PURPOSE:Magnetic particle hyperthermia (MPH), the mild heating of solid tumors with magnetic nanoparticles, is an emerging treatment modality used as an adjuvant to therapies such as ionizing radiation. MPH can be paired with magnetic particle imaging (MPI) hardware to improve thermal treatment planning, spatially confined heating, and thermal dose delivery. In this work, we describe the design, verification, and validation of a radiofrequency (RF) head coil designed to integrate into a clinical MPI scanner. METHODS:The RF coil was designed to accommodate an adult human head, provide a homogeneous (±10%) field along a 10 cm axial centerline, generate a peak magnetic flux density of 10 mT at 100 kHz, and be MPI compliant. Verification of the design consisted of a combination of magnetic field and nanoparticle heating measurements. To validate an MPI/MPH imaging and heating workflow, a canine cadaver was surgically prepared by implanting magnetic nanoparticles in the brain, followed by anatomical imaging, MPI, and heating with the head coil. To explore if the measured performance can be generalized to human treatment, we conducted a virtual MPH treatment of a human glioma. RESULTS:Coil performance verification demonstrated RF fields as high as Bpeak=14 mT at 100.4 kHz, while achieving hyperthermic temperatures in tumor phantoms. The MPI scan of the canine cadaver head revealed differences in signal intensity between particle injection sites, which correlated with temperature increases measured during heating. Computational simulation of a human head showcased the feasibility of this system to treat gliomas. CONCLUSIONS:We successfully constructed, verified, and validated an MPI-compatible RF head coil for combined MPI/MPH therapy.

Magnetic Particle Imaging (MPI) is a tracer-based medical imaging modality that detects magnetic nanoparticles with no background tissue signal. MPI acquires quantitative, high-sensitivity tomographic images of shelf-stable magnetic tracers that safely produce signals in vivo for weeks or even months. These features can fill capability gaps in medical imaging for applications benefiting from tracer specificity with an extended imaging window. Despite two decades of preclinical validation and multiple published human-scale imagers, MPI has not previously been demonstrated in human subjects. Here we report MPI imaging in two subjects following subcutaneous administration of magnetic tracer in the scalp and foot. Our results showed quantitative and longitudinal visualization of lymphatic drainage for up to six months, with supporting validation in a mouse model. Imaging in human subjects required the development and verification of a novel clinical imager, including magnetostimulation threshold testing of all magnetic fields used in imaging sequences. To understand MPI in the context of existing medical imaging technologies, we benchmarked MPI imaging performance against SPECT using lymphatic system phantom models. These findings demonstrate that MPI can translate from animals to human subjects, and establish MPI as a new tool for longitudinal tracer imaging in medicine. The addition of MPI to the clinical imaging toolbox could enable new approaches and capabilities for diagnosis, real-time interventions, and treatment monitoring across a broad range of clinical applications.

The compressibility, viscosity, and temperature of hydrogel tissue phantoms affect the MPI signal of MNP tracers, which may impact accurate in vivo tracer quantification.

Objective.Magnetic particle imaging (MPI) is an emerging tomographic 'hot spot' imaging modality with potential to visualize superparamagnetic iron oxide nanoparticle tracer distributions with high sensitivity and quantitative accuracy. MPI shares many similarities with positron emission tomography (PET), where the partial volume effect (PVE) can result in signal under- and over-quantification due to spill-over of signal arising from limited resolution. While the PVE has been alluded to in the MPI literature it has not been previously studied nor characterized. The objective of this study was to systematically characterize this PVE in MPI.Approach.This contribution characterizes the PVE using models of varying size and shape filled with a uniform concentration of tracer. The effect of object size on signal distribution was analyzed after application of a new image post-processing filter.Main results.As object size increased, signal distribution increased to a maximum signal value independent of object geometry and proportional to tracer concentration. Furthermore, for small objects with characteristic dimensions below the resolution of the tracer at the scanning conditions used, signal suppression was observed. These results are consistent with foundational observations of PVE in PET, suggesting that approaches to overcome the PVE in PET may be applicable to MPI.Significance.This finding has significant impact on the MPI field by demonstrating the presence of the PVE phenomenon that can directly influence imaging results.

