MPI-based estimation of absolute temperature using 1D system matrices

Abstract

Magnetic Particle Imaging (MPI) thermometry enables temperature mapping by exploiting temperature-dependent response of magnetic nanoparticles. These changes, influenced by particle physics (thermal agitation, relaxation dynamics), allow MPI to provide time-resolved temperature monitoring, making it a promising feed-back parameter for applications such as hyperthermia. However, current system matrix-based or ‘multi-color’ methods require time-consuming, three-dimensional calibration measurements that limit practical application and primarily yield relative temperature values only. Here, we present a novel system matrix thermometry method to enhance the efficiency of local MPI-based temperature estimation comprising MPI signals acquired at various temperatures and spatial positions along a defined line. Using MPI signals with 1D excitation and 100 averages, we demonstrate accurate estimation of absolute temperature (std <2 K) based on calibration with 11 individual matrices (~1 min each) in 2 K increments (T_min=25°C, T_max=45°C). This approach enables estimation of absolute temperatures within ~1 s and significantly reduces calibration time to ~20 minutes.