The osteoarthritis bone score (OABS): a new histological scoring system for the characterisation of bone marrow lesions in osteoarthritis.

OBJECTIVES: Bone marrow lesions (BMLs) are associated with pain in osteoarthritis (OA), but histological scores for OA focus on cartilage pathology. We developed a new scoring system, the Osteoarthritis Bone Score (OABS), to characterise OA-related BMLs. METHODS: BML/non-BML tissues identified by Magnetic Resonance Imaging (MRI) in 10 knee OA subjects were harvested at total knee replacement (TKR). Osteochondral tissue from a further 140 TKR and 23 post-mortem (PM) cases was assessed. Histological features distinguishing MRI-defined BML/non-BML tissues on qualitative analysis were classified as present (0) or absent (1), summated for the OABS, validated by Rasch analysis and sensitivity to distinguish between sample groups. Immunohistochemistry for PGP9.5 assessed innervation. RESULTS: Subchondral characteristics associated with BML tissues were cysts, fibrosis, hypervascularity, cartilage islands, trabecular thickening, loss of tidemark integrity and inflammatory cell infiltration. PGP9.5 immunoreactive perivascular nerves were associated with BMLs. OABS performed well as a measurement tool, displayed good reliability (Cronbach alpha = 0.68), had a 2-factor structure (trabecular/non-trabecular), with moderate correlation between the two factors (r = 0.56, 95% CI 0.46, 0.65). OABS scores were higher in TKR than PM cases with chondropathy, median difference 1.5 (95% CI -2, 0). OABS and Mankin scores similarly distinguished TKR from non-OA controls, but only OABS was higher in BML than non-BML tissues, median difference -4 (95% CI -5 to -2). CONCLUSIONS: OABS identifies and validly quantifies histopathological changes associated with OA BMLs. Histopathology underlying BMLs may represent 2 inter-related pathological processes affecting trabecular/non-trabecular structures. Increased vascularity/perivascular innervation in BMLs might contribute to pain.

Delineation of gliomas using radial metabolite indexing.

(1) H MRSI has demonstrated the ability to characterise and delineate brain tumours, but robust data analysis methods are still needed. In this study, we present an objective analysis method for MRSI data to delineate tumour abnormality regions. The presented method is a development of the choline-to-N-acetylaspartate index (CNI), which uses perpendicular distances in a choline versus N-acetylaspartate plot as a measure of abnormality. We propose a radial CNI (rCNI) method that uses the choline to N-acetylaspartate ratio directly as an abnormality measure. To avoid problems with small or zero denominators, we perform an arctangent transformation. CNI abnormality contours were evaluated using a z-score threshold of 2 (CNI2) and 2.5 (CNI2.5) and compared with rCNI2. Simulations modelling low-grade (LGG) and high-grade (HGG) gliomas with different tissue compartments and partial volume effects suggest improved specificity of rCNI2 (LGG 92%/HGG 91%) over CNI2 (LGG 69%/HGG 69%) and CNI2.5 (LGG 74%/HGG 75%), whilst retaining a similar sensitivity to both CNI2 and CNI2.5. Our simulation results also confirm a previously reported increase in specificity of CNI2.5 over CNI2 with little penalty in sensitivity. The analysis of MRSI data acquired from 10 patients with low-grade glioma at 3 T suggests a more robust delineation of the lesions using rCNI with respect to conventional imaging compared with standard CNI. Further analysis of 29 glioma datasets acquired at 1.5 T, together with previously published estimated tumour proportions, suggests that rCNI has higher sensitivity and specificity for the identification of abnormal MRSI voxels.

Quantitative evaluation of MRI and histological characteristics of the 5xFAD Alzheimer mouse brain.

