Different quantification algorithms may lead to different results: a comparison using proton MRS lipid signals

Experimental Basis Sets of Quantification of Brain 1H-Magnetic Resonance Spectroscopy at 3.0 T

In vivo short echo time (TE) proton magnetic resonance spectroscopy (1H-MRS) is a useful method for the quantification of human brain metabolites. The purpose of this study was to evaluate the performance of an in-house, experimentally measured basis set and compare it with the performance of a vendor-provided basis set. A 3T clinical scanner with 32-channel receive-only phased array head coil was used to generate 16 brain metabolites for the metabolite basis set. For voxel localization, point-resolved spin-echo sequence (PRESS) was used with volume of interest (VOI) positioned at the center of the phantoms. Two different basis sets were subjected to linear combination of model spectra of metabolite solutions in vitro (LCModel) analysis to evaluate the in-house acquired in vivo 1H-MR spectra from the left prefrontal cortex of 22 healthy subjects. To evaluate the performance of the two basis sets, the Cramer-Rao lower bounds (CRLBs) of each basis set were compared. The LCModel quantified the following metabolites and macromolecules: alanine (Ala), aspartate (Asp), γ-amino butyric acid (GABA), glucose (Glc), glutamine (Gln), glutamate (Glu), glutathione (GHS), Ins (myo-Inositol), lactate (Lac), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), taurine (Tau), phosphoryl-choline + glycerol-phosphoryl-choline (tCho), N-acetylaspartate + N-acetylaspartylglutamate (tNA), creatine + phosphocreatine (tCr), Glu + Gln (Glx) and Lip13a, Lip13b, Lip09, MM09, Lip20, MM20, MM12, MM14, MM17, Lip13a + Lip13b, MM14 + Lip13a + Lip13b + MM12, MM09 + Lip09, MM20 + Lip20. Statistical analysis showed significantly different CRLBs: Asp, GABA, Gln, GSH, Ins, Lac, NAA, NAAG, Tau, tCho, tNA, Glx, MM20, MM20 + Lip20 (p < 0.001), tCr, MM12, MM17 (p < 0.01), and Lip20 (p < 0.05). The estimated ratio of cerebrospinal fluid (CSF) in the region of interest was calculated to be about 5%. Fitting performances are better, for the most part, with the in-house basis set, which is more precise than the vendor-provided basis set. In particular, Asp is expected to have reliable CRLB (<30%) at high field (e.g., 3T) in the left prefrontal cortex of human brain. The quantification of Asp was difficult, due to the inaccuracy of Asp fitting with the vendor-provided basis set.

Inflammatory Blood Biomarker Kynurenine Is Linked With Elevated Neuroinflammation and Neurodegeneration in Older Adults: Evidence From Two 1H-MRS Post-Processing Analysis Methods

RATIONALE AND OBJECTIVES

Pro-inflammatory processes have been argued to play a role in conditions associated with cognitive decline and neurodegeneration, like aging and obesity. Only a limited number of studies have tried to measure both peripheral and central biomarkers of inflammation and examined their interrelationship. The primary aim of this study was to examine the hypothesis that chronic peripheral inflammation would be associated with neurometabolic changes that indicate neuroinflammation (the combined elevation of myoinositol and choline), brain gray matter volume decrease, and lower cognitive functioning in older adults.

MATERIALS AND METHODS

Seventy-four older adults underwent bio-impedance body composition analysis, cognitive testing with the Montreal Cognitive Assessment (MoCA), blood serum analysis of inflammatory markers interleukin-6 (IL-6) and kynurenine, magnetic resonance imaging (MRI), and proton magnetic resonance spectroscopy (¹H-MRS) of the brain. Neurometabolic findings from both Tarquin and LCModel ¹H-MRS post-processing software packages were compared. The regions of interest for MRI and ¹H-MRS measurements were dorsal posterior cingulate cortex (DPCC), left hippocampal cortex (HPC), left medial temporal cortex (MTC), left primary sensorimotor cortex (SM1), and right dorsolateral prefrontal cortex (DLPFC).

