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Abstract #4714

CASSAVA: a Compressed Adaptive SenSing Algorithm with Variable k‑space Averaging for high‑resolution volumetric 31P MRSI at 7T

Gino G. Rincon1,2, Philip S. Boyd1, Vanessa L. Franke1,2, Cornelius J. Bauer1,2, Mark E. Ladd1,2,3, Peter Bachert1,2, and Andreas Korzowski1
1Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany, 3Faculty of Medicine, University of Heidelberg, Heidelberg, Germany

Synopsis

Keywords: Non-Proton, Spectroscopy, Phosphorous MRSICompressed sensing (CS) techniques suggest the feasibility of reducing the measurement duration of highresolution 31PMRSI at 7T to a clinically reasonable time (20 minutes) while preserving data quality. The proposed Compressed Adaptive SenSing Algorithm with Variable kspace Averaging (CASSAVA) reconstructs 31PMRSI data with an undersampling factor of $$$R=3.8$$$ while simultaneously maintaining spectral peak accuracy and a high spatial resolution. This was demonstrated in the conducted simulation, retrospective, and prospective studies by evaluating the reconstructed spectra and intracellular pH maps of healthy and tumor tissues as a benchmark test. As a result, clinical research on larger patient cohorts becomes feasible.

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Keywords