Susan M Noworolski1, Galen D Reed, John Kurhanewicz, Daniel B Vigneron. 1. The Center for Molecular and Functional Imaging, Department of Radiology and Biomedical Imaging, The University of California, San Francisco, California 94107, USA. sue@radiology.ucsf.edu
Abstract
PURPOSE: To develop and validate a post-processing correction algorithm to remove the effect of the inhomogeneous reception profile of the endorectal coil on MR spectroscopic imaging (MRSI) data. MATERIALS AND METHODS: A post-processing algorithm to correct for the endorectal coil reception effects on MRSI data was developed based upon theoretical modeling of the endorectal coil reception profile and of the spatial saturation pulse profiles. This algorithm was evaluated on three-dimensional (3D) MRSI data acquired at 3T from a uniform phantom and from 18 patients with known or suspected prostate cancer. RESULTS: For the phantom data, the coefficient of variation of metabolite peak areas decreased 16% to 46% and the peak area distributions became more Gaussian with correction, as demonstrated by higher Q-Q plot linear correlations (R(2) = 0.98 +/- 0.007 vs. R(2) = 0.89 +/- 0.066). Across the 18 patients, the mean coefficient of variation for suppressed water decreased significantly, from 0.95 +/- 0.18, to 0.66 +/- 0.11, (P < 10(-6), paired t-test) and the linear correlations of the Q-Q plots for the suppressed water increased from R(2) = 0.91 to R(2) = 0.95 (P = 0.0083, paired t-test) with correction. CONCLUSION: An algorithm for reducing the effect of the inhomogeneous reception profile in endorectal coil acquired 3D MRSI prostate data was demonstrated, illustrating increased homogeneity and more Gaussian peak area distributions.
PURPOSE: To develop and validate a post-processing correction algorithm to remove the effect of the inhomogeneous reception profile of the endorectal coil on MR spectroscopic imaging (MRSI) data. MATERIALS AND METHODS: A post-processing algorithm to correct for the endorectal coil reception effects on MRSI data was developed based upon theoretical modeling of the endorectal coil reception profile and of the spatial saturation pulse profiles. This algorithm was evaluated on three-dimensional (3D) MRSI data acquired at 3T from a uniform phantom and from 18 patients with known or suspected prostate cancer. RESULTS: For the phantom data, the coefficient of variation of metabolite peak areas decreased 16% to 46% and the peak area distributions became more Gaussian with correction, as demonstrated by higher Q-Q plot linear correlations (R(2) = 0.98 +/- 0.007 vs. R(2) = 0.89 +/- 0.066). Across the 18 patients, the mean coefficient of variation for suppressed water decreased significantly, from 0.95 +/- 0.18, to 0.66 +/- 0.11, (P < 10(-6), paired t-test) and the linear correlations of the Q-Q plots for the suppressed water increased from R(2) = 0.91 to R(2) = 0.95 (P = 0.0083, paired t-test) with correction. CONCLUSION: An algorithm for reducing the effect of the inhomogeneous reception profile in endorectal coil acquired 3D MRSI prostate data was demonstrated, illustrating increased homogeneity and more Gaussian peak area distributions.
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