RESULTS

Elevated serum kynurenine levels were associated with signs of neuroinflammation, specifically in the DPCC, left SM1 and right DLPFC, and signs of neurodegeneration, specifically in the left HPC, left MTC and left SM1, after adjusting for age, sex and fat percentage (fat%). Elevated serum IL-6 levels were associated with increased Glx levels in left HPC, left MTC, and right DLPFC, after processing the ¹H-MRS data with Tarquin. Overall, the agreement between Tarquin and LCModel results was moderate-to-strong for tNAA, tCho, mIns, and tCr, but weak to very weak for Glx. Peripheral inflammatory markers (IL-6 and kynurenine) were not associated with older age, higher fat%, decreased brain gray matter volume loss or decreased cognitive functioning within a cohort of older adults.

CONCLUSION

Our results suggest that serum kynurenine may be used as a peripheral inflammatory marker that is associated with neuroinflammation and neurodegeneration, although not linked to cognition. Future studies should consider longitudinal analysis to assess the causal inferences between chronic peripheral and neuroinflammation, brain structural and neurometabolic changes, and cognitive decline in aging.

Comparison of different linear-combination modeling algorithms for short-TE proton spectra

Short-TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large-scale multi-site study compares the levels of the four major metabolite complexes in short-TE spectra estimated by three linear-combination modeling (LCM) algorithms. 277 medial parietal lobe short-TE PRESS spectra (TE = 35 ms) from a recent 3 T multi-site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor-specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was R 2 ¯ = 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean R 2 ¯ = 0.10). While mean estimates of major metabolite complexes broadly agree between linear-combination modeling algorithms at group level, correlations between algorithms are only weak-to-moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.

Cortical glutamate and gamma-aminobutyric acid over the course of a provoked migraine attack, a 7 Tesla magnetic resonance spectroscopy study

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7T MRS separately measured glutamate, glutamine and GABA towards triggered attacks.

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Visual cortex GABA levels increased towards a preictal migraine state.

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Visual cortex glutamate and glutamine levels were stable across migraine states.

Enhanced activity of the glutamatergic system has been linked to migraine pathophysiology. The present study aimed to assess the involvement of the glutamatergic system in the onset of attacks. We provoked attacks by infusion of glyceryl trinitrate (GTN; 0.5 µg/kg/min over 20 min) in 24 female episodic migraineurs without aura and 13 female age-matched healthy controls. Over the course of a single day participants were scanned three times at fixed time slots (baseline before GTN infusion, 90 min and 270 min after start of GTN infusion). Single-volume proton magnetic resonance spectra (¹H–MRS) were acquired at 7 Tesla from a volume of interest (VOI, 2x2x3 cm) in the visual cortex. We assessed the concentrations of glutamate, its major precursor glutamine, and its product gamma-aminobutyric acid (GABA) over the course of a provoked attack. The preictal state was defined as the period after GTN infusion until the migraine-like headache started, independent of possible experienced premonitory symptoms, and the ictal state was defined as the period with provoked migraine-like headache. Data were analyzed using a linear mixed-effect model for repeated measures. Glutamate and glutamine levels did not change from interictal to the preictal and ictal state. GABA levels increased from interictal towards the preictal state for migraine patients compared with healthy controls. We conclude that high resolution 7T MRS is able to show changes in the glutamatergic system towards a triggered migraine attack, by revealing an increased GABA concentration associated with the onset of a migraine attack.

Ultralong TE In Vivo 1 H MR Spectroscopy of Omega-3 Fatty Acids in Subcutaneous Adipose Tissue at 7 T

BACKGROUND

Omega-3 (n-3) fatty acids (FA) play and important role in neural development and other metabolic diseases such as obesity and diabetes. The knowledge about the in vivo content and distribution of n-3 FA in human body tissues is not well established and the standard quantification of FA is invasive and costly.

PURPOSE

To detect omega-3 (n-3 CH3 ) and non-omega-3 (CH3 ) methyl group resonance lines with echo times up to 1200 msec, in oils, for the assessment of n-3 FA content, and the n-3 FA fraction in adipose tissue in vivo.

