Spectroscopic assessment of alterations in macromolecule and small-molecule metabolites in human brain after stroke

Age-related differences in macromolecular resonances observed in ultra-short-TE STEAM MR spectra at 7T

PURPOSE

To understand how macromolecular content varies in the human brain with age in a large cohort of healthy subjects.

METHODS

In-vivo 1H-MR spectra were acquired using ultra-short TE STEAM at 7T in the posterior cingulate cortex. Macromolecular content was studied in 147 datasets from a cohort ranging in age from 19 to 89 y. Three fitting approaches were used to evaluate the macromolecular content: (1) a macromolecular resonances model developed for this study; (2) LCModel-simulated macromolecules; and (3) a combination of measured and LCModel-simulated macromolecules. The effect of age on the macromolecular content was investigated by considering age both as a continuous variable (i.e., linear regressions) and as a categorical variable (i.e., multiple comparisons among sub-groups obtained by stratifying data according to age by decade).

RESULTS

While weak age-related effects were observed for macromolecular peaks at ˜0.9 (MM09), ˜1.2 (MM12), and ˜1.4 (MM14) ppm, moderate to strong effects were observed for peaks at ˜1.7 (MM17), and ˜2.0 (MM20) ppm. Significantly higher MM17 and MM20 content started from 30 to 40 y of age, while for MM09, MM12, and MM14, significantly higher content started from 60 to 70 y of age.

CONCLUSIONS

Our findings provide insights into age-related differences in macromolecular contents and strengthen the necessity of using age-matched measured macromolecules during quantification.

1H and 31P magnetic resonance spectroscopy reveals potential pathogenic and biomarker metabolite alterations in Lafora disease

Lafora disease is a fatal teenage-onset progressive myoclonus epilepsy and neurodegenerative disease associated with polyglucosan bodies. Polyglucosans are long-branched and as a result precipitation- and aggregation-prone glycogen. In mouse models, downregulation of glycogen synthase, the enzyme that elongates glycogen branches, prevents polyglucosan formation and rescues Lafora disease. Mouse work, however, has not yet revealed the mechanisms of polyglucosan generation, and few in vivo human studies have been performed. Here, non-invasive in vivo magnetic resonance spectroscopy (1H and 31P) was applied to test scan feasibility and assess neurotransmitter balance and energy metabolism in Lafora disease towards a better understanding of pathogenesis. Macromolecule-suppressed gamma-aminobutyric acid (GABA)-edited 1H magnetic resonance spectroscopy and 31P magnetic resonance spectroscopy at 3 and 7 tesla, respectively, were performed in 4 Lafora disease patients and a total of 21 healthy controls (12 for the 1H magnetic resonance spectroscopy and 9 for the 31PMRS). Spectra were processed using in-house software and fit to extract metabolite concentrations. From the 1H spectra, we found 33% lower GABA concentrations (P = 0.013), 34% higher glutamate + glutamine concentrations (P = 0.011) and 24% lower N-acetylaspartate concentrations (P = 0.0043) in Lafora disease patients compared with controls. From the 31P spectra, we found 34% higher phosphoethanolamine concentrations (P = 0.016), 23% lower nicotinamide adenine dinucleotide concentrations (P = 0.003), 50% higher uridine diphosphate glucose concentrations (P = 0.004) and 225% higher glucose 6-phosphate concentrations in Lafora disease patients versus controls (P = 0.004). Uridine diphosphate glucose is the substrate of glycogen synthase, and glucose 6-phosphate is its extremely potent allosteric activator. The observed elevated uridine diphosphate glucose and glucose 6-phosphate levels are expected to hyperactivate glycogen synthase and may underlie the generation of polyglucosans in Lafora disease. The increased glutamate + glutamine and reduced GABA indicate altered neurotransmission and energy metabolism, which may contribute to the disease's intractable epilepsy. These results suggest a possible basis of polyglucosan formation and potential contributions to the epilepsy of Lafora disease. If confirmed in larger human and animal model studies, measurements of the dysregulated metabolites by magnetic resonance spectroscopy could be developed into non-invasive biomarkers for clinical trials.

Macromolecule modelling for improved metabolite quantification using short echo time brain 1 H MRS at 3 T and 7 T: The PRaMM Model

Purpose

To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1 H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints.

Methods

Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared to those other methods was investigated.

Results

The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. While the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p≤0.0001). Minimally detectable changes are in the range 0.5 - 1.9 mM and percent coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out.

Conclusion

Here, the PRaMM model, a method for an improved quantification of metabolites was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids. An improved version of the quantification algorithm QUantitation based on quantum ESTimation (QUEST), with MM prior knowledge (QUEST-MM), dedicated to proton signals and invoking appropriate prior knowledge on MM, is proposed and tested. From a single acquisition, it enables better metabolite quantification, automatic estimation of the background, and additional automatic quantification of MM components, thus improving its applicability in the clinic. The proposed algorithm may facilitate studies that involve patients with pathological MM in the brain. QUEST-MM and three QUEST-based strategies for quantifying short echo time signals are compared in terms of bias-variance trade-off and Cramér-Rao lower bound estimates. The performances of the methods are evaluated through extensive Monte Carlo studies. In particular, the histograms of the metabolite and MM amplitude distributions demonstrate the performances of the estimators. They showed that QUEST-MM works better than QUEST (Subtract approach) and is a good alternative to QUEST when measured MM signal is unavailable or unsuitable. Quantification with QUEST-MM is shown for 1 H in vivo rat brain signals obtained with the SPECIAL pulse sequence at 9.4 T, and human brain signals obtained, respectively, with STEAM at 4 T and PRESS at 3 T. QUEST-MM is implemented in jMRUI and will be available for public use from version 7.1.

