1H–MRS processing parameters affect metabolite quantification: The urgent need for uniform and transparent standardization

Proton magnetic resonance spectroscopy (¹H–MRS) can be used to quantify in vivo metabolite levels, such as lactate, γ‐aminobutyric acid (GABA) and glutamate (Glu). However, there are considerable analysis choices which can alter the accuracy or precision of ¹H–MRS metabolite quantification . It is currently unknown to what extent variations in the analysis pipeline used to quantify ¹H–MRS data affect outcomes. The purpose of this study was to evaluate whether the quantification of identical ¹H–MRS scans across independent and experienced research groups would yield comparable results. We investigated the influence of model parameters and spectral quantification software on fitted metabolite concentration values. Sixty spectra in 30 individuals (repeated measures) were acquired using a 7‐T MRI scanner. Data were processed by four independent research groups with the freedom to choose their own individualized and optimal parameter settings using LCModel software. Data were processed a second time in one group using an independent software package (NMRWizard) for an additional comparison with a different post‐processing platform. Correlations across research groups of the ratio between the highest and, arguably, the most relevant resonances for neurotransmission [N‐acetyl aspartate (NAA), N‐acetyl aspartyl glutamate (NAAG) and Glu] over the total creatine [creatine (Cr) + phosphocreatine (PCr)] concentration, using Pearson's product–moment correlation coefficient (r), were calculated. Mean inter‐group correlations using LCModel software were 0.87, 0.88 and 0.77 for NAA/Cr + PCr, NAA + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. The mean correlations when comparing NMRWizard results with LCModel fitting results at University Medical Center Utrecht (UMCU) were 0.87, 0.89 and 0.71 for NAA/Cr + PCr, NAA + NAAG/Cr + PCr and Glu/Cr + PCr, respectively. Metabolite quantification using identical ¹H–MRS data was influenced by processing parameters, basis sets and software choice. Locally preferred processing choices affected metabolite quantification, even when using identical software. Our results reinforce the notion that standard practices should be established to regularize outcomes of ¹H–MRS studies, and that basis sets used for processing should be made available to the scientific community.     

Quantification of MRS data in the frequency domain using a wavelet filter, an approximated Voigt lineshape model and prior knowledge

Quantification of MRS spectra is a challenging problem when a large baseline is present along with a low signal to noise ratio. This work investigates a robust fitting technique that yields accurate peak areas under these conditions. Using simulated long echo time (1)H MRS spectra with low signal to noise ratio and a large baseline component, both the accuracy and reliability of the fit in the frequency domain were greatly improved by reducing the number of fitted parameters and making full use of all the known information concerning the Voigt lineshape. Using an appropriate first order approximation to a popular approximation of the Voigt lineshape, a significant improvement in the estimate of the area of a known spectral peak was obtained with a corresponding reduction in the residual. Furthermore, this improved parameter choice resulted in a large reduction in the number of iterations of the least-squares fitting routine. On the other hand, making use of the known centre frequency differences of the component resonances gave negligible improvement. A wavelet filter was used to remove the baseline component. In addition to performing a Monte Carlo study, these fitting techniques were also applied to a set of 10 spectra acquired from healthy human volunteers. Again, the same reduced parameter model gave the lowest value for chi(2) in each case.     

Online 1H‐MRS measurements of time‐varying lactate production in an animal model of glioma during administration of an anti‐tumoral drug