Assessment of ß-amyloid (Aß) plaque load in Alzheimer's disease by MRI would provide an important biomarker to monitor disease progression or treatment response. Alterations in tissue structure caused by the presence of Aß may cause localised changes that can be detected by quantitative T1 and T2 relaxation time measurements averaged over larger areas of tissue than that of individual plaques. We constructed depth profiles of the T1 and T2 relaxation times of the cerebral cortex with subjacent white matter and hippocampus in six 5xFAD transgenic and six control mice at 11 months of age. We registered these profiles with corresponding profiles of three immunohistochemical markers: ß-amyloid; neuron-specific nuclear protein (NeuN), a marker of neuronal cell load; and myelin basic protein (MBP), a marker of myelin load. We found lower T1 in the 5xFAD transgenic mice compared to wild type control mice at all depths, with maximum sensitivity for detection at specific layers. T1 negatively correlated with Aß staining intensity in the 5xFAD mice which had no changes in NeuN and MBP staining compared to wild type mice. We postulate that these relaxation time changes are due to the presence of ß-amyloid in the transgenic mice. It may be clinically feasible to develop a similar layered analysis protocol as a biomarker for Alzheimer's disease in humans.

Classification of single-voxel 1H spectra of brain tumours using LCModel.

This study presents a novel method for the direct classification of (1)H single-voxel MR brain tumour spectra using the widespread analysis tool LCModel. LCModel is designed to estimate individual metabolite proportions by fitting a linear combination of in vitro metabolite spectra to an in vivo MR spectrum. In this study, it is used to fit representations of complete tumour spectra and to perform a classification according to the highest estimated tissue proportion. Each tumour type is represented by two spectra, a mean component and a variability term, as calculated using a principal component analysis of a training dataset. In the same manner, a mean component and a variability term for normal white matter are also added into the analysis to allow a mixed tissue approach. An unbiased evaluation of the method is carried out through the automatic selection of training and test sets using the Kennard and Stone algorithm, and a comparison of LCModel classification results with those of the INTERPRET Decision Support System (IDSS) which incorporates an advanced pattern recognition method. In a test set of 46 spectra comprising glioblastoma multiforme, low-grade gliomas and meningiomas, LCModel gives a classification accuracy of 90% compared with an accuracy of 95% by IDSS.

Blood-brain barrier permeability is increased in normal-appearing white matter in patients with lacunar stroke and leucoaraiosis.

BACKGROUND AND AIM: The pathogenesis of cerebral small-vessel disease (SVD) is incompletely understood. Endothelial dysfunction has been implicated and may result in increased blood-brain barrier (BBB) permeability with leakage of blood constituents into the vessel wall and white matter. We used contrast-enhanced MRI to determine whether there was any evidence for BBB permeability in the white matter of patients with SVD, and whether this was present not only in areas of leucoaraiosis (white-matter lesions) but also in normal-appearing white matter (NAWM). METHODS: Subjects underwent T1 volumetric MRI before and after bolus injection of contrast. Scanning was continued for 30 min postinjection to determine the contrast-enhancement time course. The mean signal intensity change was plotted against time to calculate the area under the curve values, a parameter related to BBB permeability. Automated brain segmentation and regions of interest analysis were performed to determine 'permeability' in different brain compartments. RESULTS: Compared with controls (n=15), the SVD patient group (n=24) had signal changes consistent with increased BBB permeability in NAWM (p=0.033). Multivariate regression analyses identified leucoaraiosis grade as an independent predictor of these permeability related signal changes in NAWM after adjustment for age, gender, weight, brain volume, area under the curve in the internal carotid arteries and cardiovascular risk factors. CONCLUSION: This study provides evidence for increased BBB permeability in SVD, and this is particularly seen in SVD with leucoaraiosis. Its presence in NAWM would be consistent with it playing a causal role in disease pathophysiology.

Pattern recognition of MRSI data shows regions of glioma growth that agree with DTI markers of brain tumor infiltration.

Gliomas are the most common primary brain tumors and the majority are highly malignant, with one of the worst prognoses for patients. Gliomas are characterized by invasive growth into normal brain tissue that makes complete surgical resection and accurate radiotherapy planning extremely difficult. We have performed independent component analysis of magnetic resonance spectroscopy imaging data from human gliomas to segment brain tissue into tumor core, tumor infiltration, and normal brain, with confirmation by diffusion tensor imaging analysis. Our data are consistent with previous studies that compared anomalies in isotropic and anisotropic diffusion images to determine regions of potential glioma infiltration. We show that coefficients of independent components can be used to create colored images for easy visual identification of regions of infiltrative tumor growth.