Quantitative GABA magnetic resonance spectroscopy as a measure of motor learning function in the motor cortex after subarachnoid hemorrhage

The neural mechanisms underlying gross and fine motor dysfunction after subarachnoid hemorrhage (SAH) remain unknown. The γ-aminobutyric acid (GABA) deficit hypothesis proposes that reduced neuronal GABA concentrations and the subsequent lack of GABA-mediated inhibition cause motor impairment after SAH. This study aimed to explore the correlation between GABA levels and a behavioral measure of motor performance in patients with SAH. Motor cortical GABA levels were assessed in 40 patients with SAH and 10 age-matched healthy controls using proton magnetic resonance spectroscopy. The GABA and N-acetylasparate (NAA) ratio was measured in the normal gray matter within the primary motor cortex. The relationship between GABA concentration and hand-motor performance was also evaluated. Results showed significantly lower GABA levels in patients with SAH's left motor cortex than in controls (GABA/NAA ratio: 0.282 ± 0.085 vs. 0.341 ± 0.031, respectively; p = 0.041). Reaction times (RTs), a behavioral measure of motor performance potentially dependent on GABAergic synaptic transmission, were significantly longer in patients than in controls (936.8 ± 303.8 vs. 440.2 ± 67.3 ms, respectively; p < 0.001). Moreover, motor cortical GABA levels and RTs exhibited a significant positive linear correlation among patients (r = 0.572, rs = 0.327, p = 0.0001). Therefore, a decrease in GABA levels in the primary motor cortex after SAH may lead to impaired cortical inhibition of neuronal function and indicates that GABA-mediated synaptic transmission in the motor cortex is critical for RT.

In vivo imaging of cerebral glucose metabolism informs on subacute to chronic post-stroke tissue status - A pilot study combining PET and deuterium metabolic imaging

Recanalization therapy after acute ischemic stroke enables restoration of cerebral perfusion. However, a significant subset of patients has poor outcome, which may be caused by disruption of cerebral energy metabolism. To assess changes in glucose metabolism subacutely and chronically after recanalization, we applied two complementary imaging techniques, fluorodeoxyglucose (FDG) positron emission tomography (PET) and deuterium (2H) metabolic imaging (DMI), after 60-minute transient middle cerebral artery occlusion (tMCAO) in C57BL/6 mice. Glucose uptake, measured with FDG PET, was reduced at 48 hours after tMCAO and returned to baseline value after 11 days. DMI revealed effective glucose supply as well as elevated lactate production and reduced glutamate/glutamine synthesis in the lesion area at 48 hours post-tMCAO, of which the extent was dependent on stroke severity. A further decrease in oxidative metabolism was evident after 11 days. Immunohistochemistry revealed significant glial activation in and around the lesion, which may play a role in the observed metabolic profiles. Our findings indicate that imaging (altered) active glucose metabolism in and around reperfused stroke lesions can provide substantial information on (secondary) pathophysiological changes in post-ischemic brain tissue.

Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment-based manifold learning

PURPOSE

To develop a manifold learning-based method that leverages the intrinsic low-dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification.

METHODS

A linear tangent space alignment (LTSA) model was proposed to represent MRSI signals. In the proposed model, the signals of each metabolite were represented using a subspace model and the local coordinates of the subspaces were aligned to the global coordinates of the underlying low-dimensional manifold via linear transform. With the basis functions of the subspaces predetermined via quantum mechanics simulations, the global coordinates and the matrices for the local-to-global coordinate alignment were estimated by fitting the proposed LTSA model to noisy MRSI data with a spatial smoothness constraint on the global coordinates and a sparsity constraint on the matrices.

RESULTS

The performance of the proposed method was validated using numerical simulation data and in vivo proton-MRSI experimental data acquired on healthy volunteers at 3T. The results of the proposed method were compared with the QUEST method and the subspace-based method. In all the compared cases, the proposed method achieved superior performance over the QUEST and the subspace-based methods both qualitatively in terms of noise and artifacts in the estimated metabolite concentration maps, and quantitatively in terms of spectral quantification accuracy measured by normalized root mean square errors.

CONCLUSION

Joint spectral quantification using linear tangent space alignment-based manifold learning improves the accuracy of MRSI spectral quantification.

High cerebrospinal fluid lactate concentration at 48 h of hospital admission predicts poor outcomes in patients with tuberculous meningitis: A multicenter retrospective cohort study

Objective

This study aimed to analyze the cerebrospinal fluid (CSF) parameters affecting the outcomes of patients with tuberculous meningitis (TBM).

Methods

This is a multi-center, retrospective, cohort study involving 81 patients who were diagnosed with TBM and treated in Haihe Clinical College of Tianjin Medical University, Tianjin Medical University General Hospital, and General Hospital of Air Force PLA from January 2016 to December 2019. Baseline data, Glasgow Coma Scale (GCS) score, and clinical presentations of all patients were collected at admission. CSF samples were collected at 48 h, 1, 2, and 3 weeks after admission. CSF lactate, adenosine deaminase, chloride, protein, glucose levels and intracranial pressure were measured. After a follow-up of 16.14 ± 3.03 months, all patients were assessed using the modified Rankin Scale (mRS) and divided into good (mRS scores of 0–2 points) and poor outcome groups (mRS scores of 3–6 points). The differences in patients' baseline data, GCS score, clinical presentations, and levels of CSF parameters detected at 48 h, 1, 2, and 3 weeks after admission between two groups were compared. Statistically significant variables were added to the binary logistic regression model to identify the factors impacting the outcomes of patients with TBM. Receiver operating characteristic (ROC) curve was used to assess the predictive ability of the model.