The aims of this study were to implement a magnetic resonance spectroscopy (MRS) protocol for the online profiling of subnanomolar quantities of metabolites sampled from the extracellular fluid using implanted microdialysis and to apply this protocol in glioma‐bearing rats for the quantification of lactate concentration and the measurement of time‐varying lactate concentration during drug administration. MRS acquisitions on the brain microdialysate were performed using a home‐built, proton‐tuned, microsolenoid with an active volume of 2 μL. The microcoil was placed at the outlet of the microdialysis probe inside a preclinical magnetic resonance imaging (MRI) scanner. C6‐bearing rats were implanted with microdialysis probes perfused with artificial cerebrospinal fluid solution and the lactate dehydrogenase (LDH) inhibitor oxamate. Microcoil magnetic resonance spectra were continuously updated using a single‐pulse sequence. Localized in vivo spectra and high‐resolution spectra on the dialysate were also acquired. The limit of detection and limit of quantification per unit time of the lactate methyl peak were determined as 0.37 nmol/√min and 1.23 nmol/√min, respectively. Signal‐to‐noise ratios (SNRs) of the lactate methyl peak above 120 were obtained from brain tumor microdialysate in an acquisition time of 4 min. On average, the lactate methyl peak amplitude measured in vivo using the nuclear magnetic resonance (NMR) microcoil was 193 ± 46% higher in tumor dialysate relative to healthy brain dialysate. A similar ratio was obtained from high‐resolution NMR spectra performed on the collected dialysate. Following oxamate addition in the perfusate, a monotonic decrease in the lactate peaks was observed in all animals with an average time constant of 4.6 min. In the absence of overlapping NMR peaks, robust profiling of extracellular lactate can be obtained online using a dedicated sensitive NMR microcoil. MRS measurements of the dynamic changes in lactate production induced by anti‐tumoral drugs can be assessed accurately with temporal resolutions on the order of minutes. The MRS protocol can be readily transferred to the clinical environment with the use of suitable clinical microdialysis probes.     

Elevated levels of GABA+ in migraine detected using 1H‐MRS

γ‐Aminobutyric acid (GABA) has been implicated in several pain conditions, yet no study has systematically evaluated GABA levels in migraine using ¹H‐MRS. The accurate detection, separation and quantification of GABA in individuals with migraine could elucidate the role of this neurotransmitter in migraine pathophysiology. Such information may eventually be useful in the diagnosis and development of more effective treatments for migraine. The aims of this study were therefore to compare the concentration of GABA+ in individuals with migraine with that in asymptomatic individuals, and to determine the diagnostic potential of GABA+ in the classification of those with or without migraine. In this case–control study, GABA+ levels in the brain were determined in 19 participants with migraine and 19 matched controls by ¹H‐MRS using Mescher–Garwood point‐resolved spectroscopy (MEGA‐PRESS) sequence. The diagnostic accuracy of GABA+ for the detection of migraine and the optimal cut‐off value were determined by receiver operating characteristic analysis. GABA+ levels were significantly higher (p = 0.002) in those with migraine [median, 1.41 institutional units (IU); interquartile range, 1.31–1.50 IU] than in controls (median, 1.18 IU; interquartile range, 1.12–1.35 IU). The GABA+ concentration appears to have good accuracy for the classification of individuals with or without migraine [area under the curve (95% confidence interval), 0.837 (0.71–0.96); p < 0.001]. The optimal GABA+ cut‐off value for migraine was 1.30 IU, with a sensitivity of 84.2%, specificity of 68.4% and positive likelihood ratio of +2.67. The outcomes of this study suggest altered GABA metabolism in migraine. These results add to the scarce evidence on the putative role of GABA in migraine and provide a basis to further explore the causal relationship between GABA+ and the pathophysiology of migraine. This study also demonstrates that GABA+ concentration has good diagnostic accuracy for migraine. These findings offer new research and practice directions for migraine diagnosis. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterization of hepatic fatty acids in mice with reduced liver fat by ultra‐short echo time 1H‐MRS at 14.1 T in vivo