STUDY TYPE

Prospective technical development.

POPULATION

Three oils with different n-3 FA content and 24 healthy subjects.

FIELD STRENGTH/SEQUENCE

Single-voxel MR spectroscopy (SVS) with a point-resolved spectroscopy (PRESS) sequence with an echo time (TE) of 1000 msec at 7 T.

ASSESSMENT

Knowledge about the J-coupling evolution of both CH3 resonances was used for the optimal detection of the n-3 CH3 resonance line at a TE of 1000 msec. The accuracy of the method in oils and in vivo was validated from a biopsy sample with gas chromatography analysis.

STATISTICAL TESTS

SVS data were compared to gas chromatography with the Pearson correlation coefficient.

RESULTS

T2 relaxation times in oils were assessed as follows: CH2 , 65 ± 22 msec; CH3 , 325 ± 7 msec; and n-3 CH3 , 628 ± 34 msec. The n-3 FA fractions from oil phantom experiments (n = 3) were in agreement with chromatography analysis and the comparison of in vivo obtained data with the results of chromatography analysis (n = 5) yielded a significant correlation (P = 0.029).

DATA CONCLUSION

PRESS with ultralong-TE can detect and quantify the n-3 CH3 signal in vivo at 7 T.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:71-82.

3D Chemical Shift-Encoded MRI for Volume and Composition Quantification of Abdominal Adipose Tissue During an Overfeeding Protocol in Healthy Volunteers

BACKGROUND

Overweight and obesity are major worldwide health concerns characterized by an abnormal accumulation of fat in adipose tissue (AT) and liver.

PURPOSE

To evaluate the volume and the fatty acid (FA) composition of the subcutaneous adipose tissue (SAT) and the visceral adipose tissue (VAT) and the fat content in the liver from 3D chemical-shift-encoded (CSE)-MRI acquisition, before and after a 31-day overfeeding protocol.

STUDY TYPE

Prospective and longitudinal study.

SUBJECTS

Twenty-one nonobese healthy male volunteers.

FIELD STRENGTH/SEQUENCE

A 3D spoiled-gradient multiple echo sequence and STEAM sequence were performed at 3T.

ASSESSMENT

AT volume was automatically segmented on CSE-MRI between L2 to L4 lumbar vertebrae and compared to the dual-energy X-ray absorptiometry (DEXA) measurement. CSE-MRI and MR spectroscopy (MRS) data were analyzed to assess the proton density fat fraction (PDFF) in the liver and the FA composition in SAT and VAT. Gas chromatography-mass spectrometry (GC-MS) analyses were performed on 13 SAT samples as a FA composition countermeasure.

STATISTICAL TESTS

Paired t-test, Pearson's correlation coefficient, and Bland-Altman plots were used to compare measurements.

RESULTS

SAT and VAT volumes significantly increased (P < 0.001). CSE-MRI and DEXA measurements were strongly correlated (r = 0.98, P < 0.001). PDFF significantly increased in the liver (+1.35, P = 0.002 for CSE-MRI, + 1.74, P = 0.002 for MRS). FA composition of SAT and VAT appeared to be consistent between localized-MRS and CSE-MRI (on whole segmented volume) measurements. A significant difference between SAT and VAT FA composition was found (P < 0.001 for CSE-MRI, P = 0.001 for MRS). MRS and CSE-MRI measurements of the FA composition were correlated with the GC-MS results (for ndb: r_MRS/GC-MS  = 0.83 P < 0.001, r_{CSE-MRI/GC-MS}  = 0.84, P = 0.001; for nmidb: r_MRS/GC-MS  = 0.74, P = 0.006, r_{CSE-MRI/GC-MS}  = 0.66, P = 0.020) DATA CONCLUSION: The follow-up of liver PDFF, volume, and FA composition of AT during an overfeeding diet was demonstrated through different methods. The CSE-MRI sequence associated with a dedicated postprocessing was found reliable for such quantification.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1587-1599.

