Abstract #4258

Harnessing sparsity: Feasibility of undersampled fixed evolution time ²³Na TQTPPI FID reconstruction for optimal ²³Na TQ/SQ-signal estimation

Dominik Zehender^1,2,3, Simon Reichert^1,2,3, Frank G. Zöllner^1,2,3, and Lothar R. Schad^1,2

¹Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany, ²Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, ³Cooperative Core Facility Animal Scanner ZI, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany

Synopsis

Keywords: Sparse & Low-Rank Models, Spectroscopy, Sodium

Motivation: The ²³Na TQ-signal is a potential biomarker for cell viability but the required phase-cycling leads to long scan times with redundant information.

Goal(s): To investigate the feasibility of undersampling the fixed TQTPPI FID in the second dimension and reconstructing it by either an undersampled fit or two iterative thresholding algorithms.

Approach: Investigation of the feasibility of undersampling the fixed TQTPPI FID in the second dimension and reconstructing it by either an undersampled fit or two iterative thresholding algorithms.

Results: Undersampled fit successfully reconstructed data up to a 14 undersampling factor, while accuracy of the CS algorithms declined post-Nyquist-limit in both measurement and simulation.

Impact: While undersampled fit was as accurate as CS algorithms in simulations and below the Nyquist-limit it showed more reliable results and outperformed the latter two on measurement data and post-Nyquist limit, suggesting that physics informed reconstruction is advantageous.

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