Automated adaptive preconditioner for quantitative susceptibility mapping.

PURPOSE: To develop an automated adaptive preconditioner for QSM reconstruction with improved susceptibility quantification accuracy and increased image quality.

THEORY AND METHODS: The total field was used to rapidly produce an approximate susceptibility map, which was then averaged and trended over binning to generate a spatially varying distribution of preconditioning values. This automated adaptive preconditioner was used to reconstruct QSM via total field inversion and was compared with its empirical counterparts in a numerical simulation, a brain experiment with 5 healthy subjects and 5 patients with intracerebral hemorrhage, and a cardiac experiment with 3 healthy subjects.

RESULTS: Among evaluated preconditioners, the automated adaptive preconditioner achieved the fastest convergence in reducing the RMSE of the QSM in the simulation, suppressed hemorrhage-associated artifacts while preserving surrounding brain tissue contrasts, and provided cardiac chamber oxygenation values consistent with those reported in the literature.

CONCLUSION: An automated adaptive preconditioner allows high-quality QSM from the total field in imaging various anatomies with dynamic susceptibility ranges.