Comparison of MRI-derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals

INTRODUCTION

The composition of fatty acids in the body is gaining increasing interest, and can be followed up noninvasively by quantitative magnetic resonance spectroscopy (MRS). However, current MRS quantification methods have been shown to provide different quantitative results in terms of lipid signals, with possible varying outcomes for a given biological examination. Quantitative magnetic resonance imaging using multigradient echo sequence (MGE-MRI) has recently been added to MRS approaches. In contrast, these methods fit the undersampled magnetic resonance temporal signal with a simplified model function (expressing the triglyceride [TG] spectrum with only three TG parameters), specific implementations and prior knowledge. In this study, an adaptation of an MGE-MRI method to MRS lipid quantification is proposed.

METHODS

Several versions of the method - with time data fully or undersampled, including or excluding the spectral peak T₂ knowledge in the fitting - were compared theoretically and on Monte Carlo studies with a time-domain, peak-fitting approach. Robustness, repeatability and accuracy were also inspected on in vitro oil acquisitions and test-retest in vivo subcutaneous adipose tissue acquisitions, adding results from the reference LCModel method.

RESULTS

On simulations, the proposed method provided TG parameter estimates with the smallest variability, but with a possible bias, which was mitigated by fitting on undersampled data and considering peak T₂ values. For in vitro measurements, estimates for all approaches were correlated with theoretical values and the best concordance was found for the usual MRS method (LCModel and peak fitting). Limited in vivo test-retest variability was found (4.1% for PUFAindx, 0.6% for MUFAindx and 3.6% for SFAindx), as for LCModel (7.6% for PUFAindx, 7.8% for MUFAindx and 3.0% for SFAindx).

CONCLUSION

This study shows that fitting the three TG parameters directly on MRS data is one valuable solution to circumvent the poor conditioning of the MRS quantification problem.

Comparison of reproducibility of single voxel spectroscopy and whole-brain magnetic resonance spectroscopy imaging at 3T

To date, single voxel spectroscopy (SVS) is the most commonly used MRS technique. SVS is relatively easy to use and provides automated and immediate access to the resulting spectra. However, it is also limited in spatial coverage. A new and very promising MRS technique allows for whole-brain MR spectroscopic imaging (WB-MRSI) with much improved spatial resolution. Establishing the reproducibility of data obtained using SVS and WB-MRSI is an important first step for using these techniques to evaluate longitudinal changes in metabolite concentration. The purpose of this study was to assess and directly compare the reproducibility of metabolite quantification at 3T using SVS and WB-MRSI in 'hand-knob' areas of motor cortices and hippocampi in healthy volunteers. Ten healthy adults were scanned using both SVS and WB-MRSI on three occasions one week apart. N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) were quantified using SVS and WB-MRSI with reference to both Cr and H₂ O. The reproducibility of each technique was evaluated using the coefficient of variation (CV), and the correspondence between the two techniques was assessed using Pearson correlation analysis. The measured mean (range) intra-subject CVs for SVS were 5.90 (2.65-10.66)% for metabolites (i.e. NAA, Cho, mI) relative to Cr, and 8.46 (4.21-21.07)% for metabolites (NAA, Cr, Cho, mI) relative to H₂ O. The mean (range) CVs for WB-MRSI were 7.56 (2.78-11.41)% for metabolites relative to Cr, and 7.79 (4.57-14.11)% for metabolites relative to H₂ O. Significant positive correlations were observed between metabolites quantified using SVS and WB-MRSI techniques when the Cr but not H₂ O reference was used. The results demonstrate that reproducibilities of SVS and WB-MRSI are similar for quantifying the four major metabolites (NAA, Cr, Cho, mI); both SVS and WB-MRSI exhibited good reproducibility. Our findings add reference information for choosing the appropriate ¹ H-MRS technique in future studies.

