Evaluating selection criteria for optimized excitation coils in magnetorelaxometry imaging.

Magnetorelaxometry imaging (MRXI) is an experimental imaging technique applicable for noninvasive, qualitative and quantitative imaging of magnetic nanoparticles (MNPs). Accurate reconstructions of nanoparticle distributions are crucial for several novel treatment methods employing MNPs such as magnetic drug targeting or magnetic hyperthermia therapy. Hence, it is desirable to design MRXI setups such that the reconstruction accuracy is maximized for a given set of design parameters. Several attempts exist in literature that focus on the improvement of MRXI and other related linear inverse problems with respect to various figures of merit. However, to date it remains unclear, which approach leads to the largest benefit for the reconstruction accuracy. Thus, the aim of this study is to compare the different figures of merit, thereby determining the most reliable and effective optimization approach for magnetorelaxometry setups.In the present simulation study, we translate these figures of merit to various cost functions, allowing us to optimize the electromagnetic coil positions and radii of two distinct MRXI setups with an adapted tabu search algorithm. Multiple artificial MNP phantoms are reconstructed employing the optimized setups and the resulting imaging qualities are subsequently compared.The extensive amount of generated synthetic data unprecedented in previous MRXI studies identifies the condition number as the most reliable indicator for good imaging results. This is the case for both the qualitative as well as the quantitative reconstruction accuracies.The results of this study show that optimized coil configurations increase the reconstruction quality compared to the state-of-the-art. The insights obtained here can also be extended to other design parameters of MRXI setups, thus enabling more reliable reconstructions of MNP ensembles which will ultimately render the aforementioned treatment methods safer and more efficient.