470910 Insights into Magnetic Particle Imaging Obtained from Modeling

Wednesday, November 16, 2016: 9:55 AM
Golden Gate 6 (Hilton San Francisco Union Square)
Rohan Dhavalikar1, Daniel Hensley2, Lorena Maldonado-Camargo1, Steven Ceron3, Nicolas Garraud4, Laura R. Croft2, Patrick W. Goodwill5, Steven M. Conolly2, David P. Arnold4 and Carlos Rinaldi1,6, (1)Chemical Engineering, University of Florida, Gainesville, FL, (2)Bioengineering, University of California, Berkeley, CA, (3)Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, (4)Electrical and Computer Engineering, University of Florida, Gainesville, FL, (5)Magnetic Insight, Inc., Newark, CA, (6)J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL

Magnetic particle imaging (MPI) is an emerging biomedical imaging technology enabled by the non-linear response of magnetic nanoparticle tracers to a scanned magnetic gradient field.1 This tracer-based technology provides a safer alternative to other radioactive imaging modalities like single photon emission computed tomography (SPECT) and positron emission tomography (PET). MPI has been demonstrated in applications such as real-time cardiovascular imaging2, cell labeling and tracking3,4, and has potential in magnetic fluid hyperthermia.5 The original MPI theory assumes that tracers respond instantaneously to the magnetic fields encountered in MPI. In practice, this is not the case, and finite magnetic relaxation or response time has been implicated in secondary blurring of the image, even limiting the attainable resolution in MPI.6,7 To understand the effect of response time, or relaxation, on the MPI signal and resolution, we applied rotational Brownian dynamics (RBD) simulations8 and we observed a drop in resolution and signal. To investigate the effect of field-dependent relaxation we used ferrohydrodynamic modeling to obtain predictions of the point spread function (PSF) in an x-space relaxometer7 and the nanoparticle harmonic spectra in a magnetic particle spectrometer (MPS)9,10. These instruments are employed to assess the performance of tracers for use in MPI. Through this study we observed considerable agreement between the model predictions and experiments without the need of empirical parameter fits. Finally, we explored the potential of MPI field gradients in magnetic fluid hyperthermia to achieve selective heating of nanoparticles. Here, we used the ferrohydrodynamic equations to calculate theoretical predictions of specific absorption rate (SAR) and obtain millimeter scale spatial distribution of SAR by tuning the MPI field gradients. Through our modeling efforts we were able to understand the effect of relaxation in MPI and show the potential of MPI field gradients to achieve spatially selective magnetic fluid hyperthermia.

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