A Method to Identify and Correct for Blurring Artifacts in Hyperpolarized Metabolic Imaging
Stephen J. Kadlecek1, Mehrdad Pourfathi1,2, Harrilla Profka1, and Rahim R. Rizi1
1Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, United States
Hyperpolarized imaging sequences are subject to potential bias and spread of apparent signal to neighboring voxels due to the time-dependence of magnetization as RF pulses are applied and as polarization is lost through spin-lattice relaxation. In this abstract, we discuss a method to detect and correct for artifacts and demonstrate it using chemical shift imaging. The method utilizes periodic resampling of nonselective spectra to correct for signal dynamics. We show that this technique results in a higher fidelity, "de-blurred" image.
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