Alterations in the hepatic lipid content (HLC) and fatty acid composition are associated with disruptions in whole body metabolism, both in humans and in rodent models, and can be non‐invasively assessed by ¹H‐MRS in vivo. We used ¹H‐MRS to characterize the hepatic fatty‐acyl chains of healthy mice and to follow changes caused by streptozotocin (STZ) injection. Using STEAM at 14.1 T with an ultra‐short T_E of 2.8 ms, confounding effects from T₂ relaxation and J‐coupling were avoided, allowing for accurate estimations of the contribution of unsaturated (UFA), saturated (SFA), mono‐unsaturated (MUFA) and poly‐unsaturated (PUFA) fatty‐acyl chains, number of double bonds, PU bonds and mean chain length. Compared with in vivo ¹H‐MRS, high resolution NMR performed in vitro in hepatic lipid extracts reported longer fatty‐acyl chains (18 versus 15 carbons) with a lower contribution from UFA (61 ± 1% versus 80 ± 5%) but a higher number of PU bonds per UFA (1.39 ± 0.03 versus 0.58 ± 0.08), driven by the presence of membrane species in the extracts. STZ injection caused a decrease of HLC (from 1.7 ± 0.3% to 0.7 ± 0.1%), an increase in the contribution of SFA (from 21 ± 2% to 45 ± 6%) and a reduction of the mean length (from 15 to 13 carbons) of cytosolic fatty‐acyl chains. In addition, SFAs were also likely to have increased in membrane lipids of STZ‐induced diabetic mice, along with a decrease of the mean chain length. These studies show the applicability of ¹H‐MRS in vivo to monitor changes in the composition of the hepatic fatty‐acyl chains in mice even when they exhibit reduced HLC, pointing to the value of this methodology to evaluate lipid‐lowering interventions in the scope of metabolic disorders. Copyright © 2015 John Wiley & Sons, Ltd.     

A quantitative comparison of metabolite signals as detected by in vivo MRS with ex vivo 1H HR‐MAS for childhood brain tumours

¹H MRS provides a powerful method for investigating tumour metabolism by allowing the measurement of metabolites in vivo. Recently, the technique of ¹H high‐resolution magic angle spinning (HR‐MAS) has been shown to produce high‐quality data, allowing the accurate measurement of many metabolites present in unprocessed biopsy tissue. The purpose of this study was to evaluate the agreement between the techniques of in vivo MRS and ex vivo HR‐MAS for investigating childhood brain tumours. Short‐TE (30 ms), single‐voxel, in vivo MRS was performed on 16 paediatric patients with brain tumours at 1.5 T. A frozen biopsy sample was available for each patient. HR‐MAS was performed on the biopsy samples, and metabolite quantities were determined from the MRS and HR‐MAS data using the LCModel? and TARQUIN algorithms, respectively. Linear regression was performed on the metabolite quantities to asses the agreement between MRS and HR‐MAS. Eight of the 12 metabolite quantities were found to correlate significantly (P < 0.05). The four worst correlating metabolites were aspartate, scyllo‐inositol, glycerophosphocholine and N‐acetylaspartate, and, except for glycerophosphocholine, this error was reflected in their higher Cramer–Rao lower bounds (CRLBs), suggesting that low signal‐to‐noise was the greatest source of error for these metabolites. Glycerophosphocholine had a lower CRLB implying that interference with phosphocholine and choline was the most significant source of error. The generally good agreement observed between the two techniques suggests that both MRS and HR‐MAS can be used to reliably estimate metabolite quantities in brain tumour tissue and that tumour heterogeneity and metabolite degradation do not have an important effect on the HR‐MAS metabolite profile for the tumours investigated. HR‐MAS can be used to improve the analysis and understanding of MRS data. Copyright © 2009 John Wiley & Sons, Ltd.     

