Frequency-selective quantitation of short-echo time 1H magnetic resonance spectra.

Accurate and efficient filtering techniques are required to suppress large nuisance components present in short-echo time magnetic resonance (MR) spectra. This paper discusses two powerful filtering techniques used in long-echo time MR spectral quantitation, the maximum-phase FIR filter (MP-FIR) and the Hankel-Lanczos Singular Value Decomposition with Partial ReOrthogonalization (HLSVD-PRO), and shows that they can be applied to their more complex short-echo time spectral counterparts. Both filters are validated and compared through extensive simulations. Their properties are discussed. In particular, the capability of MP-FIR for dealing with macromolecular components is emphasized. Although this property does not make a large difference for long-echo time MR spectra, it can be important when quantifying short-echo time spectra.

[1]  Pietro Luigi Indovina,et al.  A new time-domain frequency-selective quantification algorithm. , 2002, Journal of magnetic resonance.

[2]  Jouni Kaartinen,et al.  Quantification of human brain metabolites from in vivo 1H NMR magnitude spectra using automated artificial neural network analysis. , 2002, Journal of magnetic resonance.

[3]  J. Suykens,et al.  Classification of brain tumours using short echo time 1H MR spectra. , 2004, Journal of magnetic resonance.

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

[5]  S Van Huffel,et al.  Accurate quantification of (1)H spectra: from finite impulse response filter design for solvent suppression to parameter estimation. , 1999, Journal of magnetic resonance.

[6]  C Chauvin,et al.  Wavelets and related time‐frequency techniques in magnetic resonance spectroscopy , 2001, NMR in biomedicine.

[7]  Keith J. Cross.  Improved Digital Filtering Technique for Solvent Suppression , 1993 .

[8]  D. Calvetti,et al.  AN IMPLICITLY RESTARTED LANCZOS METHOD FOR LARGE SYMMETRIC EIGENVALUE PROBLEMS , 1994 .

[9]  B J Soher,et al.  Representation of strong baseline contributions in 1H MR spectra , 2001, Magnetic resonance in medicine.

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

[11]  M. Sdika,et al.  Time‐domain semi‐parametric estimation based on a metabolite basis set , 2005, NMR in biomedicine.

[12]  Paul A Bottomley,et al.  Quantifying in vivo MR spectra with circles. , 2006, Journal of magnetic resonance.

[13]  M. Delepierre,et al.  Binomial frequency response to non-binomial pulse sequences for efficient water suppression , 1993, Journal of biomolecular NMR.

[14]  B J Soher,et al.  Automated spectral analysis II: Application of wavelet shrinkage for characterization of non‐parameterized signals , 1998, Magnetic resonance in medicine.

[15]  C. Elster,et al.  Quantitative magnetic resonance spectroscopy: Semi‐parametric modeling and determination of uncertainties , 2005, Magnetic resonance in medicine.

[16]  Petre Stoica,et al.  Frequency-domain method based on the singular value decomposition for frequency-selective NMR spectroscopy. , 2003, Journal of magnetic resonance.

[17]  C. Sidney Burrus,et al.  Constrained least square design of FIR filters without specified transition bands , 1996, IEEE Trans. Signal Process..

[18]  Wolfgang Grodd,et al.  Parameterized evaluation of macromolecules and lipids in proton MR spectroscopy of brain diseases , 2003, Magnetic resonance in medicine.

[19]  R S Menon,et al.  Spectroscopic lineshape correction by QUECC: Combined QUALITY deconvolution and eddy current correction , 2000, Magnetic resonance in medicine.

[20]  S. Confort-Gouny,et al.  Optimization of residual water signal removal by HLSVD on simulated short echo time proton MR spectra of the human brain. , 2001, Journal of magnetic resonance.

[21]  V. Govindaraju,et al.  Proton NMR chemical shifts and coupling constants for brain metabolites , 2000, NMR in biomedicine.

[22]  Sabine Van Huffel,et al.  Bandpass prefiltering for exponential data fitting with known frequency region of interest , 1996, Signal Process..

[23]  J. Antoine,et al.  Water peak suppression: time-frequency vs time-scale approach. , 2000, Journal of magnetic resonance.

[24]  Heinz Rüterjans,et al.  WAVEWAT-improved solvent suppression in NMR spectra employing wavelet transforms. , 2002, Journal of magnetic resonance.

[25]  S Van Huffel,et al.  Improved Lanczos algorithms for blackbox MRS data quantitation. , 2002, Journal of magnetic resonance.

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

[27]  S Mierisová,et al.  MR spectroscopy quantitation: a review of frequency domain methods , 2001, NMR in biomedicine.

[28]  C Boesch,et al.  Characterization of the macromolecule baseline in localized 1H‐MR spectra of human brain , 2001, Magnetic resonance in medicine.

[29]  S. Huffel,et al.  MR spectroscopy quantitation: a review of time‐domain methods , 2001, NMR in biomedicine.

[30]  Sabine Van Huffel,et al.  An automated quantitation of short echo time MRS spectra in an open source software environment: AQSES , 2007, NMR in biomedicine.

[31]  A. J. Shaka,et al.  Application of the filter diagonalization method to one- and two-dimensional NMR spectra , 1998, Journal of magnetic resonance (San Diego, Calif. 1997 : Print).

[32]  Ad Bax,et al.  Improved solvent suppression in one-and two-dimensional NMR spectra by convolution of time-domain data , 1989 .

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

[34]  D. Graveron-Demilly,et al.  Time-domain quantitation of 1H short echo-time signals: background accommodation , 2004, Magnetic Resonance Materials in Physics, Biology and Medicine.

[35]  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.

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