Magnetic particle fingerprinting using arbitrary waveform relaxometer

Abstract

In magnetic particle imaging (MPI), the information about the local environment, such as its viscosity and temperature, can be inferred via the relaxation behavior of the nanoparticles. As the nanoparticle signal also changes with drive field (DF) parameters, one potential problem for quantitative mapping applications is the optimization of these parameters. In this work, an accelerated framework is proposed for characterizing the unique response of a nanoparticle under different environmental settings. The proposed technique, called magnetic particle fingerprinting (MPF), rapidly sweeps a wide range of DF parameters, mapping the unique tau-fingerprint of a sample. This technique can enable simultaneous mapping of several parameters (e.g., viscosity, temperature, nanoparticle type, etc.) with reduced scan time.