Decoding Sensitivity of Quantitative Susceptibility Mapping: Influence of Background Field Removal and Inversion Algorithms

Motivation: Quantitative Susceptibility Mapping (QSM) is widely applied in clinical research. However, its accuracy relies on the choice of background field removal (BFR) and inversion algorithms. This raises the question: What is the sensitivity of algorithms toward the detection of in-vivo group differences and over-time susceptibility changes?Goal(s): Explore the impact of BFR and inversion algorithms on the detection of over-time susceptibility changes. Approach: Utilizing six BFRs and twenty-one inversion algorithms, we studied the sensitivity to detect aging-related over-time susceptibility changes. Results: RESHARP+iSWIM within overall DGM, RESHARP+AMP-PE in putamen, PDF+IterTIK in caudate, PDF+TKD in globus pallidus and RESHARP+iSWIM in thalamus demonstrated the highest sensitivity. Impact: The importance of algorithm and reference region choice in QSM studies, impacting findings beyond demographics and clinical characteristics. Future research should employ varied QSM algorithms to assess their impact on longitudinal QSM changes, enhancing the quality of clinical investigations.