Results

The CSF lactate level exhibited a decreasing trend within 3 weeks of admission in the two groups. For the within-group comparison, statistically significant differences in the lactate level was found in both groups between four different time points. A binary logistic regression model revealed that CSF lactate level at 48 h after admission, age, and GSC score on admission were independently associated with the outcomes of patients with TBM. ROC curve analysis showed that the area under the ROC curve (AUC) was 0.786 for the CSF lactate level (48 h), 0.814 for GCS score, and 0.764 for age.

Conclusion

High CSF lactate level at 48 h after admission is one of the important factors for poor outcomes in patients with TBM.

Functional connectivity and neurotransmitter impairments of the salience brain network in chronic low back pain patients: a combined resting state functional MRI and 1H-MRS study

ABSTRACT

Functional re-organisation of the salience network (SN) has been proposed as one of the key pathomechanisms associated with central nociceptive processing in the chronic pain state. Being associated with an altered functional connectivity within the SN, these processes have been hypothesized to result from a loss of inhibitory function leading to node hyperexcitability and spontaneous pain. Combined resting-state (rs) BOLD fMRI and 1H-MR spectroscopy was applied to chronic back pain (CBP) patients and healthy subjects (HS) to assess deviations from functional integrity (weighted closeness centrality, wCC, derived from rs-fMRI), oscillatory BOLD characteristics (spectral power, SP), and neurotransmitter levels (GABA+, glutamate+glutamine) in two key SN nodes, anterior insular (aInsR) and anterior mid-cingulate (aMCC) cortices. In addition, examinations were repeated in CBP patients after a four week interdisciplinary multimodal pain treatment and in HS after four weeks to explore longitudinal, treatment-mediated changes in target variables. The aInsR and, to a lesser extent, the aMCC of patients exhibited significantly reduced wCC accompanied by a SP shift from a lower to a higher frequency band, indicating a desynchronization of their neuronal activity within the SN, possibly due to increased spontaneous activations. Without revealing neurotransmitter differences, patients alone showed significant positive associations between local GABA+ levels and wCC in aInsR, suggesting a stronger dependence of node synchronization on the inhibitory tone in the chronic pain state. However, this needs to be explored in future using MRS techniques that are more sensitive to detecting subtle neurotransmitter changes and also allow multifocal characterization of neurotransmitter tone.

Admission blood lactate levels of patients diagnosed with cerebrovascular disease effects on short- and long-term mortality risk

OBJECTIVE

Our study was carried out on patients admitted to the emergency ward with acute stroke symptoms that were subsequently diagnosed with cerebrovascular disease. We aimed to examine the relationship between these patients' admission lactate levels and their 1-, 3-, and 12-month mortality rates in order to evaluate the prognostic value of lactate levels.

METHODS

Our data were obtained retrospectively from 568 patients diagnosed with acute ischemic stroke at our emergency department between 1 January 2017 and 1 January 2018. Patient data were accessed via the hospital patient database. Included patients' files were assessed for examination and history taken at admission, comorbid diseases, demographic characteristics, treatments utilized, and laboratory results. Hyperlactatemia was defined as a lactate level of over 2 mmol/L. The relationship between lactate levels and survival was investigated. Patients' complication rates after discharge were assessed alongside their 1-, 3-, and 12-month mortality.

RESULTS

Our study assessed 568 patients. Out of these patients, 400 patients met our inclusion criteria and constituted the study population. These patients were separated into two groups according to their lactate levels. The hyperlactatemic group had a statistically significant increase in 1-, 3-, and 12-month mortality rates in comparison to the other group.

CONCLUSIONS

Our study found that hyperlactatemia was associated with a higher risk of 1-, 3-, and 12-month mortality, suggesting that it has predictive prognostic value. In the future, we believe that prospective observational studies and/or large-scale retrospective studies will be of great value in providing more insight into this topic.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Separation of Metabolites and Macromolecules for Short-TE 1H-MRSI Using Learned Component-Specific Representations

Short-echo-time (TE) proton magnetic resonance spectroscopic imaging (MRSI) allows for simultaneously mapping a number of molecules in the brain, and has been recognized as an important tool for studying in vivo biochemistry in various neuroscience and disease applications. However, separation of the metabolite and macromolecule (MM) signals present in the short-TE data with significant spectral overlaps remains a major technical challenge. This work introduces a new approach to solve this problem by integrating imaging physics and representation learning. Specifically, a mixed unsupervised and supervised learning-based strategy was developed to learn the metabolite and MM-specific low-dimensional representations using deep autoencoders. A constrained reconstruction formulation is proposed to integrate the MRSI spatiospectral encoding model and the learned representations as effective constraints for signal separation. An efficient algorithm was developed to solve the resulting optimization problem with provable convergence. Simulation and experimental results have been obtained to demonstrate the component-specific representation power of the learned models and the capability of the proposed method in separating metabolite and MM signals for practical short-TE [Formula: see text]-MRSI data.

ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI

A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B₁⁺ field and lipid T₁ heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.

Effects of different macromolecular models on reproducibility of FID-MRSI at 7T

PURPOSE

A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID-MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility.

METHODS

Clinically feasible, high-resolution FID-MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test-retest reproducibility of MRSI scans was assessed voxel-wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model.

RESULTS

The full MM model provided the most reproducible quantification of total NAA, total Cho, myo-inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to -0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites.

CONCLUSION

Clinically feasible FID-MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered.

Intact metabolite spectrum mining by deep learning in proton magnetic resonance spectroscopy of the brain

PURPOSE

To develop a robust method for brain metabolite quantification in proton magnetic resonance spectroscopy (¹ H-MRS) using a convolutional neural network (CNN) that maps in vivo brain spectra that are typically degraded by low SNR, line broadening, and spectral baseline into noise-free, line-narrowed, baseline-removed intact metabolite spectra.

