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

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.