Multi-Contrast Magnetic Particle Imaging

Magnetic particle imaging is a tracer-based tomographic imaging technique that uses static and oscillating magnetic fields to generate an image contrast from the spatial distribution of magnetic nanoparticles. Recent investigations have shown that multi-contrast MPI is able to generate additional contrasts from different tracer materials or their environments. In this project we investigate tracer properties and properties of the particle environment that influence the tracer relaxation behavior using multi-contrast MPI, such as

To speed up the multi-contrast MPI image reconstruction, we have introduced an accelerated Kaczmarz algorithm. we have also introduced some potential medical and physical applications of multi-contrast MPI, such as 3D tracking of endovascular devices and balloon catheter imaging

Using the Accelerated Kaczmarz for multi-contrast MPI reconstruction speeds up the convergence.

Publications

[100542]
Title: Viscosity quantification using multi-contrast magnetic particle imaging.
Written by: M. Möddel, C. Meins, J. Dieckhoff, and T. Knopp
in: <em>New Journal of Physics</em>. (2018).
Volume: <strong>20</strong>. Number: (8),
on pages: 083001
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DOI: 10.1088/1367-2630/aad44b
URL: http://iopscience.iop.org/article/10.1088/1367-2630/aad44b
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Note: article, multi-contrast, openaccess

Abstract: Abstract Magnetic particle imaging (MPI) is a relatively new tomographic imaging technique using static and oscillating magnetic fields to image the spatial distribution of magnetic nanoparticles. The latter being the contrast MPI has been initially designed for. However, recently it has been shown that MPI can be extended to a multi-contrast method that allows to simultaneously image the signals of different MPI tracer materials. Additionally, it has been shown that changes in the particles environment, e.g. the viscosity have an impact on the MPI signal and can potentially be used for functional imaging. The purpose of the present work is twofold. First, we generalize the MPI imaging equation to describe different multi-contrast settings in a unified framework. This allows for more precise interpretation and discussion of results obtained by single- and multi-contrast reconstruction. Second, we propose and validate a method that allows to determine the viscosity of a small sample from a dual-contrast reconstruction. To this end, we exploit a calibration curve mapping the sample viscosity onto the relative signal weights within the channels of the dual-contrast reconstruction. The latter allows us to experimentally determine the viscosity of the particle environment in the range of 1 mPas to 51.8 mPas with a relative methodological error of less than 6%.