In vivo MRS for the assessment of mouse colon using a dedicated endorectal coil: initial findings

Inflammatory bowel disease is a common group of inflammation conditions that can affect the colon and the rectum. These pathologies require a careful follow-up of patients to prevent the development of colorectal cancer. Currently, conventional endoscopy is used to depict alterations of the intestinal walls, and biopsies are performed on suspicious lesions for further analysis (histology). MRS enables the in vivo analysis of biochemical content of tissues (i.e. without removing any samples). Combined with dedicated endorectal coils (ERCs), MRS provides new ways of characterizing alterations of tissues. An MRS in vivo protocol was specifically set up on healthy mice and on mice chemically treated to induce colitis. Acquisitions were performed on a 4.7 T system using a linear volume birdcage coil for the transmission of the B₁ magnetic field, and a dedicated ERC was used for signal reception. Colon-wall complex, lumen and visceral fat were assessed on healthy and treated mice with voxel sizes ranging from 0.125 μL to 2 μL while keeping acquisition times below 3 min. The acquired spectra show various biochemical contents such as α- and β-methylene but also glycerol backbone and diacyl. Choline was detected in tumoral regions. Visceral fat regions display a high lipid content with no water, whereas colon-wall complex exhibits both high lipid and high water contents. To the best of our knowledge, this is the first time that in vivo MRS using an ERC has been performed in the assessment of colon walls and surrounding structures. It provides keys for the in vivo characterization of small local suspicious lesions and offers complementary solutions to biopsies.

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

Proton magnetic resonance spectroscopy (¹ H-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 ¹ H-MRS metabolite quantification. It is currently unknown to what extent variations in the analysis pipeline used to quantify ¹ H-MRS data affect outcomes. The purpose of this study was to evaluate whether the quantification of identical ¹ H-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 ¹ H-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 ¹ H-MRS studies, and that basis sets used for processing should be made available to the scientific community.

Quantifying fat replacement of muscle by quantitative MRI in muscular dystrophy

The muscular dystrophies are rare orphan diseases, characterized by progressive muscle weakness: the most common and well known is Duchenne muscular dystrophy which affects young boys and progresses quickly during childhood. However, over 70 distinct variants have been identified to date, with different rates of progression, implications for morbidity, mortality, and quality of life. There are presently no curative therapies for these diseases, but a range of potential therapies are presently reaching the stage of multi-centre, multi-national first-in-man clinical trials. There is a need for sensitive, objective end-points to assess the efficacy of the proposed therapies. Present clinical measurements are often too dependent on patient effort or motivation, and lack sensitivity to small changes, or are invasive. Quantitative MRI to measure the fat replacement of skeletal muscle by either chemical shift imaging methods (Dixon or IDEAL) or spectroscopy has been demonstrated to provide such a sensitive, objective end-point in a number of studies. This review considers the importance of the outcome measures, discusses the considerations required to make robust measurements and appropriate quality assurance measures, and draws together the existing literature for cross-sectional and longitudinal cohort studies using these methods in muscular dystrophy.

Preclinical In vivo Imaging for Fat Tissue Identification, Quantification, and Functional Characterization

Localization, differentiation, and quantitative assessment of fat tissues have always collected the interest of researchers. Nowadays, these topics are even more relevant as obesity (the excess of fat tissue) is considered a real pathology requiring in some cases pharmacological and surgical approaches. Several weight loss medications, acting either on the metabolism or on the central nervous system, are currently under preclinical or clinical investigation. Animal models of obesity have been developed and are widely used in pharmaceutical research. The assessment of candidate drugs in animal models requires non-invasive methods for longitudinal assessment of efficacy, the main outcome being the amount of body fat. Fat tissues can be either quantified in the entire animal or localized and measured in selected organs/regions of the body. Fat tissues are characterized by peculiar contrast in several imaging modalities as for example Magnetic Resonance Imaging (MRI) that can distinguish between fat and water protons thank to their different magnetic resonance properties. Since fat tissues have higher carbon/hydrogen content than other soft tissues and bones, they can be easily assessed by Computed Tomography (CT) as well. Interestingly, MRI also discriminates between white and brown adipose tissue (BAT); the latter has long been regarded as a potential target for anti-obesity drugs because of its ability to enhance energy consumption through increased thermogenesis. Positron Emission Tomography (PET) performed with 18F-FDG as glucose analog radiotracer reflects well the metabolic rate in body tissues and consequently is the technique of choice for studies of BAT metabolism. This review will focus on the main, non-invasive imaging techniques (MRI, CT, and PET) that are fundamental for the assessment, quantification and functional characterization of fat deposits in small laboratory animals. The contribution of optical techniques, which are currently regarded with increasing interest, will be also briefly described. For each technique the physical principles of signal detection will be overviewed and some relevant studies will be summarized. Far from being exhaustive, this review has the purpose to highlight some strategies that can be adopted for the in vivo identification, quantification, and functional characterization of adipose tissues mainly from the point of view of biophysics and physiology.

