Background field removal for susceptibility mapping of human brain with large susceptibility variations

Purpose: In quantitative susceptibility mapping (QSM) of human brain, the background field induced by air-tissue interface varies significantly with respect to the rotation angle between the head and the static field, which may result in substantial error in the estimated magnetic susceptibility values. The goal of this study was to develop a strategy to better remove such orientation dependent background field. Methods: An improved background field removal method is proposed based on the sophisticated harmonic artifact reduction for phase data using a region adaptive kernel (R-SHARP), named iRSHARP. It uses a spatially weighted spherical Gaussian kernel exploiting the amplitude, gradient, and wrap count of the phase map. The method was validated using both numerical simulations and in vivo human brain data at multiple head orientations. Performance was compared with the variable kernel (V-SHARP) and R-SHARP methods. Results: The proposed iRSHARP method showed improved background removal over R-SHARP while cutting the computational time in half. As compared to V-SHARP and R-SHARP, the iRSHARP generated local field and susceptibility maps showed fewer artifacts in regions of large susceptibility variations, and for the in vivo human brain, the susceptibilities of the deep gray matter nuclei were consistent with the in vivo gold-standard “Calculation of Susceptibility through Multiple Orientation Sampling” (COSMOS) values. Conclusion: iRSHARP can remove the orientation dependent background field effectively. Using iRSHARP, the paranasal sinus regions can be preserved in the brain mask and the brain integrity was conserved, which may facilitate further data analysis and clinical application.