Abstract
Purpose: To develop a fully automated algorithm for combining multivoxel magnetic resonance spectroscopy (MRS) data acquired with a phased-array coil. Materials and Methods: The frequency-domain fitting method of LCModel (Provencher SW, Magn Reson Med 1993;30:672-679) was utilized to analyze the individual data sets. The phase corrections and the metabolite areas were then extracted from the LCModel output files for each individual spectrum. These areas were used to determine the dominant metabolite for each spatial location and to combine the individual spectra in a weighted manner. Results: The combination of MRS data acquired from a phantom and the brains of normal volunteers with a four array coil yielded improved signal-to-noise ratio (SNR) in all voxels. The average improvement in SNR of the combined spectrum, as compared with the best of the individual spectra at each spatial location, was 1.4. In the phantom, the predicted SNR improvement of two-fold was achieved at the center of the sample. In the brain, the maximum improvement was 1.8, due to sampling of the ventricles in the center of the sample. Conclusion: The method described in this report provides a means for employing phased-array coils in MRS with the same advantages as those found in MRI.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 317-322 |
| Number of pages | 6 |
| Journal | Journal of Magnetic Resonance Imaging |
| Volume | 21 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2005 |
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Keywords
- Automation
- CSI
- LCModel
- Phased array coil
- Weighted combination
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Radiological and Ultrasound Technology
Cite this
An automated algorithm for combining multivoxel MRS data acquired with phased-array coils. / Maril, Nimrod; Lenkinski, Robert E.
In: Journal of Magnetic Resonance Imaging, Vol. 21, No. 3, 03.2005, p. 317-322.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An automated algorithm for combining multivoxel MRS data acquired with phased-array coils
AU - Maril, Nimrod
AU - Lenkinski, Robert E.
PY - 2005/3
Y1 - 2005/3
N2 - Purpose: To develop a fully automated algorithm for combining multivoxel magnetic resonance spectroscopy (MRS) data acquired with a phased-array coil. Materials and Methods: The frequency-domain fitting method of LCModel (Provencher SW, Magn Reson Med 1993;30:672-679) was utilized to analyze the individual data sets. The phase corrections and the metabolite areas were then extracted from the LCModel output files for each individual spectrum. These areas were used to determine the dominant metabolite for each spatial location and to combine the individual spectra in a weighted manner. Results: The combination of MRS data acquired from a phantom and the brains of normal volunteers with a four array coil yielded improved signal-to-noise ratio (SNR) in all voxels. The average improvement in SNR of the combined spectrum, as compared with the best of the individual spectra at each spatial location, was 1.4. In the phantom, the predicted SNR improvement of two-fold was achieved at the center of the sample. In the brain, the maximum improvement was 1.8, due to sampling of the ventricles in the center of the sample. Conclusion: The method described in this report provides a means for employing phased-array coils in MRS with the same advantages as those found in MRI.
AB - Purpose: To develop a fully automated algorithm for combining multivoxel magnetic resonance spectroscopy (MRS) data acquired with a phased-array coil. Materials and Methods: The frequency-domain fitting method of LCModel (Provencher SW, Magn Reson Med 1993;30:672-679) was utilized to analyze the individual data sets. The phase corrections and the metabolite areas were then extracted from the LCModel output files for each individual spectrum. These areas were used to determine the dominant metabolite for each spatial location and to combine the individual spectra in a weighted manner. Results: The combination of MRS data acquired from a phantom and the brains of normal volunteers with a four array coil yielded improved signal-to-noise ratio (SNR) in all voxels. The average improvement in SNR of the combined spectrum, as compared with the best of the individual spectra at each spatial location, was 1.4. In the phantom, the predicted SNR improvement of two-fold was achieved at the center of the sample. In the brain, the maximum improvement was 1.8, due to sampling of the ventricles in the center of the sample. Conclusion: The method described in this report provides a means for employing phased-array coils in MRS with the same advantages as those found in MRI.
KW - Automation
KW - CSI
KW - LCModel
KW - Phased array coil
KW - Weighted combination
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UR - http://www.scopus.com/inward/citedby.url?scp=14044249515&partnerID=8YFLogxK
U2 - 10.1002/jmri.20261
DO - 10.1002/jmri.20261
M3 - Article
C2 - 15723370
AN - SCOPUS:14044249515
VL - 21
SP - 317
EP - 322
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
SN - 1053-1807
IS - 3
ER -