This article derives and implements a computational physics model for model-based image reconstruction in magnetic particle imaging (MPI) applications. To our knowledge, this is the first ever computationally tractable model-based image reconstruction in MPI, which is neither constructed from calibration or simulation experiments or limited to specific scan acquisition geometries. The derived model results in a system constructed from a series of fast linear transforms, each of which incorporate the individual components from the paramagnetic model. These include the field free point velocity and location, gradient strength, receive coil sensitivity, and receive chain filtering. Each of these modeling components are amendable to any changes in the acquisition parameters. This allows us to adopt a computationally tractable system matrix modeling approach to MPI for any scan specific parameters at very high pixel resolutions. The model is derived from first principles, and it results from taking the fundamental MPI signal theory and decomposing these modeling equations into the series of linear transforms acting on a pixelated image. Each transform is formally defined in matrix form but implemented in a matrix-free fashion with fast and/or sparse operations. For these reasons, our new model should be a fundamental tool in the future of computational imaging in MPI. We demonstrate our new method on a variety of pre-clinical and simulated data sets, and these results confirm that our method is both efficient and accurate.

Magnetic particle imaging (MPI) is an emerging modality that can address longstanding technological challenges encountered with magnetic particle hyperthermia (MPH) cancer therapy. MPI is a tracer technology compatible with MPH for which magnetic nanoparticles (MNPs) provide signal for MPI and heat for MPH. Identifying whether a specific MNP formulation is suitable for both modalities is essential for clinical implementation. Current models predict that functional requirements of each modality impose conflicting demands on nanoparticle magnetic properties. This objective here is to develop a measurement and ranking scheme based on end-use performance to streamline evaluation of candidate MNP formulations. The measured MPI point-spread function (PSF) and specific loss power (SLP) is combined to generate a single numerical value for comparison on a relative ranking scale, or figure of merit (FoM). 12 aqueous iron-containing formulations are evaluated, including FDA-approved (parenteral) iron-containing colloids. MNPs with high (Synomag-D70: 123.4), medium (Synomag-D50: 63.2), and low (NanoXact: 0.147) FoM values are selected for in vivo validation of the selection scheme in subcutaneous 4T1 tumors. Results demonstrate that the proposed ranking accurately assessed the relative performance of MNPs for MPI and MPH. Data demonstrated that image quality and tumor temperature rise increased with FoM ranking, validating predictions. It isshown that the MPI signal correlated with MNP concentration in tissue. Computational heat transfer models anchored on tumor MPI data harmonized with experimental results to within an average of 2 degrees C when MNP content estimated from MPI data is included. Computational studies emphasized the importance of post-injection MNP quantitation and MPI spatial resolution. Magnetic particle imaging (MPI) is a nascent modality that can provide imaging guidance for magnetic particle hyperthermia (MPH) to treat cancer. For MPI, magnetic particles are both imaging tracers and therapeutic heaters. A particle ranking system is validated, which condenses particle imaging and heating performance into a single metric to aid particle selection. image

Introduction Clinical adoption of NK cell immunotherapy is underway for medulloblastoma and osteosarcoma, however there is currently little feedback on cell fate after administration. We propose magnetic particle imaging (MPI) for the detection, localization, and quantification of VivoTrax-labeled NK cells. Methods Human-derived NK-92 cells were labeled by co-incubation with VivoTrax for 24 hours then the excess nanoparticles were washed with centrifugation. Cytolytic activity of labeled vs. unlabeled NK-92 cells was assessed after 4 hours of co- incubation with medulloblastoma cells (DAOY) or osteosarcoma cells (LM7 or OS17) using bioluminescent or GFP counts. Labeled NK-92 cells at two different doses (0.5 or 1 x 106) were administered to excised mouse brains (cerebellum), tibias, and lungs then imaged by 3D preclinical MPI (MOMENTUM imager) and localized relative to fiducial markers. NK-92 cells were imaged by clinical-scale MPI under development at Magnetic Insight Inc. Results NK-92 cells were labeled with an average of 3.17 pg Fe/cell with no measured effects on cell viability or cytolytic activity against 3 tumor cell lines. MPI signal was directly quantitative with the number of VivoTrax-labeled NK-92 cells, with preclinical limit of detection of 3.1 x 104 cells on MOMENTUM imager. Labeled NK-92 cells could be accurately localized in mouse brains, tibias, and lungs within < 1 mm of stereotactic injection coordinates with preclinical scanner. Feasibility for detection of a clinically relevant dose of 4 x 107 labeled NK-92 cells was demonstrated on clinical-scale MPI. Conclusion MPI can provide sensitive, quantitative, and accurate spatial information on NK cell delivery, showing its potential to resolve a significant unmet clinical need to track NK cell treatments in patients. ### Competing Interest Statement Olivia C. Sehl, Kelvin Guo, Benjamin Fellows, A. Rahman Mohtasebzadeh, Erica E. Mason, Toby Sanders, Petrina Kim, David Trease, Patrick W. Goodwill, and Joan M Greve report relationship with Magnetic Insight Inc. that includes: employment and stock ownership.

