 models all showed significantly decreased (p < 0.05) tCr, and RG2, GL261 and C6 models all exhibited significantly decreased (p < 0.05) NAA. The RG2 model showed significantly decreased (p < 0.05) Gln and Glu, the C6 model significantly decreased (p < 0.05) Asp, and the F98 and U87 models significantly decreased (p < 0.05) Gua, compared with controls. The GL261 model showed the greatest alterations in metabolites. (1)H MRS was able to differentiate the metabolic profiles in many of the seven rodent glioma models assessed. These models are considered to resemble certain characteristics of human glioblastomas, and this study may be helpful in selecting appropriate models.

Five-Year Longitudinal MRI Follow-up and (1)H Single Voxel MRS in 14 patients with Gliomatosis Treated with Temodal, Radiotherapy and Antiangiogenic Therapy

Gliomatosis cerebri (GC) is a challenging tumor, considered to have a poor prognosis and poor response to treatments. The purpose of this study is to better understand glial tumor metabolism and post chemotherapy, radiotherapy and antiangiogenic variations in a longitudinal study to determine cerebral variation in MRS area, amplitude, and ratios of metabolites and spectral profiles during a five year longitudinal follow-up in 14 patients with gliomatosis without initial hyperperfusion and treated with chemotherapy (Temozolomide (Temodal(®))), radiotherapy and subsequent antiangiogenic therapy. The study also aimed to detect changes in infiltration, proliferation, lipids or glycolytic metabolism, as these changes could be monitored longitudinally in humans with glial brain tumors (low and high grade) after therapy, using conventional magnetic resonance imaging (MRI), spectroscopy (MRS) and MR perfusion. Most patients had first initial clinical and MRS improvement and stable MRI. After 12 to 24 chemotherapy treatment cycles MRS usually showed an increase in the Cho/Cr ratio (proliferation) and sometimes contrast enhancements. Later, the patients showed clinical deterioration and radiotherapy was started. There was an improvement with radiotherapy that lasted nine to 18 months. This was followed by a worsening that led to try antiangiogenic therapy. Later in the evolution for three patients with hyperperfusion this symptom disappeared, but proliferation, infiltration and glycolytic metabolism remained at a high level. Spectroscopic and metabolic changes often occur well before clinical deterioration and sometimes before improvement. Therefore, MRS could be more sensitive and could detect changes earlier than MRI and is sometimes predictive. Despite the difficulty, the variability and unknown factors, these repeated measurements give us a better insight into the nature of the different processes, tumor progression and could lead to better understanding of therapeutic response.

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.

Linear discriminant analysis of brain tumour (1)H MR spectra: a comparison of classification using whole spectra versus metabolite quantification

(1)H MRS is an attractive choice for non-invasively diagnosing brain tumours. Many studies have been performed to create an objective decision support system, but there is not yet a consensus as to the best techniques of MRS acquisition or data processing to be used for optimum classification. In this study, we investigate whether LCModel analysis of short-TE (30 ms), single-voxel tumour spectra provide a better input for classification than the use of the original spectra. A total of 145 histologically diagnosed brain tumour spectra were acquired [14 astrocytoma grade II (AS2), 15 astrocytoma grade III (AS3), 42 glioblastoma (GBM), 41 metastases (MET) and 33 meningioma (MNG)], and linear discriminant analyses (LDA) were performed on the LCModel analysis of the spectra and the original spectra. The results consistently suggest improvement in classification when the LCModel concentrations are used. LDA of AS2, MNG and high-grade tumours (HG, comprising GBM and MET) correctly classified 94% using the LCModel dataset compared with 93% using the spectral dataset. The inclusion of AS3 reduced the accuracy to 82% and 78% for LCModel analysis and the original spectra, respectively, and further separating HG into GBM and MET gave 70% compared with 60%. Generally MNG spectra have profiles that are visually distinct from those of the other tumour types, but the classification accuracy was typically about 80%, with MNG with substantial lipid/macromolecule signals being classified as HG. Omission of the lipid/macromolecule concentrations in the LCModel dataset provided an improvement in classification of MNG (91% compared with 76%). In conclusion, there appears to be an advantage to performing pattern recognition on the quantitative analysis of tumour spectra rather than using the whole spectra. However, the results suggest that a two-step LDA process may help in classifying the five tumour groups to provide optimum classification of MNG with high lipid/macromolecule contributions which maybe misclassified as HG.