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

This study extensively investigates different strategies for the absolute quantitation of N‐acetyl aspartate, creatine and choline in white and grey matter by ¹H‐MRS at 1.5 T. The main focus of this study was to reliably estimate metabolite concentrations while reducing the scan time, which remains as one of the main problems in clinical MRS. Absolute quantitation was based on the water‐unsuppressed concentration as the internal standard. We compared strategies based on various experimental protocols and post‐processing strategies. Data were obtained from 30 control subjects using a PRESS sequence at several TE to estimate the transverse relaxation time, T₂, of the metabolites. Quantitation was performed with the algorithm QUEST using two different metabolite signal basis sets: a whole‐metabolite basis set (WhoM) and a basis set in which the singlet signals were split from the coupled signals (MSM). The basis sets were simulated in vivo for each TE used. Metabolites' T₂s were then determined by fitting the estimated signal amplitudes of the metabolites obtained at different TEs. Then the absolute concentrations (mM) of the metabolites were assessed for each subject using the estimated signal amplitudes and either the mean estimated relaxation times of all subjects (mean protocol, MP) or the T₂ estimated from the spectra derived from the same subject (individual protocol, IP). Results showed that MP represents a less time‐consuming alternative to IP in the quantitation of brain metabolites by ¹H‐MRS in both grey and white matter, with a comparable accuracy when performed by MSM. It was also shown that the acquisition time might be further reduced by using a variant of MP, although with reduced accuracy. In this variant, only one water‐suppressed and one water‐unsuppressed spectra were acquired, drastically reducing the duration of the entire MRS examination. However, statistical analysis highlights the reduced accuracy of MP when performed using WhoM, particularly at longer echo times. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantification of glutamate and glutamine using constant‐time point‐resolved spectroscopy at 3 T

Separate quantification of glutamate (Glu) and glutamine (Gln) using conventional MRS on clinical scanners is challenging. In previous work, constant‐time point‐resolved spectroscopy (CT‐PRESS) was optimized at 3 T to detect Glu, but did not resolve Gln. To quantify Glu and Gln, a time‐domain basis set was constructed taking into account metabolite T₂ relaxation times and dephasing from B₀ inhomogeneity. Metabolite concentrations were estimated by fitting the basis one‐dimensional CT‐PRESS diagonal magnitude spectra to the measured spectrum. This method was first validated using seven custom‐built phantoms containing variable metabolite concentrations, and then applied to in vivo data acquired in rats exposed to vaporized ethanol and controls. Separate metabolite quantification revealed increased Gln after 16 weeks and increased Glu after 24 weeks of vaporized ethanol exposure in ethanol‐treated compared with control rats. Without separate quantification, the signal from the combined resonances of Glu and Gln (Glx) showed an increase at both 16 and 24 weeks in ethanol‐exposed rats, precluding the determination of the independent and differential contribution of each metabolite at each time. Copyright © 2012 John Wiley & Sons, Ltd.     

Altered metabolites of the rat hippocampus after mild and moderate traumatic brain injury – a combined in vivo and in vitro 1H–MRS study

Traumatic brain injury (TBI) has been shown to affect hippocampus‐associated learning, memory and higher cognitive functions, which may be a consequence of metabolic alterations. Hippocampus‐associated disorders may vary depending on the severity of injury [mild TBI (miTBI) and moderate TBI (moTBI)] and time since injury. The underlying hippocampal metabolic irregularities may provide an insight into the pathological process following TBI. In this study, in vivo and in vitro proton magnetic resonance spectroscopy (¹H–MRS) data were acquired from the hippocampus region of controls and TBI groups (miTBI and moTBI) at D0 (pre‐injury), 4 h, Day 1 and Day 5 post‐injury (PI). In vitro MRS results indicated trauma‐induced changes in both miTBI and moTBI; however, in vivo MRS showed metabolic alterations in moTBI only. miTBI and moTBI showed elevated levels of osmolytes indicating injury‐induced edema. Altered levels of citric acid cycle intermediates, glutamine/glutamate and amino acid metabolism indicated injury‐induced aberrant bioenergetics, excitotoxicity and oxidative stress. An overall similar pattern of pathological process was observed in both miTBI and moTBI, with the distinction of depleted N‐acetylaspartate levels (indicating neuronal loss) at 4 h and Day 1 and enhanced lactate production (indicating heightened energy depletion leading to the commencement of the anaerobic pathway) at Day 5 in moTBI. To the best of our knowledge, this is the first study to investigate the hippocampus metabolic profile in miTBI and moTBI simultaneously using in vivo and in vitro MRS.     