Abstract Sentinel Lymph Node (LN) biopsy involves the identification and surgical removal of the first LN(s) that drain from a primary tumor to evaluate for metastasis by histopathology [1]. For several tumor types, the standard of care is to manage the regional LN basin separately from the primary tumor. For head and neck cancer, melanoma, and complex breast cancer cases, pre-surgical imaging is required to determine the number and location of LN(s) to remove. Most sentinel LN biopsies are performed with nuclear imaging, which relies on short-lived radiotracers and can have poor image quality, making it challenging to identify sentinel LNs in complex anatomies. An alternative and non-inferior workflow uses a non-radioactive iron oxide magnetic tracer (ferucarbotran) with a magnetic probe [2], however this tool can only be used intraoperatively. In this abstract we introduce magnetic particle imaging (MPI) as a pre-surgical imaging technology that detects iron oxides with high sensitivity at mm-scale resolution [3]. Our objective is to demonstrate that MPI provides sensitive and quantitative tracking of ferucarbotran pharmacokinetics from four anatomical sites to primary draining LNs in mice. Methods: Ferucarbotran was administered intradermally to C57BL/6 mice at a standard clinical dose of 0.675 mg Fe/kg to the forepaw, hindpaw, or base of tail, or tongue (n = 4). Full-body 2D and 3D imaging was performed after 20 mins, 24 h, and 48 h, and 144 h using MOMENTUM imager (Magnetic Insight Inc.). MPI signal was quantified at the injection site and draining LNs. LNs of interest were extracted to verify MPI signals ex vivo then were processed for Perl’s Prussian iron staining. Results: After 20 minutes, MPI signal was seen at the injection site and primary LNs. The pharmacokinetics of ferucarbotran to LNs varied based on administration site. For hindpaw, signal was present in the popliteal LN (1.4% of tracer). For forepaw, ferucarbotran accumulated in the primary axillary LN (9%). For base of the tail, signal was observed in inguinal LN (2%). For tongue, MPI signal was detected in cervical LNs (14%). In all mice, MPI signal at the injection site decreased over time and signal in primary LNs persisted for at least 6 days. Conclusions: We demonstrated MPI is a quantitative, hotspot imaging technique for identifying primary LNs. As iron oxide tracer pharmacokinetics varies with injection site, this imaging technique could provide fundamental information required for surgical planning. Unlike nuclear imaging, persistence of MPI signal for several days provides tremendous flexibility in clinical workflow and introduces the potential for an image-guide delayed SLN biopsy [4] . This preclinical LN imaging is timely as our team is actively building and testing the world’s first large-bore, clinical-scale MPI scanner.[1] Leong SP, Clin Exp Metastasis (2022). [2] Alvarado MD, et al. Ann Surg Oncol (2019). [3] Sarnitas EU, et al. J Magn Reson (2014). [4] Karakatsanis A, et al. Ann Surg Oncol (2023). Citation Format: Olivia C. Sehl, A. Rahman Mohtasebzadeh, Kelvin Guo, Petrina Kim, Benjamin Fellows, Marcela Weyhmiller, Paula J. Foster, Patrick W. Goodwill, Joan M. Greve. First demonstration of magnetic particle imaging for sentinel lymph node identification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4135.

Tumour Associated Macrophages (TAMs) play a crucial role in breast cancer progression and have the potential to be used as a biomarker for patient prognosis. Magnetic particle imaging (MPI) is an emerging modality which can detect cells labelled with superparamagnetic iron oxide (SPIO) nanoparticles and can be used for non-invasive TAM assessment. However, MPI TAM detection is limited by its effective dynamic range. This limitation occurs when SPIO nanoparticles injected intravenously accumulate in the liver resulting in a large MPI signal which shadows regions of interest with lower signals (i.e the tumour) preventing their isolation and quantification. In this study we test an advanced reconstruction algorithm which allows us to prescribe a small focused field of view (FOV) on lower signals of interest. We then demonstrate the success of this method with an in vivo tumour model and show enhanced image quality and successful quantification of TAMs in mouse mammary tumours with different metastatic potentials (4T1 and E0771). Utilizing in vivo MPI, we did not see significant differences in the MPI signal for 4T1 tumours compared to E0771. These findings highlight the potential of MPI for in vivo TAM quantification offering a promising avenue for broader applications in cancer research and potentially overcoming constraints of MPI in other in vivo imaging contexts. ### Competing Interest Statement The authors have declared no competing interest.

