Ultrasound-based Eigenfrequency Analysis to Determine Material Parameters of Tissue Mimicking Phantoms

Abstract A modern area of research in cancer treatment is magnetic drug targeting (MDT) with superparamagnetic iron oxide nanoparticles (SPIONs). In order to understand the processes involved in MDT in more detail and to be able to perform this therapy as efficiently as possible, a monitoring system for the spatial distribution of SPIONs in biological tissue is required. One approach is to use magnetomotive ultrasound (MMUS) to monitor the spatial distribution over time. However, the spatial distribution of SPIONs cannot be quantitatively determined applying basic MMUS algorithms. Therefore, MMUS has been extended by a simulation part to quantitatively determine the spatial distribution of SPIONs. This extended MMUS algorithm requires the material parameters and the geometry of the target tumorous tissue. In this contribution, we describe an ultrasound-based eigenfrequency analysis combined with an iterative inverse simulation-based method to determine the mechanical parameter Young's modulus of tissue mimicking phantoms. The presented approach yields a good estimate of the Young's modulus compared to the result from a compression test.