New approach for quantitation of short echo time in vivo 1H MR spectra of brain using AMARES

Short echo time in vivo STEAM 1H MR spectra (4.7 T, TE =16 ms) of normal rat brain were fitted in the time domain using a VARPRO‐like algorithm called AMARES which allows an inclusion of a large amount of prior knowledge. The prior knowledge was derived from phantom spectra of pure metabolite solutions measured under the same experimental conditions as the in vivo spectra. The prior knowledge for the in vivo spectra was constructed as follows: for each VARPRO‐fitted phantom spectrum one peak (the most prominent one in the in vivo spectrum) was chosen and left unconstrained in the AMARES fitting while all the other peaks in the metabolite spectrum (i.e. their corresponding parameters—amplitudes, damping factors, frequencies and phases) were fixed to the parameter values of the unconstrained peak via amplitude and damping ratios and frequency and phase shifts. Including N ‐acetyl‐aspartate, glutamate, total creatine, cholines, glucose and myo ‐inositol into the fits provided results which were in agreement with published data. An inclusion of glutamine into the set of fitted metabolites was also investigated. © 1998 John Wiley & Sons, Ltd.

[1]  Vanhamme,et al.  Improved method for accurate and efficient quantification of MRS data with use of prior knowledge , 1997, Journal of magnetic resonance.

[2]  M. Weiner,et al.  Metabolite 1H relaxation in normal and hyponatremic brain , 1996, Magnetic resonance in medicine.

[3]  P. Williamson,et al.  The use of a priori knowledge to quantify short echo in vivo 1h mr spectra , 1995, Magnetic resonance in medicine.

[4]  M. McLean,et al.  Continuing ischemic damage after acute middle cerebral artery infarction in humans demonstrated by short-echo proton spectroscopy. , 1995, Stroke.

[5]  A. van den Boogaart,et al.  Time and frequency domain analysis of NMR data compared: An application to 1D 1H spectra of lipoproteins , 1994, Magnetic resonance in medicine.

[6]  S. Provencher Estimation of metabolite concentrations from localized in vivo proton NMR spectra , 1993, Magnetic resonance in medicine.

[7]  J. Frahm,et al.  Localized proton NMR spectroscopy of experimental gliomas in rat brain In Vivo , 1992, NMR in biomedicine.

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

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

[10]  J. Ellermann,et al.  Non‐invasive 1H NMR spectroscopy of the rat brain In Vivo using a short echo time STEAM localization sequence , 1991, NMR in biomedicine.

[11]  J. Frahm,et al.  Cerebral glucose is detectable by localized proton NMR spectroscopy in normal rat brain in Vivo , 1991, Magnetic resonance in medicine.

[12]  W M Bovée,et al.  Improved quantification of in vivo1H NMR spectra by optimization of signal acquisition and processing and by incorporation of prior knowledge into the spectral fitting , 1990, Magnetic resonance in medicine.

[13]  U. Klose In vivo proton spectroscopy in presence of eddy currents , 1990, Magnetic resonance in medicine.

[14]  William H. Oldendorf,et al.  N-Acetyl-L-Aspartic acid: A literature review of a compound prominent in 1H-NMR spectroscopic studies of brain , 1989, Neuroscience & Biobehavioral Reviews.

[15]  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.

[16]  John E. Dennis,et al.  Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4] , 1981, TOMS.

[17]  Sabine Van Huffel,et al.  Improved Fitting Method for Parameter Estimation of MRS Signals with Prior Knowledge , 1997 .

[18]  E. Cady Quantification of metabolites in human brain by proton magnetic resonance spectroscopy: Methodologies, limitations, and achievements. , 1996 .