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

Denoising NMR time-domain signal by singular-value decomposition accelerated by graphics processing units

We present a post-processing method that decreases the NMR spectrum noise without line shape distortion. As a result the signal-to-noise (S/N) ratio of a spectrum increases. This method is called Cadzow enhancement procedure that is based on the singular-value decomposition of time-domain signal. We also provide software whose execution duration is a few seconds for typical data when it is executed in modern graphic-processing unit. We tested this procedure not only on low sensitive nucleus (29)Si in hybrid materials but also on low gyromagnetic ratio, quadrupole nucleus (87)Sr in reference sample Sr(NO3)2. Improving the spectrum S/N ratio facilitates the determination of T/Q ratio of hybrid materials. It is also applicable to simulated spectrum, resulting shorter simulation duration for powder averaging. An estimation of the number of singular values needed for denoising is also provided.

Increasing sensitivity in determining chemical shifts in one dimensional Lorentzian NMR spectra

An algorithm is presented for one-dimensional NMR systems that employs nonlinear, non-Fourier methods to convert noisy time-dependent free induction decay (FID) data to a denoised frequency spectrum that gives reliable chemical shifts and coupling constants when the spectrum is Lorentzian. It is formulated in a way that increases frequency sensitivity and resolution and, for nuclei of low natural abundance, potentially avoids enrichment totally or in part. The algorithm should also be of use in analytical chemistry where enrichment is not possible. In effect, the useful limit of detection is significantly lowered. The algorithm uses new "phasing" and "feature stability upon accumulation" methods to reliably separate signal from noise at low signal-to-noise ratios where the Fourier spectrum requires many more transients to be definitive as to what is signal and what is noise. The long-standing problem of "false features" that plagued many prior attempts to employ nonlinear methods is thereby resolved for Lorentzian spectra. Examples are reported, and the limitations of the algorithm are discussed.

Two-dimensional ECD FT-ICR mass spectrometry of peptides and glycopeptides

2D FT-ICR MS allows the correlation between precursor and fragment ions by modulating ion cyclotron radii for fragmentation modes with radius-dependent efficiency in the ICR cell without the need for prior ion isolation. This technique has been successfully applied to ion-molecule reactions, Collision-induced dissociation and infrared multiphoton dissociation. In this study, we used electron capture dissociation for 2D FT-ICR MS for the first time, and we recorded two-dimensional mass spectra of peptides and a mixture of glycopeptides that showed fragments that are characteristic of ECD for each of the precursor ions in the sample. We compare the sequence coverage obtained with 2D ECD FT-ICR MS with the sequence coverage obtained with ECD MS/MS and compare the sensitivities of both techniques. We demonstrate how 2D ECD FT-ICR MS can be implemented to identify peptides and glycopeptides for proteomics analysis.

Two-dimensional Fourier transform ion cyclotron resonance mass spectrometry: reduction of scintillation noise using Cadzow data processing

In two-dimensional Fourier transform ion cyclotron resonance mass spectrometry (2D FTICR-MS), scintillation noise, caused mostly by fluctuations in the number of ions in the ICR cell, is the leading cause for errors in spectrum interpretation. In this study, we adapted an algorithm based on singular value decomposition and first introduced by Cadzow et al. (IEE Proceedings Pt. F 1987, 134, 69) to 2D FTICR-MS and we measured its performance in terms of noise reduction without losing signal information in the 2D mass spectrum.

NMR signal enhancement via a new time-frequency transform

In this paper, a reliable method to reduce the noise from nuclear magnetic resonance (NMR) signals using a recently developed linear critically sampled time-frequency transform is proposed. In addition to its low computational requirements, this transform has many theoretical advantages that make it a good candidate for NMR signal enhancement. NMR signals in the transform domain are concentrated in a few coefficients while the noise is well distributed. Performing a thresholding technique in the transform domain, therefore, significantly enhances the signal. A comparison with other signal enhancement techniques shows that this technique has a superior performance, thus confirming the theoretical expectations.

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).

MR spectroscopy quantitation: a review of time-domain methods

In this article an overview of time-domain quantitation methods is given. Advantages of processing the data in the measurement domain are discussed. The basic underlying principles of the methods are outlined and from them the situations under which these algorithms perform well are derived. Also an overview of methods to preprocess the data is given. In that respect, signal-to-noise and/or resolution enhancement, the removal of unwanted components and corrections for model imperfections are discussed.

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.