Differential diagnosis of a vanishing brain space occupying lesion in a child

We describe clinical, diagnostic features and follow up of a patient with a vanishing brain lesion. A 14-year-old child admitted to the department of Neurology at September 2009 with a history of subacute onset of fever, anorexia, vomiting, blurring of vision and right hemiparesis since one month. Magnetic resonance imaging (MRI) of the brain revealed presence of intra-axial large mass (25 mm × 19 mm) in the left temporal lobe and the brainstem which showed hypointense signal in T1W and hyperintense signals in T2W and fluid attenuated inversion recovery (FLAIR) images and homogenously enhanced with gadolinium (Gd). It was surrounded by vasogenic edema with mass effect. Intravenous antibiotics, mannitol (2 g/12 h per 2 d) and dexamethasone (8 mg/12 h) were given to relief manifestations of increased intracranial pressure. Whole craniospinal radiotherapy (brain = 4000 CGy/20 settings per 4 wk; Spinal = 2600/13 settings per 3 wk) was given based on the high suspicion of neoplastic lesion (lymphoma or glioma). Marked clinical improvement (up to complete recovery) occurred within 15 d. Tapering of the steroid dose was done over the next 4 mo. Follow up with MRI after 3 mo showed small lesion in the left antero-medial temporal region with hypointense signal in T1W and hyperintense signals in T2W and FLAIR images but did not enhance with Gd. At August 2012, the patient developed recurrent generalized epilepsy. His electroencephalography showed the presence of left temporal focus of epileptic activity. MRI showed the same lesion as described in the follow up. The diffusion weighted images were normal. The seizures frequency was decreased with carbamazepine therapy (300 mg/12 h). At October 2014, single voxel proton (1H) MR spectroscopy (MRS) showed reduced N-acetyl-aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, NAA/Cho ratios consistent with absence of a neoplasm and highly suggested presence of gliosis. A solitary brain mass in a child poses a considerable diagnostic difficulty. MRS provided valuable diagnostic differentiation between tumor and pseudotumor lesions.

Quantitative analysis of ³¹P NMR spectra of soil extracts--dealing with overlap of broad and sharp signals

Solution (31)P NMR analysis following extraction with a mixture of sodium hydroxide and ethylenediaminetetraacetic acid is the most widely used method for detailed characterization of soil organic P. However, quantitative analysis of the (31)P NMR spectra is complicated by severe spectral overlap in the monoester region. Various deconvolution procedures have been developed for the task, yet none of these are widely accepted or implemented. In this mini-review, we first describe and compare these varying approaches. We then review approaches to similar issues of spectral overlap in biomedical science applications including NMR-based metabolic profiling and analyzing (31)P magnetic resonance spectra of ex vivo and in vivo intact tissues. The greater maturity and resourcing of this biomedical research means that a wider variety of approaches has been developed. Of particular relevance are approaches to dealing with overlap of broad and sharp signals. Although the existence of this problem is still debated in the context of soil analyses, not only is it well-recognized in biomedical applications, but multiple approaches have been developed to deal with it, including T2 editing and time-domain fitting. Perhaps the most transferable concept is the incorporation of 'prior knowledge' in the fitting of spectra. This is well established in biomedical applications but barely touched in soil analyses. We argue that shortcuts to dealing with overlap in the monoester region (31)P NMR soil spectra are likely to be found in the biomedical literature, although some degree of adaptation will be necessary.