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Abstract #2292

Enhanced Phase Regression with Savitzky-Golay Filtering for High-Resolution BOLD FMRI

Robert L. Barry1, 2, John C. Gore, 23

1Vanderbilt University Institute of Imaging Science, Nashville, TN, United States; 2Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States; 3Vanderbilt University, Nashville, TN, United States

Phase regression exploits the temporal evolution of phase in individual voxels to suppress BOLD fluctuations from larger vessels while preserving signal changes from microvascular effects. However, the efficacy of this algorithm is hindered when the phase time series exhibits low signal-to-noise ratio. We demonstrate that Savitzky-Golay filters may be used to recover the underlying change in phase and completely restore the efficacy of phase regression. This approach is shown to work on data acquired with single-shot and multi-shot pulse sequences, and should be useful for both human and animal gradient-echo fMRI at high spatial resolutions at high- and ultra-high fields.