Changes in mouse brain metabolism following a convulsive dose of soman: a proton HRMAS NMR study.

Soman, an irreversible organophosphorus cholinesterase inhibitor, induces status epilepticus and, in sensitive brain areas, seizure-related brain damage (e.g. brain edema and neuronal loss). The brain metabolic disturbances associated with these events are ill known. In the present study, we thus evaluated these changes in a murine model of soman-induced status epilepticus up to 7 days after intoxication. Mice, protected by HI-6 and atropine methyl nitrate, were poisoned with soman (172 microg/kg) and then sacrificed at set time points, from 1 h to 7 days. Brain biopsies from the piriform cortex (Pir) and cerebellum (Cer) were analyzed by 1H HRMAS NMR spectroscopy. Spectra were then analyzed using both a supervised multivariate analysis and the QUEST procedure of jMRUI for the quantification of 17 metabolites. The multivariate analysis clearly showed the metabolic differences between a damaged structure (Pir) and a structure with less prominent changes (cerebellum) and helped to globally assess the time course of metabolic changes. Analysis of the individual metabolites showed that the major changes took place in the piriform cortex but that cerebellum was not change-free. The most prominent changes in the former were an early (1-4 h) increase in alanine and acetate, a delayed increase in lactate, glycerophosphocholine and glutamine as well as a delayed decrease in myo-inositol and N-acetylaspartate. A week after poisoning, some metabolic disturbances were still present. Further research will be necessary to clarify what could be the involvement of these metabolites in physiological processes and how they might become useful surrogate markers of brain damage and repair.

Quantitation with QUEST of brain HRMAS-NMR signals: application to metabolic disorders in experimental epileptic seizures.

Quantitation of High Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) signals enables establishing reference metabolite profiles of ex vivo tissues. Signals are often contaminated by a background signal originating mainly from macromolecules and lipids and by residual water which hampers proper quantitation. We show that automatic quantitation of HRMAS signals, even in the presence of a background, can be achieved by the semi-parametric algorithm QUEST based on prior knowledge of a metabolite basis-set. The latter was quantum-mechanically simulated with NMR-SCOPE and requires accurate spin parameters. The region of interest of spectra is a small part of the full spectral bandwidth. Reducing the computation time inherent to the large number of data-points is possible by using ER-Filter in a preprocessing step. Through Monte-Carlo studies, we analyze the performances of quantitation without and with ER-Filtering. Applications of QUEST to quantitation of 1H ex vivo HRMAS-NMR data of mouse brains after intoxication with soman, are demonstrated. Metabolic profiles obtained during status epilepticus and later when neuronal lesions are installed, are established. Acetate, Alanine, Choline and gamma-amino-butyric acid concentrations increase in the piriform cortex during the initial status epilepticus, when seizures are maximum; Lactate and Glutamine concentrations increase while myo-Inositol and N-acetylaspartate concentrations decrease when neuronal lesions are clearly installed.

Semi-parametric estimation in magnetic resonance spectroscopy: automation of the disentanglement procedure.

Semi-parametric disentanglement of parametric parts from non-parametric parts of a signal is a universal problem. This study concerns estimation of metabolite concentrations from in vivo Magnetic Resonance Spectroscopy (MRS) signals. Due to in vivo conditions, so-called macro-molecules contribute non-parametric components to the signals. Disentanglement is achieved by exploiting prior knowledge about the parametric and non-parametric parts directly in the measurement domain. Moreover, Cramér-Rao bounds on the non-parametric part are derived. These expressions are used to automate the disentanglement procedure.

Comparison of two strategies of background-accommodation: influence on the metabolite concentration estimation from in vivo Magnetic Resonance Spectroscopy data.

Localized proton Magnetic Resonance Spectroscopy brain signals acquired at short echo-time contain contributions from metabolites, water and a ;background' which mainly originates from macromolecules and lipids. The purpose of the present study was to compare the influence of the background-accommodation strategy on the metabolite concentration estimates. Two strategies were investigated to accommodate the background, 1) the measured background signal was incorporated in the metabolite basis-set; and 2) the background signal was estimated and subtracted from the in vivo signal using Subtract-QUEST. The influence of the background-accommodation strategy was addressed with the aid of Monte Carlo and in vivo studies. For the considered signals of this study, the concentration estimates obtained using the first approach were below those obtained with Subtract-QUEST. Indeed, the presence of residual contribution of metabolite signals with short longitudinal relaxation times (T1) in the measured background led to an underestimation of metabolite concentration estimates. Conversely, the observed underestimation of the background contribution using Subtract-QUEST led to an overestimation of the metabolite estimates.