The clinical value of proton magnetic resonance spectroscopy in adult brain tumours

Proton magnetic resonance spectroscopy (1H MRS) non-invasively provides information on the biochemical profile (typically including up to nine metabolites and mobile lipids) of brain tissue, which varies according to the underlying disease process. A number of studies have assessed its accuracy in the diagnosis of adult brain tumours. This article describes the basic principles of 1H MRS, the metabolic profiles of different brain tumours, and practical points to aid interpretation of spectra. The literature is reviewed regarding the role of 1H MRS in the diagnosis of brain tumours and more specifically where it has proven to be of additional benefit over conventional magnetic resonance imaging.

Spectroscopie 1H, perfusion, diffusion : quelle place pour ces techniques lors du diagnostic et du suivi des principales tumeurs cérébrales sus-tentorielles de l’adulte ?

INTRODUCTION

In a few years, magnetic resonance imaging (MRI) has evolved from a morphology-based examination to one that encompasses metabolism and function.

STATE OF ART

MRI is a well-established tool for the initial evaluation of brain tumors, but conventional MR sequences have some limitations. Conventional MRI is unable to distinguish high-grade glioma from metastasis and abscess, to define precisely the histopathological grade of gliomas, to determine exactly the limits of tumor extension, to characterize meningeal tumors. Differentiation of tumor recurrence from treatment-related changes may be difficult with standard MR imaging because the interpretation is essentially based on volume analysis.

PERSPECTIVES

1H Spectroscopy, diffusion and perfusion imaging become possible with the development of MR imagers and can be routinely performed in clinical settings. They give complementary information about tumor metabolism and vascularity and allow a better analysis of post-treatment modifications. Functional and metabolic explorations should be used to characterize brain tumors.

Brain lactate responses during visual stimulation in fasting and hyperglycemic subjects: a proton magnetic resonance spectroscopy study at 1.5 Tesla

Proton magnetic resonance spectroscopy ((1)H-MRS) studies showing increased lactate during neural activation support a broader role for lactate in brain energy metabolism than was traditionally recognized. Proton MRS measures of brain lactate responses have been used to study regional brain metabolism in clinical populations. This study examined whether variations in blood glucose influence the lactate response to visual stimulation in the visual cortex. Six subjects were scanned twice, receiving either saline or 21% glucose intravenously. Using (1)H-MRS at 1.5 Tesla with a long echo time (TE=288 ms), the lactate doublet was visible at 1.32 ppm in the visual cortex of all subjects. Lactate increased significantly from resting to visual stimulation. Hyperglycemia had no effect on this increase. The order of the slice-selective gradients for defining the spectroscopy voxel had a pronounced effect on the extent of contamination by signal originating outside the voxel. The results of this preliminary study demonstrate a method for observing a consistent activity-stimulated increase in brain lactate at 1.5 T and show that variations in blood glucose across the normal range have little effect on this response.

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.

[Proton magnetic resonance spectroscopy (1H-MRS) for the diagnosis of brain tumors and the evaluation of treatment]

MR spectroscopy (MRS) is a technique used to study a few metabolites in the brain or tumors in situ. This technique can provide information on tumor histological type and grade, and is helpful to identify tumor-like lesions, particularly abscesses. MRS can be used for treatment monitoring.

Untreated pediatric primitive neuroectodermal tumor in vivo: quantitation of taurine with MR spectroscopy

PURPOSE

To retrospectively investigate whether quantitation of taurine (Tau) concentrations with proton magnetic resonance (MR) spectroscopy in vivo improves the differentiation of primitive neuroectodermal tumors (PNET) from other common brain tumors in pediatric patients.

MATERIALS AND METHODS

The institutional review board approved this review of clinical data; it was not necessary to obtain parental consent. This study was HIPAA compliant. Single-voxel proton spectroscopy was added to the preoperative MR imaging work-up of 29 patients (12 boys and 17 girls; mean age, 6.5 years +/- 3.5) with untreated brain tumors; 13 had PNETs, and 16 had other tumors. Absolute concentrations (measured in millimoles per kilogram of brain tissue) of metabolites of the proton spectrum were determined. Student t tests were used for statistical comparisons.

