Automated adaptive preconditioner for quantitative susceptibility mapping. Issue 1 (11th August 2019) - Liu, Zhe; Wen, Yan; Spincemaille, Pascal; Zhang, Shun; Yao, Yihao; Nguyen, Thanh D.; Wang, Yi
Abstract : 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 R 2 ∗ 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.