METHODS

A CNN was trained (n = 40 000) and tested (n = 5000) on simulated brain spectra with wide ranges of SNR (6.90-20.74) and linewidth (10-20 Hz). The CNN was further tested on in vivo spectra (n = 40) from five healthy volunteers with substantially different SNR, and the results were compared with those from the LCModel analysis. A Student t test was performed for the comparison.

RESULTS

Using the proposed method the mean-absolute-percent-errors (MAPEs) in the estimated metabolite concentrations were 12.49% ± 4.35% for aspartate, creatine (Cr), γ-aminobutyric acid (GABA), glucose, glutamine, glutamate, glutathione (GSH), myo-Inositol (mI), N-acetylaspartate, phosphocreatine (PCr), phosphorylethanolamine, and taurine over the whole simulated spectra in the test set. The metabolite concentrations estimated from in vivo spectra were close to the reported ranges for the proposed method and the LCModel analysis except mI, GSH, and especially Cr/PCr for the LCModel analysis, and phosphorylcholine to glycerophosphorylcholine ratio (PC/GPC) for both methods. The metabolite concentrations estimated across the in vivo spectra with different SNR were less variable with the proposed method (~10% or less) than with the LCModel analysis.

CONCLUSION

The robust performance of the proposed method against low SNR may allow a subminute ¹ H-MRS of human brain, which is an important technical development for clinical studies.

Proton and multinuclear magnetic resonance spectroscopy in the human brain at ultra-high field strength: A review

Magnetic Resonance Spectroscopy (MRS) allows for a non-invasive and non-ionizing determination of in vivo tissue concentrations and metabolic turn-over rates of more than 20 metabolites and compounds in the central nervous system of humans. The aim of this review is to give a comprehensive overview about the advantages, challenges and advances of ultra-high field MRS with regard to methodological development, discoveries and applications from its beginnings around 15 years ago up to the current state. The review is limited to human brain and spinal cord application at field strength of 7T and 9.4T and includes all relevant nuclei (¹H, ³¹P, ¹³C).

Simultaneous mapping of metabolites and individual macromolecular components via ultra-short acquisition delay 1 H MRSI in the brain at 7T

Purpose

Short‐echo‐time proton MR spectra at 7T feature nine to 10 distinct macromolecule (MM) resonances that overlap with the signals of metabolites. Typically, a metabolite‐nulled in vivo MM spectrum is included in the quantification`s prior knowledge to provide unbiased metabolite quantification. However, this MM model may fail if MMs are pathologically altered. In addition, information about the individual MM peaks is lost. In this study, we aimed to create an improved MM model by parameterization of the in vivo MM spectrum into individual components, and to use this new model to quantify free induction decay MR spectroscopic imaging (FID‐MRSI) data.

Methods

The measured in vivo MM spectrum was parameterized using advanced method for accurate, robust, and efficient spectral fitting (AMARES) and Hankel‐Lanczos singular value decomposition algorithms from which six different MM models were derived. Soft constraints were applied to avoid over‐parameterization. All MM models were combined with simulated metabolite spectra to form complete basis sets. FID‐MRSI data from 14 healthy volunteers were quantified via LCModel, and the results were compared between all basis sets.

Results

The MM model using nine individual AMARES‐parameterized MM components with additional soft constraints achieved the most reliable results. Nine MMs and seven metabolites were mapped simultaneously over the whole slice.

Conclusion

The proposed MM model may facilitate studies that involve patients with pathologically altered MMs. Magn Reson Med 79:1231–1240, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Forecasting the quality of water-suppressed 1 H MR spectra based on a single-shot water scan

PURPOSE

To investigate whether an initial non-water-suppressed acquisition that provides information about the signal-to-noise ratio (SNR) and linewidth is enough to forecast the maximally achievable final spectral quality and thus inform the operator whether the foreseen number of averages and achieved field homogeneity is adequate.

METHODS

A large range of spectra with varying SNR and linewidth was simulated and fitted with popular fitting programs to determine the dependence of fitting errors on linewidth and SNR. A tool to forecast variance based on a single acquisition was developed and its performance evaluated on simulated and in vivo data obtained at 3 Tesla from various brain regions and acquisition settings.

RESULTS

A strong correlation to real uncertainties in estimated metabolite contents was found for the forecast values and the Cramer-Rao lower bounds obtained from the water-suppressed spectra.

CONCLUSION

It appears to be possible to forecast the best-case errors associated with specific metabolites to be found in model fits of water-suppressed spectra based on a single water scan. Thus, nonspecialist operators will be able to judge ahead of time whether the planned acquisition can possibly be of sufficient quality to answer the targeted clinical question or whether it needs more averages or improved shimming. Magn Reson Med 78:441-451, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

The age dependence of T2 relaxation times of N-acetyl aspartate, creatine and choline in the human brain at 3 and 4T

Knowledge of the T2 age dependence is of importance for MRS clinical studies involving subject groups with a wide age range. A number of studies have focused on the age dependence of T2 values in the human brain, with rather conflicting results. The aim of this study was to analyze the age dependence of T2 values of N-acetyl aspartate (NAA), creatine (Cr) and choline (Cho) in the human brain using data acquired at 3T and 4T and to assess the influence of the macromolecule (MM) baseline handling on the obtained results. Two distinct groups of young and elderly controls have been measured at 3T (TE = 30-540 ms, 9 young and 11 elderly subjects) and 4T (TE = 10-180 ms, 18 young and 14 elderly subjects) using single-voxel spectroscopy. In addition, MM spectra were measured from two subjects using the inversion-recovery technique at 4T. All spectra were processed with LCModel using basis sets with different MM signals (measured or simulated) and also with MM signals included for a different TE range. Individual estimated T2 values were statistically analyzed using the R programming language for the age dependence of T2 values as well as the influence of the MM baseline handling. A significant decrease of T2 values of NAA and Cr in elderly subjects compared with young subjects was confirmed. The same trend was observed for Cho. Significantly higher T2 values calculated using the measured MM baseline for all studied metabolites at 4T were observed for both young and elderly subjects. To conclude, while the handling of MM and lipid signals may have a significant effect on estimated T2 values, we confirmed the age dependence of T2 values of NAA and Cr and the same trend for Cho in the human brain. Copyright © 2016 John Wiley & Sons, Ltd.