Background:Sentinel lymph node biopsy (SLNB) is an important cancer diagnostic staging procedure. Conventional SLNB procedures with 99mTc radiotracers and scintigraphy are constrained by tracer half-life and, in some cases, insufficient image resolution. Here, we explore an alternative magnetic (nonradioactive) image-guided SLNB procedure. Purpose:To demonstrate that magnetic particle imaging (MPI) lymphography can sensitively, specifically, and quantitatively identify and map sentinel lymph modes (SLNs) in murine models in multiple regional lymphatic basins. Materials and Methods:Iron oxide nanoparticles were administered intradermally to healthy C57BL/6 mice (male, 12-week-old, n = 5). The nanoparticles (0.675 mg Fe/kg) were injected into the tongue, forepaw, base of tail, or hind footpad, then detected by 3-dimensional MPI at multiple timepoints between 1 hour and 4 to 6 days. In this mouse model, the SLN is represented by the first lymph node draining from the injection site. SLNs were extracted to verify the MPI signal ex vivo and processed using Perl's Prussian iron staining. Paired t-test was conducted to compare MPI signal from SLNs in vivo vs. ex vivo and considered significant if P < .05. Results:MPI lymphography identified SLNs in multiple lymphatic pathways, including the cervical SLN draining the tongue, axillary SLN draining the forepaw, inguinal SLN draining the tail, and popliteal SLN draining the footpad. MPI signal in lymph nodes was present after 1 hour and stable for the duration of the study (4-6 days). Perl's Prussian iron staining was identified in the subcapsular space of excised SLNs. Conclusion:Our data support the use of MPI lymphography to specifically detect SLN(s) using a magnetic tracer for a minimum of 4 to 6 days, thereby providing information required to plan the SLN approach in cancer surgery. As clinical-scale MPI is developed, translation will benefit from a history of using iron-oxide nanoparticles in human imaging and recent regulatory-approvals for use in SLNB.

Magnetic particle imaging (MPI) is an emerging modality that can address longstanding technological challenges encountered with magnetic particle hyperthermia (MPH) cancer therapy. MPI is a tracer technology compatible with MPH for which magnetic nanoparticles (MNPs) provide signal for MPI and heat for MPH. Identifying whether a specific MNP formulation is suitable for both modalities is essential for clinical implementation. Current models predict that functional requirements of each modality impose conflicting demands on nanoparticle magnetic properties. This objective here is to develop a measurement and ranking scheme based on end-use performance to streamline evaluation of candidate MNP formulations. The measured MPI point-spread function (PSF) and specific loss power (SLP) is combined to generate a single numerical value for comparison on a relative ranking scale, or figure of merit (FoM). 12 aqueous iron-containing formulations are evaluated, including FDA-approved (parenteral) iron-containing colloids. MNPs with high (Synomag-D70: 123.4), medium (Synomag-D50: 63.2), and low (NanoXact: 0.147) FoM values are selected for in vivo validation of the selection scheme in subcutaneous 4T1 tumors. Results demonstrate that the proposed ranking accurately assessed the relative performance of MNPs for MPI and MPH. Data demonstrated that image quality and tumor temperature rise increased with FoM ranking, validating predictions. It isshown that the MPI signal correlated with MNP concentration in tissue. Computational heat transfer models anchored on tumor MPI data harmonized with experimental results to within an average of 2 °C when MNP content estimated from MPI data is included. Computational studies emphasized the importance of post-injection MNP quantitation and MPI spatial resolution.