Quantification of γ‐aminobutyric acid (GABA) in 1H MRS volumes composed heterogeneously of grey and white matter

The quantification of γ‐aminobutyric acid (GABA) concentration using localised MRS suffers from partial volume effects related to differences in the intrinsic concentration of GABA in grey (GM) and white (WM) matter. These differences can be represented as a ratio between intrinsic GABA in GM and WM: r_M. Individual differences in GM tissue volume can therefore potentially drive apparent concentration differences. Here, a quantification method that corrects for these effects is formulated and empirically validated. Quantification using tissue water as an internal concentration reference has been described previously. Partial volume effects attributed to r_M can be accounted for by incorporating into this established method an additional multiplicative correction factor based on measured or literature values of r_M weighted by the proportion of GM and WM within tissue‐segmented MRS volumes. Simulations were performed to test the sensitivity of this correction using different assumptions of r_M taken from previous studies. The tissue correction method was then validated by applying it to an independent dataset of in vivo GABA measurements using an empirically measured value of r_M. It was shown that incorrect assumptions of r_M can lead to overcorrection and inflation of GABA concentration measurements quantified in volumes composed predominantly of WM. For the independent dataset, GABA concentration was linearly related to GM tissue volume when only the water signal was corrected for partial volume effects. Performing a full correction that additionally accounts for partial volume effects ascribed to r_M successfully removed this dependence. With an appropriate assumption of the ratio of intrinsic GABA concentration in GM and WM, GABA measurements can be corrected for partial volume effects, potentially leading to a reduction in between‐participant variance, increased power in statistical tests and better discriminability of true effects.     

Complementarity of gluCEST and 1H‐MRS for the study of mouse models of Huntington's disease

Identification of relevant biomarkers is fundamental to understand biological processes of neurodegenerative diseases and to evaluate therapeutic efficacy. Atrophy of brain structures has been proposed as a biomarker, but it provides little information about biochemical events related to the disease. Here, we propose to identify early and relevant biomarkers by combining biological specificity provided by ¹H‐MRS and high spatial resolution offered by gluCEST imaging. For this, two different genetic mouse models of Huntington's disease (HD)—the Ki140CAG model, characterized by a slow progression of the disease, and the R6/1 model, which mimics the juvenile form of HD—were used. Animals were scanned at 11.7 T using a protocol combining ¹H‐MRS and gluCEST imaging. We measured a significant decrease in levels of N‐acetyl‐aspartate, a metabolite mainly located in the neuronal compartment, in HD animals, and the decrease seemed to be correlated with disease severity. In addition, variations of tNAA levels were correlated with striatal volumes in both models. Significant variations of glutamate levels were also observed in Ki140CAG but not in R6/1 mice. Thanks to its high resolution, gluCEST provided complementary insights, and we highlighted alterations in small brain regions such as the corpus callosum in Ki140CAG mice, whereas the glutamate level was unchanged in the whole brain of R6/1 mice. In this study, we showed that ¹H‐MRS can provide key information about biological processes occurring in vivo but was limited by the spatial resolution. On the other hand, gluCEST may finely point to alterations in unexpected brain regions, but it can also be blind to disease processes when glutamate levels are preserved. This highlights in a practical context the complementarity of the two methods to study animal models of neurodegenerative diseases and to identify relevant biomarkers.     

Six fucose‐α(1–2) sugars and α‐fucose assigned in the human brain using in vivo two‐dimensional MRS

A growing body of literature has indicated that fucose‐α(1–2)‐galactose sugars are implicated in the molecular mechanisms that underlie neuronal development, learning and memory in the human brain. An understanding of the in vivo roles played by these terminal fucose residues has been hampered by the lack of technology to non‐invasively monitor their levels in the human brain. We have implemented in vivo two‐dimensional MRS technology to examine the human brain in a 3‐T clinical MR scanner, and report that six fucose‐α(1–2)‐galactose residues and free α‐fucose are available for inspection. Fucose‐α(1–3)‐galactose residues cannot yet be assigned using this technology as they resonate under the water resonance. This new application offers an unprecedented insight into the molecular mechanisms by which fucosylated sugars contribute to neuronal processes and how they alter during development, ageing and disease. Copyright © 2014 John Wiley & Sons, Ltd.     

