Optimization Of Residual Water Signal Removal By HLSVD On Simulated Short Echo Time Proton MR Spectra Of The Human Brain.
E. Cabanes, S. Confort-Gouny, Y. Le Fur, G. Simond, P. Cozzone
Published 2001 · Medicine, Chemistry
Twitter
Facebook
LinkedIn
Email Suppression of the residual water signal from proton magnetic resonance (MR) spectra recorded in human brain is a prerequisite to an accurate quantification of cerebral metabolites. Several postacquisition methods of residual water signal suppression have been reported but none of them provide a complete elimination of the residual water signal, thereby preventing reliable quantification of brain metabolites. In the present study, the elimination of the residual water signal by the Hankel Lanczos singular value decomposition method has been evaluated and optimized to provide fast automated processing of spectra. Model free induction decays, reproducing the proton signal acquired in human brain localized MR spectroscopy at short echo times (e.g., 20 ms), have been generated. The optimal parameters in terms of number of components and dimension of the Hankel data matrix allowing complete elimination of the residual water signal are reported.
This paper references
10.1016/0022-2364(89)90126-1
Postacquisition data processing method for suppression of the solvent signal
Y. Kuroda (1989)
10.1002/mrm.1910290416
Double inversion recovery improves water suppression in vivo.
J. F. Shen (1993)
10.1007/978-3-642-45697-8_7
Analysis of NMR Data Using Time Domain Fitting Procedures
R. D. Beer (1992)
10.1016/0022-2364(90)90128-V
Signal suppression in the frequency domain to remove undesirable resonances with dispersive lineshapes
P. Tsang (1990)
10.1006/JMRE.1999.1782
Accurate quantification of (1)H spectra: from finite impulse response filter design for solvent suppression to parameter estimation.
T. Sundin (1999)
10.1016/0022-2364(92)90241-X
SVD-based quantification of magnetic resonance signals
W. W. Pijnappel (1992)
10.1006/jmrb.1994.1008
Distortion-Free Suppression of the Residual Water Peak in Proton Spectra by Postprocessing
J.H.J. Leclerc (1994)
10.1006/jmra.1994.1209
Algorithm for time-domain nmr data fitting based on total least-squares
S. Vanhuffel (1994)
10.1006/JMRE.1999.1792
Cross-correlated quadrupolar spin relaxation and carbon-13 lineshapes in the (13)CD(2) spin grouping.
L. Werbelow (1999)
10.1109/ICASSP.1987.1169515
The statistical performance of state-variable balancing and Prony's method in parameter estimation
A. Kot (1987)
10.1006/JMRE.1999.2011
Water peak suppression: time-frequency vs time-scale approach.
J. P. Antoine (2000)
10.1002/mrm.1910090110
Localized high-resolution proton NMR spectroscopy using stimulated echoes: initial applications to human brain in vivo.
J. Frahm (1989)
10.1002/mrm.1910310402
Time and frequency domain analysis of NMR data compared: an application to 1D 1H spectra of lipoproteins.
A. van den Boogaart (1994)
10.1097/00004728-199509000-00030
A Knowledge‐Based Approach to Deconvolve the Water Component in In Vivo Proton MR Spectroscopy
N. Saeed (1995)
10.1109/18.119728
Asymptotic wavelet and Gabor analysis: Extraction of instantaneous frequencies
N. Delprat (1992)
10.1006/jmra.1993.1037
Elimination of Water Signal by Postprocessing
Mohamed Deriche (1993)
10.1016/0022-2364(89)90391-0
Improved solvent suppression in one- and two-dimensional NMR spectra by convolution of time-domain data
D. Marion (1989)
10.1002/NBM.1940080207
In vivo 31P MRS: absolute concentrations, signal-to-noise and prior knowledge.
A. van den Boogaart (1995)
10.1006/JMRE.1999.1960
Frequency-selective quantification of biomedical magnetic resonance spectroscopy data.
L. Vanhamme (2000)
10.1006/jmra.1993.1035
Improved Digital Filtering Technique for Solvent Suppression
K. Cross (1993)
10.1006/JMRB.1995.1030
Improved water suppression for localized in vivo 1H spectroscopy.
T. Ernst (1995)
This paper is referenced by
10.1002/NBM.891
Issues of spectral quality in clinical 1H-magnetic resonance spectroscopy and a gallery of artifacts.
R. Kreis (2004)
10.1002/mrm.26536
Dual‐volume excitation and parallel reconstruction for J‐difference‐edited MR spectroscopy
G. Oeltzschner (2017)
Low myo-inositol and high glutamine levels in the brain are associated with neuropsychological deterioration following induced hyperammonemia
D. Shawcross (2004)
10.1002/nbm.3890
Maximizing sensitivity for fast GABA edited spectroscopy in the visual cortex at 7 T
Arjan D Hendriks (2018)
10.1002/mrm.28164
Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy.
