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International Journal of Hyperthermia Volume 37, 2020 - Issue 3: Nanomedicine and Thermal Therapies: Where Are We Going? Guest Editors: Andris Bakuzis
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Combining magnetic particle imaging and magnetic fluid hyperthermia for localized and image-guided treatment

Yao Lua Department of Bioengineering, University of California Berkeley, Berkeley, CA, USACorrespondence[email protected]
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,
Angelie Rivera-Rodriguezb J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USAView further author information
,
Zhi Wei Taya Department of Bioengineering, University of California Berkeley, Berkeley, CA, USAView further author information
,
Daniel Hensleyc Magnetic Insight, Inc, Alameda, CA, USAView further author information
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K.L. Barry Funga Department of Bioengineering, University of California Berkeley, Berkeley, CA, USAView further author information
,
Caylin Colsona Department of Bioengineering, University of California Berkeley, Berkeley, CA, USAView further author information
,
Chinmoy Saayujyad Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USAView further author information
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Quincy Huynhd Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USAView further author information
,
Leyla Kabulid Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USAView further author information
,
Benjamin Fellowsa Department of Bioengineering, University of California Berkeley, Berkeley, CA, USAView further author information
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Prashant Chandrasekharana Department of Bioengineering, University of California Berkeley, Berkeley, CA, USAView further author information
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Carlos Rinaldib J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA;e Department of Chemical Engineering, University of Florida, Gainesville, FL, USAView further author information
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Steven Conollya Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA;d Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USACorrespondence[email protected]
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Pages 141-154 | Received 24 Jun 2020, Accepted 05 Nov 2020, Published online: 10 Jan 2021

Figures & data

Figure 1. MPI can provide radiation-free, highly sensitive, and high resolution images. (a) Sensitive detection of gastro–intestinal bleed (Reproduced with permission from Yu et al. [Citation43]. Copyright (2017) American Chemical Society.) (b) Evaluation of inhaled drug therapeutics–MPI is not affected by air-tissue susceptibility interfaces and can even image in lungs (Reproduced with permission from Tay et al. Theranostics 2018 [Citation40]). (c) Hemorrhage diagnosis in TBI animal model (Reproduced with permission from Orandoff et al. 2017 Institute of Physics and Engineering in Medicine, IOP Publishing [Citation37]).

Figure 1. MPI can provide radiation-free, highly sensitive, and high resolution images. (a) Sensitive detection of gastro–intestinal bleed (Reproduced with permission from Yu et al. [Citation43]. Copyright (2017) American Chemical Society.) (b) Evaluation of inhaled drug therapeutics–MPI is not affected by air-tissue susceptibility interfaces and can even image in lungs (Reproduced with permission from Tay et al. Theranostics 2018 [Citation40]). (c) Hemorrhage diagnosis in TBI animal model (Reproduced with permission from Orandoff et al. 2017 Institute of Physics and Engineering in Medicine, IOP Publishing [Citation37]).

Figure 2. MPI fundamentals and systems. (a) A strong magnetic field gradient forms a sensitive point known as a Field Free Point (FFP). The FFP can be moved in a scanning trajectory to cover the imaging field of view. (b) SPIOs’ magnetization demonstrates nonlinear behavior as a function of the applied field, which can be modeled using a Langevin function ((a) and (b) are reproduced with permission from Patrick et al, Advanced Materials 2012, John Wiley and Sons [Citation81]). (c) and (d) are the hardware setups of MPI and MPI–MFH (Reproduced with permission from Tay et al., Copyright 2018 American Chemical Society [Citation22]).

Figure 2. MPI fundamentals and systems. (a) A strong magnetic field gradient forms a sensitive point known as a Field Free Point (FFP). The FFP can be moved in a scanning trajectory to cover the imaging field of view. (b) SPIOs’ magnetization demonstrates nonlinear behavior as a function of the applied field, which can be modeled using a Langevin function ((a) and (b) are reproduced with permission from Patrick et al, Advanced Materials 2012, John Wiley and Sons [Citation81]). (c) and (d) are the hardware setups of MPI and MPI–MFH (Reproduced with permission from Tay et al., Copyright 2018 American Chemical Society [Citation22]).

Figure 3. Localized selective heating using MPI–MFH. MPI gradients enable selective heating. The figure shows that the temperature increased only at the selected area. The animal liver and spleen were not affected when the gradient field was turned on. (Reproduced with permission from Tay et al., Copyright 2018 American Chemical Society [Citation22]).

Figure 3. Localized selective heating using MPI–MFH. MPI gradients enable selective heating. The figure shows that the temperature increased only at the selected area. The animal liver and spleen were not affected when the gradient field was turned on. (Reproduced with permission from Tay et al., Copyright 2018 American Chemical Society [Citation22]).