RESULTS

Elevated absolute Tau concentration proved to be the most significant metabolite in the differentiation of PNETs from other tumors (6.09 mmol/kg +/- 2.24 vs 0.76 mmol/kg +/- 0.95, P < .001). PNETs also exhibited a higher ratio of Tau relative to choline (1.21 +/- 0.48 vs 0.28 +/- 0.39, P < .001), a higher ratio of Tau relative to creatine (1.28 +/- 0.44 vs 0.38 +/- 0.67, P < .001), a reduced a ratio of N-acetyl-aspartate relative to choline (0.20 +/- 0.20 vs 0.79 +/- 0.56, P < .001), and an increased choline concentration (5.30 mmol/kg +/- 1.64 vs 3.08 mmol/kg +/- 2.53, P < .05). Tau concentrations ranged from 2.62 to 11.15 mmol/kg in individual patients with a PNET.

CONCLUSION

Single-voxel quantitative (1)H MR spectroscopy performed in patients with untreated pediatric brain tumors showed that the Tau concentration was significantly elevated in PNETs and was useful in the differentiation of PNETs from other tumors.

Detection and differentiation of lactate and lipids by single-voxel proton MR spectroscopy

The signals of lactate and lipids partially overlap in single-voxel proton MR spectroscopy (1HMRS), sometimes making them difficult to differentiate in clinical settings. Our aim in this study was to identify lactate and lipids by varying the echo time (TE). We expect that the accurate detection of lactate and lipids will have high diagnostic value in the diagnosis of brain tumors. Following our protocol, we obtained meaningful 1HMRS spectra from 213 patients, including 163 patients with brain tumors, between August 1999 and February 2004. 1HMRS was performed with a TE of 144 ms followed by a TE of 30 ms and/or a TE of 288 ms, if necessary. For the 213 patients, lactate level was "negative" in 47 patients, "positive" in 131 patients, and "strongly positive" in 35 patients. The lipid level was "negative" in 90 patients, "positive" in 56 patients, and "strongly positive" in 67 patients. Based on logistic discriminant analyses of neuro-epithelial tumor WHO grade and lactate and lipid levels, lactate and lipid levels were significant between WHO grades 2 and 3 (P=0.0239) and between grades 3 and 4 (P=0.0347). Lipids are a more significant factor for the discrimination between WHO grades 2 and 3 (P=0.0073) and between grades 3 and 4 (P=0.0048). With our method of varying the TE, it is possible accurately and efficiently to detect lactate and lipids in the brain. We found a significant correlation between lactate and lipid expression and WHO grade of neuro-epithelial tumors.

Differentiation of metastases from high-grade gliomas using short echo time 1H spectroscopy

PURPOSE

To determine if short echo time (TE) (1)H magnetic resonance spectroscopy (MRS) can distinguish between intracranial metastases and glioblastomas.

MATERIALS AND METHODS

TE 30-msec spectra were acquired (1.5 T) from voxels entirely within tumors from 23 glioblastoma patients and 24 metastases patients (3 breast carcinomas, 1 bladder carcinoma, 8 lung carcinomas, 3 probable lung carcinomas, 6 melanomas, 1 stomach carcinoma, and 2 undetermined). Spectra were analyzed quantitatively (LCModel) to determine metabolite, lipid, and macromolecule concentrations. All tumors were previously untreated and classified histopathologically.

RESULTS

The lipid peak area (LPA) ratio (total peak area at ca. delta1.3 to that at ca. delta0.9) was 2.6 +/- 0.6 (N = 25) for glioblastomas and 3.8 +/- 1.4 (N = 34) for metastases (P < 0.0001). There were no significant differences in metabolite or lipid concentrations between the tumor groups. The LPA ratio provided 80% sensitivity and 80% specificity for discriminating metastases from glioblastomas.

CONCLUSION

Lipid and macromolecule (LM) signals can dominate (1)H spectra of high-grade tumors and have characteristics that allow significant discrimination of metastases from glioblastomas. Work is now needed to determine the source and biophysical characteristics of these LM signals to further improve differentiation by optimizing the data acquisition and analysis protocol.

Quantitation of simulated short echo time1H human brain spectra by LCModel and AMARES

LCModel and AMARES, two widely used quantitation tools for magnetic resonance spectroscopy (MRS) data, were employed to analyze simulated spectra similar to those typically obtained at short echo times (TEs) in the human brain at 1.5 T. The study focused mainly on the influence of signal-to-noise ratios (SNRs) and different linewidths on the accuracy and precision of the quantification results, and their effectiveness in accounting for the broad signal contribution of macromolecules and lipids (often called the baseline in in vivo MRS). When applied in their standard configuration (i.e., fitting a spline as a baseline for LCModel, and weighting the first data points for AMARES), both methods performed comparably but with their own characteristics. LCModel and AMARES quantitation benefited considerably from the incorporation of baseline information into the prior knowledge. However, the more accurate quantitation of the sum of glutamate and glutamine (Glx) favored the use of LCModel. Metabolite-to-creatine ratios estimated by LCModel with extended prior knowledge are more accurate than absolute concentrations, and are nearly independent of SNR and line broadening.