Separation and quantification of lactate and lipid at 1.3 ppm by diffusion-weighted magnetic resonance spectroscopy

PURPOSE

To separate the spectrally overlapped lactate and lipid signals at 1.3 ppm using diffusion-weighted magnetic resonance spectroscopy (DW-MRS) based on their large diffusivity difference.

METHODS

DW-MRS was applied to the gel phantoms containing lactate and lipid droplets, and to the rat brain tumors. Lactate and lipid signals and their apparent diffusion coefficients were computed from the diffusion-weighted proton spectra. Biexponential fitting and direct spectral subtraction approaches were employed and compared.

RESULTS

DW-MRS could effectively separate lactate and lipid signals both in phantoms and rat brain C6 glioma by biexponential fitting. In phantoms, lactate and lipid signals highly correlated with the known lactate concentration and lipid volume fractions. In C6 glioma, both lactate and lipid signals were detected, and the lipid signal was an order of magnitude higher than lactate signal. The spectral subtraction approach using three diffusion weightings also allowed the separation of lactate and lipid signals, yielding results comparable to those by the biexponential fitting approach.

CONCLUSION

DW-MRS presents a new approach to separate and quantify spectrally overlapped molecules and/or macromolecules, such as lactate and lipid, by using the diffusivity difference associated with their different sizes or mobility within tissue microstructure. Magn Reson Med 77:480-489, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Transverse relaxation of selectively excited metabolites in stroke at 21.1 T

PURPOSE

This study seeks to evaluate in vivo T₂ relaxation times of selectively excited stroke-relevant metabolites via ¹ H relaxation-enhanced magnetic resonance spectroscopy (RE-MRS) at 21.1 T (900 MHz).

METHODS

A quadrature surface coil was designed and optimized for investigations of rodents at 21.1 T. With voxel localization, a RE-MRS pulse sequence incorporating the excitation of selected metabolites was modified to include a variable echo delay for T₂ measurements. A middle cerebral artery occlusion (MCAO) animal model for stroke was examined with spectra taken 24 h post occlusion. Fourteen echo times were acquired, with each measurement completed in less than 2 min.

RESULTS

The RE-MRS approach produced high-quality spectra of the selectively excited metabolites in the stroked and contralateral regions. T₂ measurements reveal differential results between these regions, with significance achieved for lactic acid.

CONCLUSION

Using the RE-MRS technique at ultra-high magnetic field and an optimized quadrature surface coil design, full metabolic T₂ quantifications in a localized voxel is now possible in less than 27 min. Magn Reson Med 77:520-528, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Influence of macromolecule baseline on 1 H MR spectroscopic imaging reproducibility

Purpose

Poorly characterized macromolecular (MM) and baseline artefacts are known to reduce metabolite quantitation accuracy in ¹H MR spectroscopic imaging (MRSI). Increasing echo time (TE) and improvements in MM analysis schemes have both been proposed as strategies to improve metabolite measurement reliability. In this study, the influence of TE and two MM analysis schemes on MRSI reproducibility are investigated.

Methods

An experimentally acquired baseline was collected using an inversion recovery sequence (TI = 750 ms) and incorporated into the analysis method. Intrasubject reproducibility of MRSI scans, acquired at 3 Tesla, was assessed using metabolite coefficients of variance (COVs) for both experimentally acquired and simulated MM analysis schemes. In addition, the reproducibility of TE = 35 ms, 80 ms, and 144 ms was evaluated.

Results

TE = 80 ms was the most reproducible for singlet metabolites with COVs < 6% for total N‐acetyl‐aspartate, total creatine, and total choline; however, moderate multiplet dephasing was observed. Analysis incorporating the experimental baseline achieved higher Glu and Glx reproducibility at TE = 35 ms, and showed improvements over the simulated baseline, with higher efficacy for poorer data.

Conclusion

Overall, TE = 80 ms yielded the most reproducible singlet metabolite estimates. However, combined use of a short TE sequence and the experimental baseline may be preferred as a compromise between accuracy, multiplet dephasing, and T2 bias on metabolite estimates. Magn Reson Med 77:34–43, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Comparison of the repeatability of GABA-edited magnetic resonance spectroscopy with and without macromolecule suppression

PURPOSE

The inhibitory neurotransmitter γ-aminobutyric acid (GABA) can be measured in vivo using edited magnetic resonance spectroscopy (MRS), but quantification suffers from contamination by macromolecules (MM). It is possible to suppress this contamination using symmetric editing, but this procedure potentially compromises reliability of the GABA measurement. The aim of this study was to compare the repeatability of GABA-edited MRS with and without MM suppression.

METHODS

GABA' (non-MM contaminated) and GABA'+MM (MM-contaminated) concentration was measured in the occipital lobe (OCC) and anterior cingulate (AC) using symmetric and standard editing (n = 15). Each method was performed twice in each region.