Applications of high‐resolution magic angle spinning MRS in biomedical studies II—Human diseases

High‐resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high‐resolution spectra of non‐liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non‐localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.     

Intra‐ and interindividual variability of fatty acid unsaturation in six different human adipose tissue compartments assessed by 1H‐MRS in vivo at 3 T

It is generally accepted that the amount and distribution of adipose tissue (AT) in the human body play an important role in the pathogenesis of metabolic diseases. In addition, metabolic effects of released saturated fatty acids (FAs) in blood are known to be more critical than those of unsaturated FAs. However, little is known about the variability in unsaturation of FAs in various AT compartments. The aim of this prospective study was the assessment of mono‐ and polyunsaturated FAs in various AT compartments by localized ¹H‐MRS in order to obtain insight into the intra‐ and interindividual variability. Associations of FA unsaturation with intrahepatic lipids (IHLs), insulin sensitivity and related AT volumes were analyzed. Fifty healthy Caucasians (36 male, 14 female) participated in this study. Spectroscopic examinations were performed in subcutaneous adipose tissue in the neck (SCAT_neck), abdominal deep subcutaneous adipose tissue (DSCAT), abdominal superficial subcutaneous adipose tissue (SSCAT), visceral adipose tissue (VAT), tibial bone marrow (BM) and subcutaneous adipose tissue of the lower leg (SCAT_calf) at 3 T. Unsaturated index (UI) was calculated by the ratio of olefinic and methyl resonances, polyunsaturated index (PUI) by the ratio of diallylic and methyl resonances. Volumes of AT compartments (by T₁‐weighted MRI) and IHL (single‐voxel STEAM) were assessed at 1.5 T, insulin sensitivity by an oral glucose tolerance test. UI was highest for SCAT_calf (0.622) and lowest for BM (0.527). Highest PUI was observed for SSCAT (0.108), lowest for BM (0.093). Significant intraindividual differences between UIs—but not PUIs—are present for most compartments. There is a non‐significant trend for higher UI in males but otherwise no correlation to anthropometric data (age, BMI). A significant negative correlation between UI and AT volume was observed for VAT but for none of the other compartments. Neither UIs nor PUIs show a relation with IHL; insulin sensitivity is significantly correlated to UI in BM (p < 0.01). Unsaturation indices in several distinct AT compartments are location dependent. Our cohort showed only moderate gender‐related differences, with a trend towards less unsaturated FAs (mainly PUI) in females. In BM, insulin resistant subjects are characterized by a higher UI compared with the insulin sensitive ones. Further studies in larger cohorts are necessary to gain further insight into unsaturation of AT.     

Initial investigation of glucose metabolism in mouse brain using enriched 17O‐glucose and dynamic 17O‐MRS

