Characterization of noise and background signals in a magnetic particle imaging system

Magnetic particle imaging (MPI) is a novel technology, which opens new possibilities for promising biomedical applications. MPI uses magnetic fields to generate a specific response from magnetic nanoparticles (MNPs), to determine their spatial location non-invasively and without using ionizing radiation. One open challenge of MPI is to achieve further improvements in terms of sensitivity to translate the currently preclinical performed research into clinical applications. In this work, we study the noise and background signals of our preclinical MPI system, to identify and characterize disturbing signal contributions. The current limit of detection achieved with our device was determined previously to be20ng of iron. Based on the results presented in this work, we describe possible hardware and software improvements and estimate that the limit of detection could be lowered to about 1-2 ng. Additionally, a long-term analysis of the scanner performance over the last 3 years is presented, which proved to be an easy and effective way to monitor possible changes or damage of hardware components. All the presented results were obtained by analysing empty scanner measurements and the presented methodology can easily be adapted for different scanner types, to compare their performances.