RESULTS

Within-participant coefficients of variation for each technique were 4.0% (GABA'+MM) and 8.6% (GABA') in the OCC and 14.8% (GABA'+MM) and 12.6% (GABA') in the AC. Intraclass correlation coefficients were better for the suppression method than standard editing in both the OCC (0.72 versus 0.67) and AC (0.41 versus 0.16). These findings were replicated in the OCC of a second cohort (n = 15).

CONCLUSION

Symmetric suppression is shown to be comparable in repeatability to standard GABA-editing. Measuring a purer quantification of GABA becomes increasingly important as more research is conducted on links between GABA concentration, pathology and healthy behavior.

Magnetic resonance spectroscopy detection of high lipid levels in intraaxial tumors without central necrosis: a characteristic of malignant lymphoma

OBJECT

The differentiation of malignant lymphomas from gliomas or malignant gliomas by conventional MRI can be difficult. The authors studied Gd-enhanced MR images to obtain a differential diagnosis between malignant lymphomas and gliomas without central necrosis or cystic changes and investigated the diagnostic value of single-voxel proton MR spectroscopy ((1)H-MRS) using different parameters, including lipid levels.

METHODS

This was a retrospective study of patients with primary malignant CNS lymphoma (n = 17) and glioma (n = 122 [Grades I, II, III, and IV in 10, 30, 33, and 49 patients, respectively]) who were treated between 2007 and 2013. The authors focused on 15 patients with homogeneously enhanced primary malignant CNS lymphomas and 7 homogeneously enhanced gliomas. Images of all the included tumors were acquired with (1)H-MRS at 3 T, and the diagnoses were histologically confirmed.

RESULTS

Using a short echo time (1)H-MRS, large lipid peaks were observed in all 17 patients with a malignant lymphoma, in 39 patients (79.6%) with a Grade IV glioma, and in 10 patients (30.3%) with a Grade III glioma. A focus on homogeneously enhanced tumors revealed large lipid peaks in 15 malignant lymphomas that were free of central necrosis on Gd-enhanced T1-weighted images. Conversely, in the 7 homogeneously enhanced gliomas (glioblastoma and anaplastic astrocytoma, n = 2 each; anaplastic oligodendroglioma, diffuse astrocytoma, and pilomyxoid astrocytoma, n = 1 each), lipid peaks were small or absent.

CONCLUSIONS

Large lipid peaks on (1)H-MRS images of tumors without central necrosis were characteristic of malignant lymphomas. Conversely, small or absent lipid peaks in intraaxial tumors without central necrosis were strongly suggestive of glioma.

Comparison of brain gray and white matter macromolecule resonances at 3 and 7 Tesla

PURPOSE

In proton MR spectra of the human brain, relatively broad macromolecule (MM) resonances underlie the narrower signals from metabolites. The purpose of this study was to quantify the MM profile in healthy human brain at 3T and 7T, both in gray matter (anterior cingulate cortex [ACC]) and white matter (centrum semiovale [CSO]).

METHODS

A water-suppressed, inversion-recovery pulse sequence was used to null metabolite signals and acquire MM spectra in 20 healthy volunteers using very similar methodology at both field strengths (n = 5 per region and field). The MM spectra were fitted with multiple Gaussian functions and quantified relative to the unsuppressed water signal from the same volume.

RESULTS

MM proton concentration values were in the range of 5-20 mmol/kg. No significant differences were found between the MM proton concentration measurements by region (P ≈ 0.8) nor by field strength (P ≈ 0.5). Linewidths of the well-resolved M1 peak were slightly more than double at 7T (43.0 ± 4.7 Hz in ACC, 45.6 ± 4.1 Hz in CSO) compared with 3T (19.8 ± 3.5 Hz in ACC, 20.0 ± 4.3 Hz in CSO).

CONCLUSION

The absence of differences in MM concentrations between white and gray matter implies that a single MM "baseline" may be adequate for spectral fitting of multiple brain regions when determining metabolite concentrations. Visibility of MM signals is similar at 3T and 7T.

Quantification of the neurochemical profile using simulated macromolecule resonances at 3 T

The broad resonances underlying the entire (1) H NMR spectrum of the brain, ascribed to macromolecules, can influence metabolite quantification. At the intermediate field strength of 3 T, distinct approaches for the determination of the macromolecule signal, previously used at either 1.5 or 7 T and higher, may become equivalent. The aim of this study was to evaluate, at 3 T for healthy subjects using LCModel, the impact on the metabolite quantification of two different macromolecule approaches: (i) experimentally measured macromolecules; and (ii) mathematically estimated macromolecules. Although small, but significant, differences in metabolite quantification (up to 23% for glutamate) were noted for some metabolites, 10 metabolites were quantified reproducibly with both approaches with a Cramer-Rao lower bound below 20%, and the neurochemical profiles were therefore similar. We conclude that the mathematical approximation can provide sufficiently accurate and reproducible estimation of the macromolecule contribution to the (1) H spectrum at 3 T.

High-field MRS of the human brain at short TE and TR

In vivo MRS of the human brain at 7 tesla allows identification of a large number of metabolites at higher spatial resolutions than currently possible at lower field strengths. However, several challenges complicate in vivo localization and artifact suppression in MRS at high spatial resolution within a clinically feasible scan time at 7 tesla. Published MRS sequences at 7 tesla suffer from long echo times, inherent signal-to-noise ratio (SNR) loss, large chemical shift displacement artifacts or long repetition times because of excessive radiofrequency (RF) power deposition. In the present study a pulse-acquire sequence was used that does not suffer from these high field drawbacks. A slice selective excitation combined with high resolution chemical shift imaging for in-plane localization was used to limit chemical shift displacement artifacts. The pulse-acquire approach resulted in a very short echo time of 1.4 ms. A cost function guided shimming algorithm was developed to constrain frequency offsets in the excited slice, therefore adiabatic frequency selective suppression could be employed to minimize artifacts from high intensity lipids and water signals in the excited slice. The high sensitivity at a TR of 1 s was demonstrated both on a supraventricular slice as well as in an area very close to the skull in the frontal cortex at a nominal spatial resolution of 0.25 cc within a feasible scan time.