In this initial work, the in vivo degradation of ¹⁷O‐labeled glucose was studied during cellular glycolysis. To monitor cellular glucose metabolism, direct ¹⁷O‐magnetic resonance spectroscopy (MRS) was used in the mouse brain at 9.4 T. Non‐localized spectra were acquired with a custom‐built transmit/receive (Tx/Rx) two‐turn surface coil and a free induction decay (FID) sequence with a short TR of 5.4 ms. The dynamics of labeled oxygen in the anomeric 1‐OH and 6‐CH₂OH groups was detected using a Hankel–Lanczos singular value decomposition (HLSVD) algorithm for water suppression. Time‐resolved ¹⁷O‐MRS (temporal resolution, 42/10.5 s) was performed in 10 anesthetized (1.25% isoflurane) mice after injection of a 2.2 M solution containing 2.5 mg/g body weight of differently labeled ¹⁷O‐glucose dissolved in 0.9% physiological saline. From a pharmacokinetic model fit of the H₂¹⁷O concentration–time course, a mean apparent cerebral metabolic rate of ¹⁷O‐labeled glucose in mouse brain of CMR_Glc = 0.07 ± 0.02 μmol/g/min was extracted, which is of the same order of magnitude as a literature value of 0.26 ± 0.06 μmol/g/min reported by ¹⁸F‐fluorodeoxyglucose (¹⁸F‐FDG) positron emission tomography (PET). In addition, we studied the chemical exchange kinetics of aqueous solutions of ¹⁷O‐labeled glucose at the C1 and C6 positions with dynamic ¹⁷O‐MRS. In conclusion, the results of the exchange and in vivo experiments demonstrate that the C6‐¹⁷OH label in the 6‐CH₂OH group is transformed only glycolytically by the enzyme enolase into the metabolic end‐product H₂¹⁷O, whereas C1‐¹⁷OH ends up in water via direct hydrolysis as well as glycolysis. Therefore, dynamic ¹⁷O‐MRS of highly labeled ¹⁷O‐glucose could provide a valuable non‐radioactive alternative to FDG PET in order to investigate glucose metabolism.     

Effects of fat on MR‐measured metabolite signal strengths: implications for in vivo MRS studies of the human brain

Recent MRS studies have indicated that a higher body mass index (BMI) is associated with lower brain metabolite levels. Generally, individuals with higher BMIs have more body fat deposits than individuals with normal BMIs. This single‐voxel spectroscopy (SVS) study investigated possible effects of fat on MR‐measured metabolite signal areas, which may at least partly explain the observed associations of BMI with MR‐measured brain metabolite levels in vivo. SVS data were acquired at 4 T from a phantom containing N‐acetylaspartate, glutamate and creatine, as well as from three healthy male adults. Back fat obtained from pig was used to assess the effects of fat on metabolite signals. With the same voxel size and placement, the phantom was first scanned without fat (baseline), and then with 0.7‐cm‐ and 1.4‐cm‐thick fat layers placed on it. Each participant was also scanned first without fat and then with two 0.7‐cm fat layers, one placed beneath the occiput and the other on the forehead. Two spectra were acquired per participant from the anterior cingulate and the parieto‐occipital cortices. The metabolite resonance and corresponding water peak areas were then fitted and metabolite to water signal ratios were used for analyses. In both phantom and in vivo experiments, the metabolite‐to‐water ratios decreased in the presence of fat relative to baseline metabolite‐to‐water ratios. The reduced metabolite signals in the presence of fat reported here are reminiscent of the negative correlations observed between BMI and MR‐measured metabolite levels. These apparent physical effects of fat have potentially far‐reaching consequences for the accuracy of MR measurements of brain metabolite levels and their interpretation, particularly when large fat stores exist around the skull, such as in individuals with higher BMI. Copyright © 2013 John Wiley & Sons, Ltd.     

Errors in 1H‐MRS estimates of brain metabolite concentrations caused by failing to take into account tissue‐specific signal relaxation

