Improved volume selective (1) H MR spectroscopic imaging of the prostate with gradient offset independent adiabaticity pulses at 3 tesla
Volume selection in (1) H MR spectroscopic imaging (MRSI) of the prostate is commonly performed with low-bandwidth refocusing pulses. However, their large chemical shift displacement error (CSDE) causes lipid signal contamination in the spectral range of interest. Application of high-bandwidth adiab...
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Published in: | Magnetic resonance in medicine Vol. 74; no. 4; pp. 915 - 924 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
01-10-2015
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Subjects: | |
Online Access: | Get full text |
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Summary: | Volume selection in (1) H MR spectroscopic imaging (MRSI) of the prostate is commonly performed with low-bandwidth refocusing pulses. However, their large chemical shift displacement error (CSDE) causes lipid signal contamination in the spectral range of interest. Application of high-bandwidth adiabatic pulses is limited by radiofrequency (RF) power deposition. In this study, we aimed to provide an MRSI sequence that overcomes these limitations.
Measurements were performed at 3 T with an endorectal receive coil. A semi-LASER sequence was equipped with low RF power demanding gradient-modulated offset-independent adiabaticity (GOIA) refocusing pulses with WURST(16,4) modulation, with a 10 kHz bandwidth.
Simulations and phantom studies verified that the GOIA pulses select slices with a flat top and sharp edges and minimal CSDE. The sequence timing was tuned to an optimal citrate signal shape at an echo time of 88 ms. Patient studies (n = 10) demonstrated that high quality spectra with reduced lipid artifacts can be obtained from the whole prostate. Compared with PRESS acquisition at 145 ms the signal-to-noise ratio (SNR) of citrate is increased up to 2.6 and choline up to 1.3.
An MRSI sequence of the prostate is presented with minimized spectral lipid contamination and improved SNR, to facilitate routine clinical acquisition of metabolic data. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1522-2594 |
DOI: | 10.1002/mrm.25476 |