Magnetic resonance spectroscopic detection of lactate is predictive of a poor prognosis in patients with diffuse intrinsic pontine glioma

Diffuse brainstem glioma has a poor prognosis, and there are few long-term survivors. We looked for clinical, conventional magnetic resonance (MR), and MR spectroscopic (MRS) findings predictive of the prognosis of patients with brainstem glioma. Our institutional review board approved this retrospective study of 23 patients with diffuse intrinsic pontine or diffuse medullary brainstem glioma treated during the period 2000-2009. To evaluate prognostic values, we performed a Kaplan-Meier survival analysis (log-rank test) that incorporated the patients' age and sex, symptom duration, the presence or absence of cranial nerve palsy, long tract sign, ataxia, and cysts, the chemotherapeutic regimen, Gd enhancement, longitudinal and cerebellar extension, basilar artery encasement, and MRS parameters. Of the 23 diffuse brainstem gliomas, 19 were located at the pons (ratio of male to female patients, 1.1:1). The mean age of the 23 patients was 15.9 years (range, 4-50 years); 16 were aged <20 years. The duration of overall survival was 19.7 months; in patients with diffuse intrinsic pontine glioma, it was 16.6 months, and in patients aged <20 years, it was 11.8 months. Clinical and conventional MR findings at presentation were not predictive of the prognosis in children with diffuse intrinsic pontine glioma. In addition, a patient age <20 years and the detection of lactate by MRS were poor prognostic factors. The MRS detection of lactate is a prognostic factor in patients with diffuse intrinsic pontine glioma. Additional studies of larger patient populations using other imaging modalities are needed.

Reduced N-acetylaspartate is consistent with axonal dysfunction in cerebral small vessel disease

BACKGROUND

Cerebral small vessel disease (SVD) is an important cause of cognitive impairment, but the pathophysiological mechanisms remain unclear. We used (1)H MRS to investigate brain metabolic differences between patients with SVD and controls and correlated this with cognition.

METHODS

35 patients with SVD (lacunar stroke and radiological evidence of confluent leukoaraiosis) and 35 controls underwent multi-voxel spectroscopic imaging of white matter to obtain absolute metabolite concentrations of N-acetylaspartate (NAA), total creatines, total cholines, myo-inositol, and lactate. A range of cognitive tests was performed on patients with SVD, and composite scores were calculated.

RESULTS

Scans of sufficient quality for data analysis were available in 29 cases and 35 controls. NAA was significantly reduced in patients compared with controls (lower by 7.27%, P = 0.004). However, when lesion load within each individual voxel (mean 22% in SVD vs 5% in controls, P < 0.001) was added as a covariate, these differences were no longer significant, suggesting that the metabolite differences arose primarily from differences in lesioned tissue. In patients with SVD, there was no correlation between cognitive scores and any brain metabolite. No lactate, an indicator of anaerobic metabolism, was detected.

CONCLUSIONS

The most consistent change in SVD is a reduction in NAA, a marker of neuronal integrity. The lack of correlation with cognition does not support the use of MRS as a surrogate disease marker.

Detection of cerebral metabolites in a canine model of ischemic stroke using 1H magnetic resonance spectroscopy

Proton magnetic resonance spectroscopy ((1)H MRS) provides in vivo biochemical information on tissue metabolites. The purpose of this study was to investigate the serial metabolic changes of (1)H MRS in the cerebrum of ischemic dogs. An ischemic stroke was induced in five health laboratory beagle dogs by permanent middle cerebral artery occlusion using a silicone plug. (1)H MRS was serially performed three times with a 1.5-T MR system: before, three days after and 10days after the stroke. Immunohistochemical staining was performed to determine the expression of neuronal nuclei (NeuN) and glial fibrillary acidic protein (GFAP) at both the ipsilateral and contralateral cerebral cortex. Reduced levels of N-acetyl-asparate (p<0.05), choline (Cho), creatine (Cr) and myo-inositol (mI), and a marked increase in the lactate (Lac) level (p<0.01) were found at three days after the stroke. At 10days after the stroke, the levels of Lac significantly increased (p<0.01); however, the other metabolites were partially elevated. The changes of Cr, Cho and mI were not statistically significant (p>0.05) when the before and after stroke values were compared. There was a significant loss of NeuN and GFAP immunoreactivity at the ischemic core. (1)H MRS may be to a useful diagnostic tool for the evaluation of ischemic stroke in dogs.

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.

Technology insight: can neuroimaging provide insights into the role of ischemia in Baló's concentric sclerosis?

Baló's concentric sclerosis (BCS) has long been considered to be a variant of multiple sclerosis. Although BCS was initially described over 100 years ago, relatively few antemortem cases have been identified, and the exact pathogenesis remains unknown. Inflammatory protective ischemic preconditioning has recently been suggested as a mechanism by which the typical concentric rings of the BCS lesion are formed. Advanced neuroimaging can provide important in vivo markers of disease progression that can assist in the diagnosis and management of patients with BCS. In this Review, we discuss evidence from longitudinal neuroimaging studies that supports the role of ischemic preconditioning in BCS.