NMRLAB-Advanced NMR data processing in matlab

NMRLAB is a toolbox for NMR data processing in MATLAB (The Mathworks). MATLAB is a matrix-oriented high-level programming environment which gives access to fast algorithms for a large number of numerical tasks on many common computer platforms. To take advantage of fast matrix operations in MATLAB most processing commands in NMRLAB have been vectorized. Data processing can be achieved either by scripts or by a user-friendly command structure. An interface to WaveLab enables spectral denoising employing wavelet transforms. The use of wavelet denoising is demonstrated for one- and two-dimensional data. Copyright 2000 Academic Press.

A new method for absolute quantitation of MRS metabolites

A new method for absolute quantitation of MRS spectra is presented. This method is not based on a reference peak, derived from a real NMR signal, but rather on a synthesized NMR reference produced by an electronic device, transmitted by a broad-band antenna to avoid quality factor variations. This signal is therefore received at the same time as the sample signal. The reference line produced is stable in time (maximum variation lower than 2%) and allows precise and accurate measurement of absolute concentrations (mean error lower than 3%) in vitro and in vivo.

Quantitation of resonances in biological 31P NMR spectra via principal component analysis: potential and limitations

This paper examines the potential and limitations of peak area quantitation of biological NMR spectra using principal component analysis (PCA), including its requirement for prior knowledge. The principles of the method are presented without in-depth mathematical treatment. PCA is illustrated for simulated data, 31P NMR spectra obtained consecutively over 1-2.5 days from perfused Rat-2 cells metabolizing the choline analogue phosphoniumcholine (Chop) and in vivo proton-decoupled, NOE-enhanced, three-dimensional CSI localized 31P NMR spectra of the liver of healthy volunteers. The results show that PCA can be used to quantitate strongly overlapping peaks without prior knowledge of the peak shapes or positions and to reconstruct spectra with significantly reduced noise variance. Two major limitations of PCA are presented: (1) PCA cannot separate peaks whose intensities are well correlated; (2) PCA is sensitive to differences in chemical shift and line-width of peaks between spectra. The discussion focuses on what knowledge of the biological and spectroscopic features of the samples and the principles of PCA is necessary for peak area quantitation via PCA.

Time and frequency domain analysis of NMR data compared: an application to 1D 1H spectra of lipoproteins

A comparison between a time domain analysis algorithm (VARPRO) and a frequency domain analysis algorithm (FITPLAC) for parameter estimation of magnetic resonance spectroscopy (MRS) data series is presented. VARPRO analyses the measured MRS signal (free induction decay; FID); FITPLAC analyses the discrete Fourier transform of the FID, the frequency domain magnetic resonance spectrum. A rapid time domain method, used to subtract the dominating water resonance from a 1H MRS FID, without affecting the metabolites of interest, is outlined and applied. Also a new "pseudofrequency selective" approach to time domain fitting is introduced. The possibilities of combining the most favorable features of time and frequency domain processing into one single MRS signal processing method are assessed. The 1H MRS signals of ultracentrifuged very low (VLDL), intermediate (IDL), and high (HDL) density lipoprotein fractions from human blood plasma were used for the comparisons. The results from both algorithms were in good agreement.

Simultaneous 31P NMR spectroscopy and EMG in exercising and recovering human skeletal muscle: technical aspects

The bioenergetics of human skeletal muscle can be studied by 31P NMR spectroscopy (31P-MRS) and by surface electromyography (SEMG). Simultaneous 31P-MRS and SEMG permit accurate and noninvasive studies of the correlation between metabolic and electrical changes in exercising and recovering human skeletal muscle, a relationship that is still poorly understood. This study describes the optimization of skeletal muscle 31P-MRS in a whole-body magnet, involving surface coil design, utilization of adiabatic radio frequency pulses and advanced time-domain fitting, to the technical design of SEMG. A nonmagnetic ergometer was used for ankle dorsiflexions that activated only the anterior tibial muscle as verified by post exercise imaging. The coil design and the adiabatic sech/tanh pulse improved sensitivity by 45% and 56% respectively, compared with standard techniques. Simultaneous electromyographic recordings did not deteriorate the NMR spectra. The VARPRO time domain fitting routine was very suitable for estimating 31P muscle spectra. With these methods it was possible to accurately estimate parameters describing metabolic and electrical changes during rest, exercise and the entire recovery period with a 20-s time resolution on a standard 1.5 T whole-body NMR scanner.

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.