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.

Cholinergic Neurotransmission in the Posterior Insular Cortex Is Altered in Preclinical Models of Neuropathic Pain: Key Role of Muscarinic M2 Receptors in Donepezil-Induced Antinociception

Neuropathic pain is one of the most debilitating pain conditions, yet no therapeutic strategy has been really effective for its treatment. Hence, a better understanding of its pathophysiological mechanisms is necessary to identify new pharmacological targets. Here, we report important metabolic variations in brain areas involved in pain processing in a rat model of oxaliplatin-induced neuropathy using HRMAS (1)H-NMR spectroscopy. An increased concentration of choline has been evidenced in the posterior insular cortex (pIC) of neuropathic animal, which was significantly correlated with animals' pain thresholds. The screening of 34 genes mRNA involved in the pIC cholinergic system showed an increased expression of the high-affinity choline transporter and especially the muscarinic M2 receptors, which was confirmed by Western blot analysis in oxaliplatin-treated rats and the spared nerve injury model (SNI). Furthermore, pharmacological activation of M2 receptors in the pIC using oxotremorine completely reversed oxaliplatin-induced mechanical allodynia. Consistently, systemic treatment with donepezil, a centrally active acetylcholinesterase inhibitor, prevented and reversed oxaliplatin-induced cold and mechanical allodynia as well as social interaction impairment. Intracerebral microdialysis revealed a lower level of acetylcholine in the pIC of oxaliplatin-treated rats, which was significantly increased by donepezil. Finally, the analgesic effect of donepezil was markedly reduced by a microinjection of the M2 antagonist, methoctramine, within the pIC, in both oxaliplatin-treated rats and spared nerve injury rats. These findings highlight the crucial role of cortical cholinergic neurotransmission as a critical mechanism of neuropathic pain, and suggest that targeting insular M2 receptors using central cholinomimetics could be used for neuropathic pain treatment.

SIGNIFICANCE STATEMENT

Our study describes a decrease in cholinergic neurotransmission in the posterior insular cortex in neuropathic pain condition and the involvement of M2 receptors. Targeting these cortical muscarinic M2 receptors using central cholinomimetics could be an effective therapy for neuropathic pain treatment.

Optimized quantitative magnetic resonance spectroscopy for clinical routine

Several practical obstacles in data handling and evaluation complicate the use of quantitative localized magnetic resonance spectroscopy (qMRS) in clinical routine MR examinations. To overcome these obstacles, a clinically feasible MR pulse sequence protocol based on standard available MR pulse sequences for qMRS has been implemented along with newly added functionalities to the free software package jMRUI-v5.0 to make qMRS attractive for clinical routine. This enables (a) easy and fast DICOM data transfer from the MR console and the qMRS-computer, (b) visualization of combined MR spectroscopy and imaging, (c) creation and network transfer of spectroscopy reports in DICOM format, (d) integration of advanced water reference models for absolute quantification, and (e) setup of databases containing normal metabolite concentrations of healthy subjects. To demonstrate the work-flow of qMRS using these implementations, databases for normal metabolite concentration in different regions of brain tissue were created using spectroscopic data acquired in 55 normal subjects (age range 6-61 years) using 1.5T and 3T MR systems, and illustrated in one clinical case of typical brain tumor (primitive neuroectodermal tumor). The MR pulse sequence protocol and newly implemented software functionalities facilitate the incorporation of qMRS and reference to normal value metabolite concentration data in daily clinical routine.

Influence of measured and simulated basis sets on metabolite concentration estimates

By quantification of brain metabolites, localized brain proton MRS can non-invasively provide biochemical information from distinct regions of the brain. Quantification of short-TE signals is usually based on a metabolite basis set. The basis set can be obtained by two approaches: (1) by measuring the signals of metabolites in aqueous solution; (2) by quantum-mechanically simulating the theoretical metabolite signals. The purpose of this study was to compare the effect of these two approaches on metabolite concentration estimates. Metabolite concentrations were quantified with the QUEST method, using both approaches. A comparison was performed with the aid of Monte Carlo studies, by using signals simulated from both basis sets. The best results were obtained when the basis set used for the fit was the same as that used to simulate the Monte Carlo signals. This comparison was also performed using in vivo short-TE signals acquired at 7 T from the central region of rat brains. The concentration estimates, with confidence intervals, obtained using both basis sets were in good agreement with values from the literature. The in vivo study showed that, in general, the differences between the estimates obtained with the two basis sets were not statistically significant or scientifically important. Consequently, a simulated basis set can be used in place of a measured basis set.