Proton magnetic resonance spectroscopy: clinical applications in patients with brain lesions

CONTEXT

Proton spectroscopy has been recognized as a safe and noninvasive diagnostic method that, coupled with magnetic resonance imaging techniques, allows for the correlation of anatomical and physiological changes in the metabolic and biochemical processes occurring within previously-determined volumes in the brain. There are two methods of proton magnetic resonance spectroscopy: single voxel and chemical shift imaging.

OBJECTIVE

The present work focused on the clinical applications of proton magnetic resonance spectroscopy in patients with brain lesions.

CONCLUSIONS

In vivo proton spectroscopy allows the detection of certain metabolites in brain tissue, such as N-acetyl aspartate, creatine, choline, myoinositol, amino acids and lipids, among others. N-acetyl aspartate is a neuronal marker and, as such, its concentration will decrease in the presence of aggression to the brain. Choline increase is the main indicator of neoplastic diseases. Myoinositol is raised in patients with Alzheimer's disease. Amino acids are encountered in brain abscesses. The presence of lipids is related to necrotic processes.

The role of relaxation time corrections for the evaluation of long and short echo time 1H MR spectra of the hippocampus by NUMARIS and LCModel techniques

1H MR spectroscopy is routinely used for lateralization of epileptogenic lesions. The present study deals with the role of relaxation time corrections for the quantitative evaluation of long (TE=135 ms) and short echo time (TE=10 ms) 1H MR spectra of the hippocampus using two methods (operator-guided NUMARIS and LCModel programs). Spectra of left and right hippocampi of 14 volunteers and 14 patients with epilepsy were obtained by PRESS (TR/TE=5000/135 ms) and STEAM (TR/TE=5000/10 ms) sequences with a 1.5-T imager. Evaluation was carried out using Siemens NUMARIS software and the results were compared with data from LCModel processing software. No significant differences between the two methods of processing spectra with TE=135 ms were found. The range of relaxation corrections was determined. Metabolite concentrations in hippocampi calculated from spectra with TE=135 ms and 10 ms after application of correction coefficients did not differ in the range of errors and agreed with published data (135 ms/10 ms: NAA=10.2+/-0.6/10.4+/-1.3 mM, Cho=2.4+/-0.1/2.7+/-0.3 mM, Cr=12.2+/-1.3/11.3+/-1.3 mM). When relaxation time corrections were applied, quantitative results from short and long echo time evaluation with LCModel were in agreement. Signal intensity ratios obtained from long echo time spectra by NUMARIS operator-guided processing also agreed with the LCModel results.

Differentiating primary central nervous system lymphoma from glioma in humans using localised proton magnetic resonance spectroscopy

In order to characterise primary central nervous system lymphomas (PCNSL) and to evaluate if 1H spectroscopy improves the preoperative differential diagnosis of PCNSL and glioma, seven immunocompetent patients with PCNSL and 21 patients with glioma were examined using single voxel, short echo time magnetic resonance spectroscopy (MRS; 1.5 T, STEAM 1500/20). All PCNSL demonstrated massively elevated lipid resonances and markedly elevated choline. Similarly increased lipid resonances were only found in seven necrotic glioblastomas, PCNSL differing from all solid astrocytomas by massively elevated lipid resonances. Additionally, PCNSL had higher Cho/Cr ratios than all grades of astrocytoma. In conclusion, we found that massively elevated lipid resonances are a hallmark of PCNSL in immunocompetent patients. Together with a markedly elevated Cho/Cr ratio, MRS provides metabolic information which may improve the preoperative differentiation of PCNSL and glioma.

1H MR spectroscopy of brain tumours and masses

Accurate diagnosis is essential for optimum management and treatment of patients with brain tumours. Proton magnetic resonance spectroscopy ((1)H MRS) provides information non-invasively on tumour biochemistry and has been shown to provide important additional information to that obtained by conventional radiology. We review the current status of (1)H MRS in classifying brain tumour type and grade, for monitoring response to therapy and progression to higher grade, and as a molecular imaging technique for determining tumour extent for treatment planning.