Taurine: a potential marker of apoptosis in gliomas.

New cancer therapies are being developed that trigger tumour apoptosis and an in vivo method of apoptotic detection and early treatment response would be of great value. Magnetic resonance spectroscopy (MRS) can determine the tumour biochemical profile in vivo, and we have investigated whether a specific spectroscopic signature exists for apoptosis in human astrocytomas. High-resolution magic angle spinning (HRMAS) (1)H MRS provided detailed (1)H spectra of brain tumour biopsies for direct correlation with histopathology. Metabolites, mobile lipids and macromolecules were quantified from presaturation HRMAS (1)H spectra acquired from 41 biopsies of grades II (n=8), III (n=3) and IV (n=30) astrocytomas. Subsequently, TUNEL and H&E staining provided quantification of apoptosis, cell density and necrosis. Taurine was found to significantly correlate with apoptotic cell density (TUNEL) in both non-necrotic (R=0.727, P=0.003) and necrotic (R=0.626, P=0.0005) biopsies. However, the ca 2.8 p.p.m. polyunsaturated fatty acid peak, observed in other studies as a marker of apoptosis, correlated only in non-necrotic biopsies (R=0.705, P<0.005). We suggest that the taurine (1)H MRS signal in astrocytomas may be a robust apoptotic biomarker that is independent of tumour necrotic status.

The relationship between white matter brain metabolites and cognition in normal aging: the GENIE study.

Magnetic resonance spectroscopy (MRS) has demonstrated age-related changes in brain metabolites that may underlie micro-structural brain changes, but few studies have examined their relationship with cognitive decline. We performed a cross-sectional study of brain metabolism and cognitive function in 82 healthy adults (aged 50-90) participating in the GENIE (St GEorge's Neuropsychology and Imaging in the Elderly) study. Absolute metabolite concentrations were measured by proton chemical shift imaging within voxels placed in the centrum semiovale white matter. Cognitive abilities assessed were executive function, working memory, information processing speed, long-term memory and fluid intelligence. Correlations showed that all cognitive domains declined with age. Total creatine (tCr) concentration increased with age (r=0.495, p<0.001). Regression analyses were performed for each cognitive variable, including estimated intelligence and the metabolites, with age then added as a final step. A significant relationship was observed between tCr and executive function, long-term memory, and fluid intelligence, although these relationships did not remain significant after age was added as a final step in the regression. The regression analysis also demonstrated a significant relationship between N-acetylaspartate (NAA) and executive function. As there was no age-related decline in NAA, this argues against axonal loss with age; however the relationship between NAA and executive function independent of age and estimated intelligence is consistent with white matter axonal integrity having an important role in executive function in normal individuals.

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.

In vivo 31P MR spectral patterns and reproducibility in cancer patients studied in a multi-institutional trial.

The standardization and reproducibility of techniques required to acquire anatomically localized 31P MR spectra non-invasively while studying tumors in cancer patients in a multi-institutional group at 1.5 T are reported. This initial group of patients was studied from 1995 to 2000 to test the feasibility of acquiring in vivo localized 31P MRS in clinical MR spectrometers. The cancers tested were non-Hodgkin's lymphomas, sarcomas of soft tissue and bone, breast carcinomas and head and neck carcinomas. The best accrual and spectral quality were achieved with the non-Hodgkin's lymphomas. The initial analysis of the spectral values of the sum of phosphoethanolamine plus phosphocholine normalized by the content of nucleotide triphosphates in a homogeneous sample of 32 NHL patients studied by in vivo (31)P MRS showed good reproducibility among different institutions. No statistical differences were found between the institution with the largest number of cases accrued and the rest of the multi-institutional NHL data (2.28 +/- 0.64, mean +/- standard error; n = 17, vs 2.08 +/- 0.14, n = 15). The preliminary data reported demonstrate that the institutions involved in this trial are obtaining reproducible 31P MR spectroscopic data non-invasively from human tumors. This is a fundamental prerequisite for the international cooperative group to be able to demonstrate the clinical value of the normalized determination of phosphoethanolamine plus phosphocholine by 31P MRS as predictor for treatment response in cancer patients.