Delayed changes in T1-weighted signal intensity in a rat model of 15-minute transient focal ischemia studied by magnetic resonance imaging/spectroscopy and synchrotron radiation X-ray fluorescence

Previous studies have found that rats subjected to 15-min transient middle cerebral artery occlusion (MCAO) show neurodegeneration in the dorsolateral striatum only, and the resulting striatal lesion is associated with increased T1-weighted (T1W) signal intensity (SI) and decreased T2-weighted (T2W) SI at 2-8 weeks after the initial ischemia. It has been shown that the delayed increase in T1W SI in the ischemic region is associated with deposition of paramagnetic manganese ions. However, it has been suggested that other mechanisms, such as tissue calcification and lipid accumulation, also contribute to the relaxation time changes. To clarify this issue, we measured changes in relaxation times, lipid accumulation, and elemental distributions in the brain of rats subjected to 15-min MCAO using MRI, in vivo 1H MR spectroscopy (MRS), and synchrotron radiation X-ray fluorescence (SRXRF). The results show that a delayed (2 weeks after ischemia) increase in T1W SI in the ischemic striatum is associated with significant increases in manganese, calcium, and iron, but without evident accumulation of MRS-visible lipids or hydroxyapatite precipitation. It was also found that 15-min MCAO results in acutely reduced N-acetylaspartate (NAA)/creatine (Cr) ratio in the ipsilateral striatum, which recovers to the control level at 2 weeks after ischemia.

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.

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Detection of the inhibitory neurotransmitter GABA in macrophages by magnetic resonance spectroscopy

Macrophages are key components of the inflammatory response to tissue injury, but their activities can exacerbate neuropathology. High-resolution magnetic resonance spectroscopy was used to identify metabolite levels in perchloric acid extracts of cultured cells of the RAW 264.7 murine macrophage line under resting and lipopolysaccharide-activated conditions. Over 25 metabolites were identified including gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter not previously reported to be present in macrophages. The presence of GABA was also demonstrated in extracts of human peripheral blood monocyte-derived macrophages. This finding suggests that there may be communication between damaged central nervous system (CNS) tissue and recruited macrophages and resident microglia, which could help orchestrate the immune response. On activation, lactate, glutamine, glutamate, and taurine levels were elevated significantly, and GABA and alanine were reduced significantly. Strong resonances from glutathione, evident in the macrophage two-dimensional 1H spectrum, suggest that this may have potential as a noninvasive marker of macrophages recruited to the CNS, as it is only present at low levels in normal brain. Alternatively, a specific combination of spectroscopic changes, such as lactate, alanine, glutathione, and polyamines, may prove to be the most accurate means of detecting macrophage recruitment to the CNS.

Brain lesions with elevated lactic acid peaks on magnetic resonance spectroscopy

Magnetic resonance (MR) spectroscopy is a noninvasive imaging tool that provides information on various metabolite concentrations within brain lesions. The biochemical information obtained with MR spectroscopy, along with the morphologic appearance of a lesion on MR imaging, allows for better characterization and improved diagnostic ability. Lactic acid is an end product of anaerobic metabolism. Under conditions of anaerobic metabolism or inflammation, lactate levels become elevated and a characteristic peak at 1.3 ppm is detected on MR spectroscopy. This review will discuss the significance of lactate as a metabolite and will describe various brain lesions and disease conditions in which elevated lactate levels are detected.

Changes in the proton T2 relaxation times of cerebral water and metabolites during forebrain ischemia in rat at 9.4 T

Proton T(2) relaxation times of cerebral water and metabolites were measured before, during, and after transient forebrain ischemia in rat at 9.4 T using localized proton magnetic resonance spectroscopy ((1)H-MRS) with Hahn echoes formed at different echo times (TEs). It was found that the T(2) values of water and N-acetyl aspartate (NAA) methyl, but not total creatine (tCr) methyl, decrease significantly (approximately 10%) during ischemia, and this T(2) reduction is reversed by reperfusion. The T(2) reduction observed for NAA was most likely caused by the extravascular component of the blood oxygenation level-dependent (BOLD) effect induced by a drastically increased deoxyhemoglobin content during ischemia. The absence of T(2) changes for tCr can probably be explained by the fact that the BOLD-related T(2) decrease was counterbalanced by the conversion of phosphocreatine (PCr) to creatine (Cr), which has a longer T(2) than PCr, during ischemia. The changes in T(2) should be taken into account for the quantification of metabolite concentrations during ischemia.

Quantitative proton short-echo-time LASER spectroscopy of normal human white matter and hippocampus at 4 Tesla incorporating macromolecule subtraction

Accurate quantification of in vivo short-echo-time (TE) (1)H spectra must account for contributions from both mobile metabolites and less mobile macromolecules, which can fluctuate in disease. The purpose of this study was to develop an approach for the acquisition and processing of macromolecule information to optimize metabolite quantification accuracy and precision. Human parietal white matter (8-cm(3) voxel) and posterior hippocampus (1.7-cm(3) voxel) metabolite levels were quantified, following manomolecule subtraction, from short-echo-time spectra (TE = 46 ms) acquired at 4.0 Tesla with localization by adiabatic selective refocusing (LASER). Nineteen metabolites were fit using a time domain Levenberg-Marquardt minimization that incorporated prior knowledge of metabolite lineshapes. The macromolecule contribution to the spectrum was reduced by 87% (P < 0.05) when the acquisition of single averages of the full spectrum and macromolecule spectrum were interleaved to reduce subtraction errors due to motion. Subtracting the Hankel Lanczos singular value decomposition (HLSVD) fit of the macromolecule spectrum, which contained no random noise, did not alter quantified metabolite levels but did not increase metabolite quantification precision. Several metabolites had higher concentrations in the posterior hippocampus compared to parietal white matter, which emphasizes the need to carefully control for partial volume contamination in hippocampal spectroscopy studies.