Hyo-Chul Lee (2020)
10.1109/ISBI.2011.5872725
Sensitivity of biomarkers to post-acquisitional processing parameters for in vivo brain MR spectroscopy signals
Daniel Cocuzzo (2011)
10.1016/S0065-3276(06)51005-6
Fast Padé Transform for Exact Quantification of Time Signals in Magnetic Resonance Spectroscopy
D. Belkic (2006)
10.1038/s41598-019-38981-1
Dynamic Imaging of Glucose and Lactate Metabolism by 13C-MRS without Hyperpolarization
J. Brender (2019)
10.1109/TBME.2011.2161609
Implementation of an Absolute Brain $^{1}$H-MRS Quantification Method to Assess Different Tissue Alterations in Multiple Sclerosis
M. Bagory (2012)
10.1002/nbm.3686
Neurometabolic profiles of the substantia nigra and striatum of MPTP-intoxicated common marmosets: An in vivo proton MRS study at 9.4 T.
Hwon Heo (2017)
10.1038/s41467-019-08313-y
Learning to optimize perceptual decisions through suppressive interactions in the human brain
P. Frangou (2019)
10.1109/ICBBE.2011.5780700
A Post-Processing Approach of HLSVD Used for Automatic Quantitative Analysis of Multi-Voxel Magnetic Resonance Spectra
Ping Chi (2011)
10.1088/0031-9155/51/10/018
Exact quantification of time signals in Padé-based magnetic resonance spectroscopy.
D. Belkic (2006)
10.1002/nbm.3115
In vivo T(2) relaxation time measurement with echo-time averaging.
A. Prescot (2014)
10.1016/j.neuroimage.2005.03.023
1H-MRS imaging in intractable frontal lobe epilepsies characterized by depth electrode recording
M. Guye (2005)
10.1109/TBME.2018.2850911
Tensor-Based Method for Residual Water Suppression in $^1$H Magnetic Resonance Spectroscopic Imaging
Bharath Halandur Nagaraja (2019)
QUANTIFICATION AND CLASSIFICATION OF MAGNETIC RESONANCE SPECTROSCOPIC DATA FOR BRAIN TUMOR DIAGNOSIS
Faculteit Ingenieurswetenschappen (2008)
10.1016/j.ejrad.2008.03.005
Introduction to post-processing techniques.
F. Jiru (2008)
10.1002/mrm.26778
Simultaneous mapping of metabolites and individual macromolecular components via ultra‐short acquisition delay 1H MRSI in the brain at 7T
M. Považan (2018)
10.1152/AJPGI.00104.2004
Low myo-inositol and high glutamine levels in brain are associated with neuropsychological deterioration after induced hyperammonemia.
D. Shawcross (2004)
10.1002/mrm.26502
Parameterization of spectral baseline directly from short echo time full spectra in 1H‐MRS
Hyeong Hun Lee (2017)
10.1002/nbm.3714
Non‐water‐suppressed short‐echo‐time magnetic resonance spectroscopic imaging using a concentric ring k‐space trajectory
Uzay E. Emir (2017)
10.1002/mrm.22084
High dynamic-range magnetic resonance spectroscopy (MRS) time-domain signal analysis.
William C. Hutton (2009)
10.1371/journal.pone.0056501
Morphological and Metabolic Changes in the Nigro-Striatal Pathway of Synthetic Proteasome Inhibitor (PSI)-Treated Rats: A MRI and MRS Study
Stefano Delli Pizzi (2013)
10.1002/mrm.25380
Semi-LASER 1 H MR spectroscopy at 7 Tesla in human brain: Metabolite quantification incorporating subject-specific macromolecule removal.
J. Penner (2015)
10.4995/THESIS/10251/17195
Incremental Learning approaches to Biomedical decision problems
Salvador Tortajada Velert (2012)
10.1113/JP276626
The dynamics of cortical GABA in human motor learning
J. Kolasinski (2019)
Title Density-weighted concentric rings k-space trajectory for 1 H magnetic resonance spectroscopic imaging at 7
Mark Chiew (2017)
10.1016/S0730-725X(03)00179-6
Molality as a unit of measure for expressing 1H MRS brain metabolite concentrations in vivo.
J. Knight‐Scott (2003)
10.1016/S0065-3276(08)00403-6
Chapter 3 Exact Signal–Noise Separation by Froissart Doublets in Fast Padé Transform for Magnetic Resonance Spectroscopy
Dž (2009)
10.1002/mrm.27049
Non‐water‐suppressed 1H FID‐MRSI at 3T and 9.4T
Paul Chang (2018)
10.3389/fnins.2019.01158
Dynamic Metabolic Changes in the Human Thalamus at the Transition From Waking to Sleep - Insights From Simultaneous Functional MR Spectroscopy and Polysomnography
Mick Lehmann (2019)
See more
Some data provided by SemanticScholar