Quantum chemistry-based NMR spin Hamiltonian parameters of GABA for quantitation in magnetic resonance spectroscopy.

Chemical shifts delta and spin-spin coupling constants J have been calculated using quantum chemistry approaches for the gamma-amino butyric acid GABA which is a brain metabolite. Two theoretical methods HF and DFT/B3LYP, two basis sets 6-31G* and 6-311+G(2d,p) and two gauge-invariant methods CSGT and GIAO have been used. From delta and J values, NMR spectra have been obtained from the strongly coupled spin system Hamiltonian using the NMR-SCOPE package. Solvent effects have been considered within the polarisable continuum model. Comparisons between calculated and experimental NMR spectra at 300 MHz show that our best results correspond to the B3LYP/6-311+G(2d,p)-GIAO calculations. They are seen to be in good agreement with experiment. This demonstrates the usefulness of quantum chemistry methods for estimating NMR spin Hamiltonian parameters involved in specific algorithms used for quantitation of metabolites such as GABA.

Time-domain semi-parametric estimation based on a metabolite basis set.

A novel and fast time-domain quantitation algorithm--quantitation based on semi-parametric quantum estimation (QUEST)--invoking optimal prior knowledge is proposed and tested. This nonlinear least-squares algorithm fits a time-domain model function, made up from a basis set of quantum-mechanically simulated whole-metabolite signals, to low-SNR in vivo data. A basis set of in vitro measured signals can be used too. The simulated basis set was created with the software package NMR-SCOPE which can invoke various experimental protocols. Quantitation of 1H short echo-time signals is often hampered by a background signal originating mainly from macromolecules and lipids. Here, we propose and compare three novel semi-parametric approaches to handle such signals in terms of bias-variance trade-off. The performances of our methods are evaluated through extensive Monte-Carlo studies. Uncertainty caused by the background is accounted for in the Cramér-Rao lower bounds calculation. Valuable insight about quantitation precision is obtained from the correlation matrices. Quantitation with QUEST of 1H in vitro data, 1H in vivo short echo-time and 31P human brain signals at 1.5 T, as well as 1H spectroscopic imaging data of human brain at 1.5 T, is demonstrated.

Metabolite concentrations of healthy mouse brain by Magnetic Resonance Spectroscopy at 7 Tesla.

In vivo1H short echo-time Magnetic Resonance spectra are made up of overlapping spectral components from many metabolites. Typically, they exibit low signal-to-noise ratio. Metabolite concentrations are obtained by quantitating such spectra. Quantitation is difficult due to the superposition of metabolite resonances, macromolecules, lipids and water residue contributions. A fitting algorithm invoking extensive prior knowledge is needed. We quantitated1H in vivo mouse brain spectra obtained at 7 Tesla using the time-domain QUEST method combined with in vitro metabolite basis set signals. Brain metabolite concentrations estimated from eight mouse brain signals are compared to previously reported results.

Time-domain quantitation of 1H short echo-time signals: background accommodation.

Quantitation of 1H short echo-time signals is often hampered by a background signal originating mainly from macromolecules and lipids. While the model function of the metabolite signal is known, that of the macromolecules is only partially known. We present time-domain semi-parametric estimation approaches based on the QUEST quantitation algorithm (QUantitation based on QUantum ESTimation) and encompassing Cramér-Rao bounds that handle the influence of 'nuisance' parameters related to the background. Three novel methods for background accommodation are presented. They are based on the fast decay of the background signal in the time domain. After automatic estimation, the background signal can be automatically (1) subtracted from the raw data, (2) included in the basis set as multiple components, or (3) included in the basis set as a single entity. The performances of these methods combined with QUEST are evaluated through extensive Monte Carlo studies. They are compared in terms of bias-variance trade-off. Because error bars on the amplitudes are of paramount importance for diagnostic reliability, Cramér-Rao bounds accounting for the uncertainty caused by the background are proposed. Quantitation with QUEST of in vivo short echo-time (1)H human brain with estimation of the background is demonstrated.

A distributed computing system for magnetic resonance imaging: Java-based processing and binding of XML.