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.

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.

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.

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.

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.

Retrospective intra-scan motion correction

This paper analyzes the effects of intra-scan motion and demonstrates the possibility of correcting them directly in k-space with a new automatic retrospective method. The method is presented for series of 2D acquisitions with Cartesian sampling. Using a reference k-space acquisition (corrected for translations) within the series, intra-scan motion parameters are accurately estimated for each trajectory in k-space of each data set in the series resulting in pseudo-random sample positions. The images are reconstructed with a Bayesian estimator that can handle sparse arbitrary sampling in k-space and reduces intra-scan rotation artefacts to the noise level. The method has been assessed by means of a Monte Carlo study on axial brain images for different signal-to-noise ratios. The accuracy of motion estimates is better than 0.1 degrees for rotation, and 0.1 and 0.05 pixel, respectively, for translation along the read and phase directions for signal-to-noise ratios higher than 6 of the signals on each trajectory. An example of reconstruction from experimental data corrupted by head motion is also given.

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.

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.

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).

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.

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

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.

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.

SRS-FT, a Fourier imaging method based on sparse radial scanning and Bayesian estimation

A new 3D Fourier imaging method based on sparse radial scanning (SRS-FT) of k space is proposed. It allows acquisition of FIDs and is therefore well suited to imaging objects with very short T2. Use of a Bayesian procedure allows (1) an important reduction of scan time to below that of the projection-reconstruction (PR) method by reducing the number of "Cartesian radial" encoding directions, and (2) a good image quality by estimating missing and corrupted Cartesian samples. SRS-FT images reconstructed from FIDs are compared to conventional FT and PR images.

Automatic in vivo NMR data processing based on an enhancement procedure and linear prediction method

A new data processing method for in vivo NMR data quantitation is presented. This method (EPLPSVD) is based on the enhancement procedure (EP) proposed by J. A. Cadzow (IEEE Trans. Acoust. Speech Signal Process. 36, 49, 1988) followed by the usual linear prediction method using the singular value decomposition (LPSVD). The evaluation of this protocol is performed using synthesized 31P signals with different signal-to-noise ratios. A Monte-Carlo simulation as a function of signal-to-noise ratio (SNR) has proved that EPLPSVD leads to unbiased estimated values of parameters. Then the Cramer-Rao method yields reliable confidence intervals for the estimated parameters. The estimates of NMR parameters using EPLPSVD are reliable and accurate for SNR > or = 1.2 while the LPSVD method failed for SNR < or = 4. This protocol is applied to analyze automatically a series of 31P free induction decays obtained from the human gastrocnemius muscle during exercise. Spectral parameters with their confidence intervals, curves of relative intensity variations in phosphocreatine and inorganic phosphate, and pH curves are automatically provided.

Improving data acquisition parameters of 31P in vivo spectra for signal analysis in the time domain

To obtain reliable NMR quantitation, experimental cautions concerning data acquisition must be taken when using automatic predictive calculations. For this study, 2000 31P in vitro and in vivo spectra were processed, using the enhancement procedure with linear prediction using singular value decomposition (EPLPSVD) method, and analyzed. The effects of quadrature detection modes (simultaneous or sequential), of the number of time-domain samples used are investigated and experimental conditions such as sample motions and spectral width are discussed.

Modified stimulated echo sequence for elimination of signals from stationary spins in MRI

Simple modification of the basic stimulated echo sequence (MSTE), including bipolar gradient modulation, permits one to generate relative motion phase modulations between the two STE magnetization components. It is shown how this self-referencing process can provide flow enhancement without combination of separated images.