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.

[1]  G. L. Bretthorst Bayesian analysis. V : Amplitude estimation for multiple well-separated sinusoids , 1992 .

[2]  R de Beer,et al.  Reduced lipid contamination in in vivo 1H MRSI using time-domain fitting and neural network classification. , 1993, Magnetic resonance imaging.

[3]  G C Levy,et al.  An evaluation of new processing protocols for in vivo NMR spectroscopy , 1991, Magnetic resonance in medicine.

[4]  P. Luyten,et al.  Accurate quantification of in vivo 31P NMR signals using the variable projection method and prior knowledge , 1988, Magnetic resonance in medicine.

[5]  D. van Ormondt,et al.  SVD-based quantification of magnetic resonance signals , 1992 .

[6]  D. van Ormondt,et al.  Improved algorithm for noniterative time-domain model fitting to exponentially damped magnetic resonance signals , 1987 .

[7]  D. van Ormondt,et al.  Error theory for time-domain signal analysis with linear prediction and singular value decomposition , 1986 .

[8]  D. van Ormondt,et al.  Frequency-selective quantification in the time domain , 1992 .

[9]  A. van den Bos Estimation of Fourier coefficients , 1989 .

[10]  André Briguet,et al.  Improvements of quantitation by using the Cadzow enhancement procedure prior to any linear-prediction methods , 1994 .

[11]  James A. Cadzow,et al.  Signal enhancement-a composite property mapping algorithm , 1988, IEEE Trans. Acoust. Speech Signal Process..

[12]  D. B. Preston Spectral Analysis and Time Series , 1983 .

[13]  Richard Kronland-Martinet,et al.  Asymptotic wavelet and Gabor analysis: Extraction of instantaneous frequencies , 1992, IEEE Trans. Inf. Theory.

[14]  M. Bos,et al.  The wavelet transform for pre-processing IR spectra in the identification of mono- and di-substituted benzenes , 1994 .