TRADITIONAL POSTER - ismrm

Poster Sessions
902. Regularized Spectral Lineshape Deconvolution
Yan Zhang 1 , Shizhe Li 1 , Jun Shen 1
1 National Institute of Mental Health, Bethesda, MD, United States
The process of lineshape deconvolution is an inverse problem. A new referencing deconvolution method is proposed, which uses Tiknohov regularization to
restrain the noise amplification. To determine the optimal regularization, the noise to signal ratio in frequency domain was defined as a function of the
regularization parameter. It was found that this function yielded a well-defined L-curve with the transition point that marks the optimal regularization
parameter. The method was validated on 1H spectral data which were acquired on human brain with single voxel at 3T. The spectral quality was markedly
improved after the data were processed with the proposed method.
903. Electronic Reference for Absolute Quantification of Brain Metabolites by 1H-MRS on Clinical Whole
Body Imager.
Hubert Desal 1 , Nashiely Pineda Alonso 2 , Serge Akoka 2
1 Neuroradiology, CHU de Nantes, Nantes, PdL, France; 2 Chemistry, Université de Nantes, CEISAM, UMR 6230, Nantes, PdL,
France
The ERETIC method is a promising avenue of research for absolute concentration quantification by MRS. However, in its initial form, this technique cannot
be implemented on most clinical MR scanners. We propose a new strategy, which consists in transmitting the ERETIC signal before the localized
spectroscopy acquisition. This approach was evaluated on phantoms and on volunteers. The results were compared to those obtained using the water signal
as reference. A very good correlation between the values obtained using the two methods was observed. Moreover, the ERETIC method overcomes many of
the drawbacks of the other absolute quantification methods.
904. Sampling Strategy Effects on in Vivo 2D J-Resolved Spectroscopy Quantification
Tangi Roussel 1 , Sophie Cavassila 1 , Hélène Ratiney 1
1 CREATIS, CNRS UMR 5220, Inserm U630, INSA-Lyon, Université de Lyon 1, Université de Lyon, Villeurbanne, France
Till now, in vivo two-dimensional spectroscopy related studies did not investigate sampling strategies of the indirect dimension as a way of improving the
quantification of metabolite concentrations. This paper presents a study carried out on simulated J-PRESS data containing macromolecular contamination.
2D J-Resolved spectroscopy quantification accuracy was evaluated for several sampling strategies and compared to 1D MRS quantification accuracy. In
vivo 2D quantification following these strategies is shown. By handling macromolecular contribution by truncation strategy, a 2D MRS experiment leads to
a more accurate quantification compared to 1D MRS time equivalent experiment, as demonstrated by a reduction of bias and standard deviation.
905. In Vitro and in Vivo Validation of Absolute Quantitation of Brain Proton MR Spectra ( 1 H-MRS) with
Respect to Heterogeneous Tissue Compositions
Alexander Gussew 1 , Marko Erdtel 1,2 , Reinhard Rzanny 1 , Juergen R. Reichenbach 1
1 Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany;
2 University of Applied Sciences Jena, Jena, Germany
This work describes in vitro and in vivo validation of absolute quantitation of 1 H-MRS brain data with respect to heterogeneous tissue distributions within
the MRS-volume. NAA concentrations were estimated from metabolite and water spectra obtained from MRS-voxels containing different metabolite and
water concentrations and were compared with nominally adjusted values. The maximal error was 4% compared to 41%, if the tissue heterogeneity was
neglected. Inter-individual distributions of NAA-, Cr- and tCho-concentrations obtained in insular cortex of volunteers had twice less scatter when taking
into account the heterogeneous tissue composition in the voxel.
906. Spectral Fitting of High Resolution Rat Brain Extract NMR Data by LCModel with a Simulated Basis
Set
Andrew Borgert 1,2 , Kelvin O. Lim 1,2 , Pierre-Gilles Henry 1,3
1 Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; 2 Department of Psychiatry,
University of Minnesota, Minneapolis, MN, United States; 3 Department of Radiology, University of Minnesota, Minneapolis, MN,
United States
Spectral fitting methods such as commercial metabolomics software (eg, Chenomx) or capabilities built into NMR system software (eg, Varian or Bruker)
require significant user input and are generally not amenable to automation, making them time-consuming, cumbersome, and prone to user error. To address
these issues, we have adapted the LCModel software package for use with high resolution in vitro NMR data, allowing for automated and consistent analysis
of such data. This adaptation utilizes a simulated basis set, with basis spectra generated for the majority of individual protons within each metabolite, as
opposed to the metabolite as a whole.
907. Simulating Human Brain Glutamate FMRS at 7.0 T to Determine Minimum SNR Requirements
Reggie Taylor 1,2 , Jean Théberge 1,2 , Peter Williamson, 1,3
1 Medical Biophysics, University of Western Ontario, London, ON, Canada; 2 Lawson Health Research Institute, London, ON, Canada;
3 Department of Psychiatry, University of Western Ontario, London, ON, Canada
Human brain glutamate fMRS has the potential to provide dynamic information regarding normal and abnormal glutamate metabolism. With ultra-high field
magnets (≤7T) increased spectral dispersion and SNR should result in more precise fMRS but how much SNR is required is not known. Using simulations of
an in vivo spectrum acquired with a STEAM sequence (TE/TM 6/32ms) at 7T minimum numbers of spectra required to detect a 3% concentration change in
glutamate between rest and activation were determined for various SNRs. A minimum SNR of 212 was needed to detect the 3% change when comparing
only one spectrum from each state.