Figure 4. Spatial resolution of MPI and MPI–MFH: (a)Measured MPI PSF using an AWR (Reproduced with permission from Tay et al., 2017 Biomedical Physics & Engineering Express, IOP Publishing [Citation66]); (b) Simulation showing the SAR resolution of MPI–MFH under different frequencies of the oscillating magnetic field (Reproduced with permission from Dhavalikar et al., Journal of Magnetism and Magnetic Materials 2016, Elsevier [Citation70]); and (c) the measured heating resolution of MPI–MFH using an optical probe (Reproduced with permission from Tay et al., Copyright 2018 American Chemistry Society [Citation22]).

Figure 4. Spatial resolution of MPI and MPI–MFH: (a)Measured MPI PSF using an AWR (Reproduced with permission from Tay et al., 2017 Biomedical Physics & Engineering Express, IOP Publishing [Citation66]); (b) Simulation showing the SAR resolution of MPI–MFH under different frequencies of the oscillating magnetic field (Reproduced with permission from Dhavalikar et al., Journal of Magnetism and Magnetic Materials 2016, Elsevier [Citation70]); and (c) the measured heating resolution of MPI–MFH using an optical probe (Reproduced with permission from Tay et al., Copyright 2018 American Chemistry Society [Citation22]).

Figure 5. Comparison of MPI–MFH among other magnetic hyperthermia techniques: (a) Whole body MFH will heat all locations where MNPs are accumulated including healthy tissue; (b) Surface coils can be used to target surface tumors but not sites deep in the body; (c) MPI–MFH can target any site in the body using the FFR, including those deep in the body with high resolution [Citation21]. (Reproduced with permission from Hensley et al., 2017 Physics in Medicine & Biology, IOP Publishing [Citation21]).

Figure 5. Comparison of MPI–MFH among other magnetic hyperthermia techniques: (a) Whole body MFH will heat all locations where MNPs are accumulated including healthy tissue; (b) Surface coils can be used to target surface tumors but not sites deep in the body; (c) MPI–MFH can target any site in the body using the FFR, including those deep in the body with high resolution [Citation21]. (Reproduced with permission from Hensley et al., 2017 Physics in Medicine & Biology, IOP Publishing [Citation21]).

Figure 6. Arbitrary waveform relaxometer (AWR) for characterizing magnetic nanoparticles for MPI and MFH: (a) Prototype of AWR developed at UC Berkeley. (b) The AWR covers all possible driving waveforms (in both frequency and field amplitude) considered safe for human scanning, and can be used to test MNP performance. This enables comprehensive driving waveform optimization. In contrast, conventional VSM [Citation94] and AC susceptometry [Citation95] cannot cover the entire driving waveform range of interest for MPI. (c) The AWR can characterize the nanoparticle PSF without the need for an MPI scanner. (Reproduced with permission from Tay et al., Scientific Reports 2016, Springer Nature [Citation96]).

Figure 6. Arbitrary waveform relaxometer (AWR) for characterizing magnetic nanoparticles for MPI and MFH: (a) Prototype of AWR developed at UC Berkeley. (b) The AWR covers all possible driving waveforms (in both frequency and field amplitude) considered safe for human scanning, and can be used to test MNP performance. This enables comprehensive driving waveform optimization. In contrast, conventional VSM [Citation94] and AC susceptometry [Citation95] cannot cover the entire driving waveform range of interest for MPI. (c) The AWR can characterize the nanoparticle PSF without the need for an MPI scanner. (Reproduced with permission from Tay et al., Scientific Reports 2016, Springer Nature [Citation96]).

Figure 7. Berkeley MPI viscosity sensing: (a) Illustration of relaxation measurement. In sinusoidal excitation, relaxation induces a significant lag and blurring of the image. In pulsed MPI, due to the fast transit, the relaxation and the square wave response are well separated in time domain. (Reproduced with permission from Tay et al, IEEE Transactions on Medical Imaging, IEEE [Citation79]) (b) Pulsed MPI relaxation times scale linearly with medium’s viscosity, with ideal R2 [Citation108]. (c) Relaxation detects ligand–receptor interaction; streptavidin-coated SPIOs binding to biotinylated albumin [Citation108]. (Reproduced with permission from Hensley, PhD dissertation, University of California, Berkeley 2017 [Citation108]).

Figure 7. Berkeley MPI viscosity sensing: (a) Illustration of relaxation measurement. In sinusoidal excitation, relaxation induces a significant lag and blurring of the image. In pulsed MPI, due to the fast transit, the relaxation and the square wave response are well separated in time domain. (Reproduced with permission from Tay et al, IEEE Transactions on Medical Imaging, IEEE [Citation79]) (b) Pulsed MPI relaxation times scale linearly with medium’s viscosity, with ideal R2 [Citation108]. (c) Relaxation detects ligand–receptor interaction; streptavidin-coated SPIOs binding to biotinylated albumin [Citation108]. (Reproduced with permission from Hensley, PhD dissertation, University of California, Berkeley 2017 [Citation108]).

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