Dynamic 2D fitting of 3D deuterium metabolic imaging data acquired in human brain at 7T

Motivation: Dynamic deuterium metabolic imaging (DMI) data are currently evaluated by first fitting the spectral and then the temporal domain (1D), leading to great fit uncertainty. This might be improved by fitting both domains simultaneously (2D). Goal(s): To compare dynamic 2D-fitting of time-resolved 3D-DMI data of the human brain and compare its performance to conventional 1D-fitting. Approach: Simulated and in vivo DMI data were fitted using 1D- and 2D-fitting algorithms and results were compared in terms of precision and accuracy. Results: 2D-fitting yielded higher precision and accuracy than 1D-fitting for simulated DMI data. For in vivo data, both fitting approaches yielded similar results. Impact: Improving fitting accuracy to estimate the underlying metabolic kinetics from dynamic deuterium metabolic imaging (DMI) data is crucial, while establishing DMI towards clinical application. 2D-fitting approaches (simultaneous spectral and temporal fitting) could potentially improve overall robustness of the methodology.