White matter damage on diffusion tensor imaging correlates with age-related cognitive decline.

BACKGROUND: Damage to white matter tracts, resulting in "cerebral disconnection," may underlie age-related cognitive decline. METHODS: Using diffusion tensor MRI (DTI) to investigate white matter damage, and magnetic resonance spectroscopy (MRS) to look at its underlying pathologic basis, the authors investigated the relationship between white matter structure and cognition in 106 healthy middle-aged and elderly adults. Fractional anisotropy (FA) and mean diffusivity (MD) values, whole brain white matter histograms, and regions of interest placed in the white matter of the centrum semiovale were analyzed. Correlations with executive function, working memory, and information-processing speed were performed. RESULTS: There was a progressive reduction in FA and increase in diffusivity with age in both region of interest (r = 0.551, p < 0.001), and whole brain histograms (r = 0.625, p < 0.001). DTI values correlated with performance in all three cognitive domains. After controlling for age, DTI parameters correlated with working memory but not with the other two cognitive domains. MRS studies found a correlation of N-acetyl aspartate, a neuronal marker, with DTI parameters (r = 0.253, p < 0.05). CONCLUSION: The results are consistent with white matter damage due to axonal loss, causing age- related cognitive decline. Working memory may be particularly dependent on complex networks dependent on white matter connections.

Methodological standardization for a multi-institutional in vivo trial of localized 31P MR spectroscopy in human cancer research. In vitro and normal volunteer studies.

A multi-institutional group has been created to demonstrate the utility of in vivo 31P magnetic resonance spectroscopy (31P-MRS) to study human cancers in vivo. This review is concerned with the novel problems concerning quality control in this large multinational trial of 31P MRS. Our results show that the careful and systematic performance of the quality control tests depicted here (standardized dual 1H/31P tuned radiofrequency probe, quality control procedures, routine use of 1H irradiation while acquiring 31P MR signals) has ensured comparable results between the different institutions. In studies made in vitro, the root-mean-square error was 3.6 %, and in muscle of healthy volunteers in vivo the coefficients of variance for the ratios phosphocreatine/nucleotide-triphosphates, phosphocreatine/noise and nucleotide-triphosphate/noise were 12.2, 7.0 and 10.8 %, respectively. The standardization of the acquisition protocol for in vivo-localized 31P MR spectroscopy across the different institutions has resulted in comparable in vivo data, decreasing the possible problems related to a research study carried out under a multi-institutional setting.

Classification of brain tumours using short echo time 1H MR spectra.

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas (n = 87), meningiomas (n = 57), metastases (n = 39), and astrocytomas grade II (n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Brain tumor classification based on long echo proton MRS signals.

There has been a growing research interest in brain tumor classification based on proton magnetic resonance spectroscopy (1H MRS) signals. Four research centers within the EU funded INTERPRET project have acquired a significant number of long echo 1H MRS signals for brain tumor classification. In this paper, we present an objective comparison of several classification techniques applied to the discrimination of four types of brain tumors: meningiomas, glioblastomas, astrocytomas grade II and metastases. Linear and non-linear classifiers are compared: linear discriminant analysis (LDA), support vector machines (SVM) and least squares SVM (LS-SVM) with a linear kernel as linear techniques and LS-SVM with a radial basis function (RBF) kernel as a non-linear technique. Kernel-based methods can perform well in processing high dimensional data. This motivates the inclusion of SVM and LS-SVM in this study. The analysis includes optimal input variable selection, (hyper-) parameter estimation, followed by performance evaluation. The classification performance is evaluated over 200 stratified random samplings of the dataset into training and test sets. Receiver operating characteristic (ROC) curve analysis measures the performance of binary classification, while for multiclass classification, we consider the accuracy as performance measure. Based on the complete magnitude spectra, automated binary classifiers are able to reach an area under the ROC curve (AUC) of more than 0.9 except for the hard case glioblastomas versus metastases. Although, based on the available long echo 1H MRS data, we did not find any statistically significant difference between the performances of LDA and the kernel-based methods, the latter have the strength that no dimensionality reduction is required to obtain such a high performance.