Accurate measurement of brain metabolite concentrations with proton magnetic resonance spectroscopy (¹H‐MRS) can be problematic because of large voxels with mixed tissue composition, requiring adjustment for differing relaxation rates in each tissue if absolute concentration estimates are desired. Adjusting for tissue‐specific metabolite signal relaxation, however, also requires a knowledge of the relative concentrations of the metabolite in gray (GM) and white (WM) matter, which are not known a priori. Expressions for the estimation of the molality and molarity of brain metabolites with ¹H‐MRS are extended to account for tissue‐specific relaxation of the metabolite signals and examined under different assumptions with simulated and real data. Although the modified equations have two unknowns, and hence are unsolvable explicitly, they are nonetheless useful for the estimation of the effect of tissue‐specific metabolite relaxation rates on concentration estimates under a range of assumptions and experimental parameters using simulated and real data. In simulated data using reported GM and WM T₁ and T₂ times for N‐acetylaspartate (NAA) at 3 T and a hypothetical GM/WM NAA ratio, errors of 6.5–7.8% in concentrations resulted when TR = 1.5 s and TE = 0.144 s, but were reduced to less than 0.5% when TR = 6 s and TE = 0.006 s. In real data obtained at TR/TE = 1.5 s/0.04 s, the difference in the results (4%) was similar to that obtained with simulated data when assuming tissue‐specific relaxation times rather than GM–WM‐averaged times. Using the expressions introduced in this article, these results can be extrapolated to any metabolite or set of assumptions regarding tissue‐specific relaxation. Furthermore, although serving to bound the problem, this work underscores the challenge of correcting for relaxation effects, given that relaxation times are generally not known and impractical to measure in most studies. To minimize such effects, the data should be acquired with pulse sequence parameters that minimize the effect of signal relaxation.     

Quantitative comparison of post‐processing methods for reduction of frequency modulation sidebands in non‐water suppression 1H MRS

Non‐water suppression MRS (NWS MRS) has several advantages. First, the unsuppressed water signal can be used as internal calibration for metabolite quantification and as a reliable frequency/phase reference for retrospective motion correction. Second, it avoids the potential artifacts caused by incomplete water suppression (WS) and extra radiofrequency deposition from WS pulses. However, the frequency modulation (FM) sidebands originating from a large water signal will distort the spectrum. Among the methods proposed to solve the problems caused by FM sidebands, post‐acquisition processing methods are superior in flexibility for general use compared with experimental methods. In this study, we propose two algorithms based on advanced matrix decomposition to remove the FM sidebands. These methods, the simultaneous diagonalization (QZ) algorithm and its subsequent variant, the simultaneously generalized Schur decomposition (SGSD) algorithm, were numerically evaluated using computer simulations. In addition, we quantitatively compared the performance of these methods and the modulus method in an in vitro experiment and in vivo NWS MRS against conventional WS data. Our results show that the proposed SGSD algorithm can reduce the FM sidebands to achieve superior estimation of concentration on three major metabolites. This method can be applied directly to spectra pre‐acquired under various experimental conditions without modifying the acquisition sequences. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of the intrinsic radiosensitivity of glioma cells and monitoring of metabolite ratio changes after irradiation by 14.7‐T high‐resolution 1H MRS

Gliomas are the most common type of primary brain tumor. Radiation therapy (RT) is the primary adjuvant treatment to eliminate residual tumor tissue after surgery. However, the current RT guided by conventional imaging is unsatisfactory. A fundamental question is whether it is possible to further enhance the effectiveness and efficiency of RT based on individual radiosensitivity. In this research, to probe the correlation between radiosensitivity and the metabolite characteristics of glioma cells in vitro, a perchloric acid (PCA) extracting method was used to obtain water‐soluble metabolites [such as N‐acetylaspartate (NAA), choline (Cho), creatine (Cr) and succinate (Suc)]. Spectral patterns from these processed water‐soluble metabolite samples were acquired by in vitro 14.7‐T high‐resolution ¹H MRS. Survival fraction analysis was performed to test the intrinsic radiosensitivity of glioma cell lines. Good ¹H MRS of PCA extracts from glioma cells was obtained. The radiosensitivity of glioma cells correlated positively with the Cho/Cr and Cho/NAA ratios, but negatively with the Suc/Cr ratio. Irradiation of the C6 cell line at different X‐ray dosages led to changes in metabolite ratios and apoptotic rates. A plateau phase of metabolite ratio change and a decrease in apoptotic rate were found in the C6 cell line. We conclude that in vitro high‐resolution ¹H MRS possesses the sensitivity required to detect subtle biochemical changes at the cellular level. ¹H MRS may aid in the assessment of the individual radiosensitivity of brain tumors, which is pivotal in the identification of the biological target volume. Copyright © 2014 John Wiley & Sons, Ltd.