Recently we have developed a Java-based heterogeneous distributed computing system for the field of magnetic resonance imaging (MRI). It is a software system for embedding the various image reconstruction algorithms that we have created for handling MRI data sets with sparse sampling distributions. Since these data sets may result from multi-dimensional MRI measurements our system has to control the storage and manipulation of large amounts of data. In this paper we describe how we have employed the extensible markup language (XML) to realize this data handling in a highly structured way. To that end we have used Java packages, recently released by Sun Microsystems, to process XML documents and to compile pieces of XML code into Java classes. We have effectuated a flexible storage and manipulation approach for all kinds of data within the MRI system, such as data describing and containing multi-dimensional MRI measurements, data configuring image reconstruction methods and data representing and visualizing the various services of the system. We have found that the object-oriented approach, possible with the Java programming environment, combined with the XML technology is a convenient way of describing and handling various data streams in heterogeneous distributed computing systems.

Dynamic magnetic resonance imaging paragraph sign with radial scanning: a post-acquisition paragraph sign keyhole approach.

A method - PA-keyhole - for 2D/3D dynamic magnetic resonance imaging with radial scanning is proposed. PA-keyhole exploits the inherent strong oversampling in the center of k-space, which contains crucial temporal information regarding contrast evolution. The method is based on: (1). a rearrangement of the temporal order of 2D/3D isotropic distributions of trajectories during the scan into subdistributions according to the desired time resolution, (2). a new post-acquisition keyhole approach based on the replacement of the central disk/sphere in k-space using data solely from a subdistribution, and (3). reconstruction of 2D/3D dynamic (time-resolved) images using 2D/3D-gridding with Pipe's approach to the sampling density compensation and 2D/3D-IFFT. The scan time is not increased with respect to a conventional 2D/3D radial scan of the same spatial resolution; in addition, one benefits from the dynamic information. The abilities of PA-keyhole and the sliding window techniques to restore simulated dynamic contrast changes are compared. Results are shown both for 2D and 3D dynamic imaging using experimental data. An application to in-vivo ventilation of rat lungs using hyperpolarized helium is demonstrated.

MR image reconstruction algorithms for sparse k-space data: a Java-based integration.

We have worked on multi-dimensional magnetic resonance imaging (MRI) data acquisition and related image reconstruction methods that aim at reducing the MRI scan time. To achieve this scan-time reduction we have combined the approach of 'increasing the speed' of k-space acquisition with that of 'deliberately omitting' acquisition of k-space trajectories (sparse sampling). Today we have a whole range of (sparse) sampling distributions and related reconstruction methods. In the context of a European Union Training and Mobility of Researchers project we have decided to integrate all methods into one coordinating software system. This system meets the requirements that it is highly structured in an object-oriented manner using the Unified Modeling Language and the Java programming environment, that it uses the client-server approach, that it allows multi-client communication sessions with facilities for sharing data and that it is a true distributed computing system with guaranteed reliability using core activities of the Java Jini package.

Cramér-Rao bounds: an evaluation tool for quantitation.

The Cramér-Rao lower bounds (CRBs) are the lowest possible standard deviations of all unbiased model parameter estimates obtained from the data. Consequently they give insight into the potential performance of quantitation estimators. Using analytical CRB expressions for spectral parameters of singlets and doublets in noise, one is able to judge the precision as a function of spectral and experimental parameters. We point out the usefulness of these expressions for experimental design. The influence of constraints (chemical prior knowledge) on spectral parameters of the peaks of doublets is demonstrated and the inherent benefits for quantitation are shown. Abbreviations used: CRB Cramér-Rao lower bounds

Current awareness.

In order to keep subscribers up-to-date with the latest developments in their field, John Wiley & Sons are providing a current awareness service in each issue of the journal. The bibliography contains newly published material in the field of NMR in biomedicine. Each bibliography is divided into 9 sections: 1 Books, Reviews ' Symposia; 2 General; 3 Technology; 4 Brain and Nerves; 5 Neuropathology; 6 Cancer; 7 Cardiac, Vascular and Respiratory Systems; 8 Liver, Kidney and Other Organs; 9 Muscle and Orthopaedic. Within each section, articles are listed in alphabetical order with respect to author. If, in the preceding period, no publications are located relevant to any one of these headings, that section will be omitted.

Java-based graphical user interface for the MRUI quantitation package.

This article describes the Java-based version of the magnetic resonance user interface (MRUI) quantitation package. This package allows MR spectroscopists to easily perform time-domain analysis of in vivo MR spectroscopy data. We show that the Java programming language is very well suited for developing highly interactive graphical software applications such as the MRUI software. We have also established that MR quantitation algorithms, programmed in other languages, can easily be embedded into the Java-based MRUI by using the Java native interface (JNI). This new graphical user interface (GUI) has been conceived for the processing of large data sets and uses prior knowledge data-bases to make interactive quantitation algorithms more userfriendly.

Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals.

This article describes a Java-based graphical user interface for the magnetic resonance user interface (MRUI) quantitation package. This package allows MR spectroscopists to easily perform time-domain analysis of in vivo/medical MR spectroscopy data. We have found that the Java programming language is very well suited for developing highly interactive graphical software applications such as the MRUI system. We also have established that MR quantitation algorithms, programmed in the past in other languages, can easily be embedded into the Java-based MRUI by using the Java native interface (JNI).

Age dependence of human gastrocnemius Mg2+: fitting 31P-NMR spectra using quantum mechanics-based prior knowledge.

The age dependence of human gastrocnemius Mg2+ concentration is demonstrated. To quantitate Mg2+ concentration, an original and accurate fitting algorithm using quantum mechanics-based prior knowledge is detailed. In a group of 28 volunteers (14 females) in the age range 5-80 years, pH, PCr/ATP and Pi/ATP values in the gastrocnemius were 7.02 +/- 0.02 pH, 4.16 +/- 0.33 and 0.13 +/- 0.02, respectively and independent of age and sex. By contrast, intracellular Mg2+ concentration (mM) decreased linearly (p < 0.05) with age (Mg2+ = 0.7803 +/- 0.0247-0.0027 +/- 0.0005 * age). No difference was found between sexes. From these results, it follows that care must be taken when comparing muscle Mg2+ data from subjects of different age. The hypothesis can be put forward that during aging insufficient intake and/or increased depletion of Mg2+ (e.g., intestinal hypoabsorption or urinary leakage) may affect the musculoskeletal system.

Cramer-Rao bound expressions for parametric estimation of overlapping peaks: influence of prior knowledge

We have derived analytical expressions of the Cramer-Rao lower bounds on spectral parameters for singlet, doublet, and triplet peaks in noise. We considered exponential damping (Lorentzian lineshape) and white Gaussian noise. The expressions, valid if a sufficiently large number of samples is used, were derived in the time domain for algebraic convenience. They enable one to judge the precision of any unbiased estimator as a function of the spectral and experimental parameters, which is useful for quantitation objectives and experimental design. The influence of constraints (chemical prior knowledge) on parameters of the peaks of doublets and triplets is demonstrated both analytically and numerically and the inherent benefits for quantitation are shown. Our expressions also enable analysis of spectra comprising many peaks. Copyright 2000 Academic Press.

MR spectroscopy of bilateral thalamic gliomas.

This study reports the MR spectroscopic patterns of two patients with bithalamic glioma. In one patient, phosphorus (31P) MR spectroscopy was performed. In both patients, the proton MR spectroscopic scans showed an increased creatine-phosphocreatine peak in the tumor. In the patient who underwent 31P-MR spectroscopy, an increased phosphocreatine peak was also observed. This group of thalamic tumors may be distinguished from other gliomas clinically, radiologically, and metabolically.

The beneficial influence of prior knowledge on the quantitation of in vivo magnetic resonance spectroscopy signals.

RATIONALE AND OBJECTIVES: This work concerns quantitation of in vivo magnetic resonance spectroscopy signals and the influence of prior knowledge on the precision of parameter estimates. The authors point out how prior knowledge can be used for experiments. METHODS: The Cramer-Rao lower bounds formulae of the noise-related standard deviations on spectral parameters for doublets and triplets were derived. Chemical prior knowledge of the multiplet structures was used. RESULTS: The benefit of chemical prior knowledge was estimated for doublet and triplet structures of arbitrary shape. Then, it was used to quantify in vivo 31P time-series signals of rat brain. CONCLUSIONS: Analytic expressions of errors on parameter estimates were derived, enabling prediction of the benefit of prior knowledge on quantitation results. These formulae allow us to state, for a given noise level, if the quantitation of strongly overlapping peaks such as adenosine triphosphate multiplets can be performed successfully.

Absolute metabolite quantification by in vivo NMR spectroscopy: V. Multicentre quantitative data analysis trial on the overlapping background problem.

The goal of this study was to establish the best approach for quantifying nuclear magnetic resonance (NMR) lines, that in the frequency domain are overlapping with broad, unwanted background features. To perform the quantitative data analysis in a controlled way, test signals were designed and utilised, derived from two different real-world in vivo nuclear magnetic resonance signals. One of the main conclusions of the study was that the quantification methods currently available to the biomedical research groups can deliver the correct values of the quantitative parameters, but that great care should be taken in using optimal input parameters for the computer programs concerned.