Effects of dichloroacetate on VO2 and intramuscular 31P metabolite kinetics during high-intensity exercise in humans.

Traditional control theories of muscle O2 consumption are based on an "inertial" feedback system operating through features of the ATP splitting (e.g., [ADP] feedback, where brackets denote concentration). More recently, however, it has been suggested that feedforward mechanisms (with respect to ATP utilization) may play an important role by controlling the rate of substrate provision to the electron transport chain. This has been achieved by activation of the pyruvate dehydrogenase complex via dichloroacetate (DCA) infusion before exercise. To investigate these suggestions, six men performed repeated, high-intensity, constant-load quadriceps exercise in the bore of an magnetic resonance spectrometer with each of prior DCA or saline control intravenous infusions. O2 uptake (Vo2) was measured breath by breath (by use of a turbine and mass spectrometer) simultaneously with intramuscular phosphocreatine (PCr) concentration ([PCr]), [Pi], [ATP], and pH (by 31P-MRS) and arterialized-venous blood sampling. DCA had no effect on the time constant (tau) of either Vo2 increase or PCr breakdown [tauVo2 45.5 +/- 7.9 vs. 44.3 +/- 8.2 s (means +/- SD; control vs. DCA); tauPCr 44.8 +/- 6.6 vs. 46.4 +/- 7.5 s; with 95% confidence intervals averaging < +/-2 s]. DCA, however, resulted in significant (P < 0.05) reductions in 1). end-exercise [lactate] (-1.0 +/- 0.9 mM), intramuscular acidification (pH, +0.08 +/- 0.06 units), and [Pi] (-1.7 +/- 2.1 mM); 2). the amplitude of the fundamental components for [PCr] (-1.9 +/- 1.6 mM) and Vo2 (-0.1 +/- 0.07 l/min, or 8%); and 3). the amplitude of the Vo2 slow component. Thus, although the DCA infusion lessened the buildup of potential fatigue metabolites and reduced both the aerobic and anaerobic components of the energy transfer during exercise, it did not enhance either tauVo2 or tau[PCr], suggesting that feedback, rather than feedforward, control mechanisms dominate during high-intensity exercise.

Tumour dose response to the antivascular agent ZD6126 assessed by magnetic resonance imaging.

ZD6126 is a vascular targeting agent that disrupts the tubulin cytoskeleton of proliferating neo-endothelial cells. This leads to the selective destruction and congestion of tumour blood vessels in experimental tumours, resulting in extensive haemorrhagic necrosis. In this study, the dose-dependent activity of ZD6126 in rat GH3 prolactinomas and murine RIF-1 fibrosarcomas was assessed using two magnetic resonance imaging (MRI) methods. Dynamic contrast-enhanced (DCE) MRI, quantified by an initial area under the time-concentration product curve (IAUC) method, gives values related to tumour perfusion and vascular permeability. Multigradient recalled echo MRI measures the transverse relaxation rate T(2)*, which is sensitive to tissue (deoxyhaemoglobin). Tumour IAUC and R(2)* (=1/T(2)*) decreased post-treatment with ZD6126 in a dose-dependent manner. In the rat model, lower doses of ZD6126 reduced the IAUC close to zero within restricted areas of the tumour, typically in the centre, while the highest dose reduced the IAUC to zero over the majority of the tumour. A decrease in both MRI end points was associated with the induction of massive central tumour necrosis measured histologically, which increased in a dose-dependent manner. Magnetic resonance imaging may be of value in evaluation of the acute clinical effects of ZD6126 in solid tumours. In particular, measurement of IAUC by DCE MRI should provide an unambiguous measure of biological activity of antivascular therapies for clinical trial.

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.