Volume-selective 1H MR spectroscopy for in vivo detection of valproate in patients with epilepsy

We performed volume-selective 1H MR spectroscopy (1H-MRS) on 12 patients on valproate monotherapy to detect valproate in vivo in the brain. We also acquired reference valproate spectra in vitro in subphysiological 15 g/l albumin solution in saline, in which valproate showed two resonance peaks at 0.7 and 1.2 ppm and a minimum detection threshold of 240 mg/l. In vivo 1H-MRS spectra in brain showed peaks between 0.6 and 1.6 ppm. Simultaneous serum valproate concentrations did not correlate with these integrated MRS peaks. On follow-up, changes in these signals also did not correlate with increasing serum valproate levels. The inconsistency of in vivo 1H-MRS signals at varying serum levels and the high detection levels in vitro suggest that valproate signals are missed in vivo because valproate is metabolised or strongly bound, presumably to brain macromolecules.

Detection of elevated glutathione in meningiomas by quantitative in vivo 1H MRS

Glutathione has major roles in removing free radicals and toxins from normal tissues, but its presence in tumor cells hinders the effectiveness of many anticancer therapies. Analysis of short echo time brain tumor (1)H spectra at 1.5 T using a linear combination of metabolite spectra (LCModel) suggested a significant contribution of glutathione to meningioma spectra. By in vivo MRS (TE = 30 ms, TR = 2020 ms), reduced glutathione was found to be significantly elevated in meningiomas (3.3 +/- 1.5 mM, Mann Whitney, P < 0.005) compared to normal white matter (1.2 +/- 0.15 mM) and low-grade gliomas (1.0 +/- 0.26 mM), in agreement with published histofluorescence studies of tumor biopsies. Glx concentrations were also found to be elevated in meningiomas compared to astrocytomas or normal white matter, indicative of metabolic differences. The ability to noninvasively quantify reduced glutathione in vivo may aid selection of treatment therapies and also provide an indication of tumor aggressiveness.

Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy

Proton spectroscopy can noninvasively provide useful information on brain tumor type and grade. Short- (30 ms) and long- (136 ms) echo time (TE) (1)H spectra were acquired from normal white matter (NWM), meningiomas, grade II astrocytomas, anaplastic astrocytomas, glioblastomas, and metastases. Very low myo-Inositol ([mI]) and creatine ([Cr]) were characteristic of meningiomas, and high [mI] characteristic of grade II astrocytomas. Tumor choline ([Cho]) was greater than NWM and increased with grade for grade II and anaplastic astrocytomas, but was highly variable for glioblastomas. Higher [Cho] and [Cr] correlated with low lipid and lactate (P < 0.05), indicating a dilution of metabolite concentrations due to necrosis in high-grade tumors. Metabolite peak area ratios showed no correlation with lipids and mI/Cho (at TE = 30 ms), and Cr/Cho (at TE = 136 ms) best correlated with tumor grade. The quantified lipid, macromolecule, and lactate levels increased with grade of tumor, consistent with progression from hypoxia to necrosis. Quantification of lipids and macromolecules at short TE provided a good marker for tumor grade, and a scatter plot of the sum of alanine, lactate, and delta 1.3 lipid signals vs. mI/Cho provided a simple way to separate most tumors by type and grade.

Parameterized evaluation of macromolecules and lipids in proton MR spectroscopy of brain diseases

Short echo time (TE) proton MR spectra of the brain include signals of several metabolites as well as macromolecules. In various pathologies, such as brain tumors and multiple sclerosis (MS), the presence of mobile lipids or pathologically altered macromolecules may provide useful additional diagnostic information. A reliable quantitation of these resonances, however, is often not possible due to the lack of adequate prior knowledge. Furthermore, even if advanced fitting procedures are used, a reliable evaluation of metabolites in the presence of pathological lipids or macromolecules often fails if the latter are omitted in the spectral evaluation. In this study, a method is presented for the simultaneous evaluation of all visible components, including metabolites, lipids, and macromolecules, by the use of the fitting procedure LCModel. A standard basis set of brain metabolites was extended by inclusion of parameterized components for macromolecules and lipids that were derived from metabolite-nulled in vivo spectra of normal brain and high-grade gliomas, respectively. The improved spectral quantitation is demonstrated in glial brain tumors and MS lesions as well as in normal brain. It is pointed out that both macromolecules and lipids must be included to provide a proper spectral evaluation.