Optimized 7-Tesla QSM reconstruction: Clinical feasibility

Motivation: Quantitative Susceptibility Mapping (QSM) at 7-Tesla (7T) has been implicated to improve assessment of neurodegenerative disorders but has yet to be integrated into clinical practice. Goal(s): We aimed to address the growing demand for a standardized and optimized QSM reconstruction protocol that enables accurate quantification of susceptibility, mitigates contaminating artifacts, and is clinically feasible. Approach: Here, we compared 32 end-to-end QSM processing pipelines and evaluated their performance. Results: We show that reconstruction with Laplacian phase-unwrapping, RESHARP background field removal, and MEDI dipole inversion outperformed other pipelines in suppressing artifacts. Impact: Our optimized pipeline results in a 7T QSM reconstruction with clear cortical and subcortical boundaries, and mitigates susceptibility artifacts. Furthermore, the comprehensive review of QSM processing algorithms highlights Laplacian, RESHARP, and MEDI as robust algorithms with reliable, consistent performance.