Clinical adoption of NK cell immunotherapy is underway for medulloblastoma and osteosarcoma, however there is currently little feedback on cell fate after administration. We propose magnetic particle imaging (MPI) may have applications for the quantitative detection of NK cells. Human-derived NK-92 cells were labeled by co-incubation with iron oxide nanoparticles (VivoTrax™) for 24 h then excess nanoparticles were washed with centrifugation. Cytolytic activity of labeled versus unlabeled NK-92 cells was assessed after 4 h of co-incubation with medulloblastoma cells (DAOY) or osteosarcoma cells (LM7 or OS17). Labeled NK-92 cells at two different doses (0.5 or 1 × 106) were administered to excised mouse brains (cerebellum), fibulas, and lungs then imaged by 3D preclinical MPI (MOMENTUM™) for detection relative to fiducial markers. NK-92 cells were also imaged by clinical-scale MPI under development at Magnetic Insight Inc. NK-92 cells were labeled with an average of 3.17 pg Fe/cell with no measurable effects on cell viability or cytolytic activity against 3 tumor cell lines. MPI signal was directly quantitative with the number of labeled NK-92 cells, with preclinical limit of detection of 3.1 × 104 cells on MOMENTUM imager. Labeled NK-92 cells could be accurately localized in mouse brains, fibulas, and lungs within < 1 mm of stereotactic injection coordinates with preclinical scanner. Feasibility for detection on a clinical-scale MPI scanner was demonstrated using 4 × 107 labeled NK-92 cells, which is in the range of NK cell doses administered in our previous clinical trial. MPI can provide sensitive, quantitative, and accurate spatial information on NK cells soon after delivery, showing initial promise to address a significant unmet clinical need to track NK cell fate in patients.

Magnetic particle hyperthermia (MPH) enables the direct heating of solid tumors with alternating magnetic fields (AMFs). One challenge with MPH is the unknown particle distribution in tissue after injection. Magnetic particle imaging (MPI) can measure the nanoparticle content and distribution in tissue after delivery. The objective of this study was to develop a clinically translatable protocol that incorporates MPI data into finite element calculations for simulating tissue temperatures during MPH. To verify the protocol, we conducted MPH experiments in tumor-bearing mouse cadavers. Five 8–10-week-old female BALB/c mice bearing subcutaneous 4T1 tumors were anesthetized and received intratumor injections of Synomag®-S90 nanoparticles. Immediately following injection, the mice were euthanized and imaged, and the tumors were heated with an AMF. We used the Mimics Innovation Suite to create a 3D mesh of the tumor from micro-computerized tomography data and spatial index MPI to generate a scaled heating function for the heat transfer calculations. The processed imaging data were incorporated into a finite element solver, COMSOL Multiphysics®. The upper and lower bounds of the simulated tumor temperatures for all five cadavers demonstrated agreement with the experimental temperature measurements, thus verifying the protocol. These results demonstrate the utility of MPI to guide predictive thermal calculations for MPH treatment planning.

Magnetic particle imaging (MPI) is a new tracer-based imaging modality that is useful in diagnosing various pathophysiology related to the vascular system and for sensitive tracking of cytotherapies. MPI uses nonradioactive and easily assimilated nanometer-sized iron oxide particles as tracers. MPI images the nonlinear Langevin behavior of the iron oxide particles and has allowed for the sensitive detection of iron oxide-labeled therapeutic cells in the body. This review will provide an overview of MPI technology, the tracer, and its use in vascular imaging and cytotherapies using molecular targets.

AbstractMagnetic Particle Imaging (MPI) directly detects superparamagnetic iron oxide (SPIO) labeled cells. We have used MPI to detect SPIO-labeled dendritic cells (DC) migrated to the popliteal lymph nodes (pLN) after injection into the hind footpads. However, in some cases the low pLN signal could not be resolved from nearby higher footpad signal where window leveling to pLN signal oversaturated the footpad signal. The same limitation occurs when SPIO is injected intravenously, accumulates in the liver, and prevents isolation of regions of interest with lower signals. Previous studies have reported on the issue of resolving a wide range of differing iron concentration. A small focused field of view (FOV), to exclude high sources of nearby signal cannot be performed with the standard reconstruction algorithm equipped on the MomentumTM MPI scanner because it is assumed that there is no signal at the edge of the FOV and these values are set to zero for each line along the transmit axis. However, when there is signal at the FOV edge, an inverted negative artifact is created. The multichannel joint reconstruction method uses an iterative reconstruction technique to recover edge information using information from an orthogonal axis, preventing this artifact and allowing the user to prescribe a small FOV on the region of interest. Here we describe the implementation of this method to isolate and quantify low regions of MPI signal from higher regions.

Purpose Magnetic particle hyperthermia is an approved cancer treatment that harnesses thermal energy generated by magnetic nanoparticles when they are exposed to an alternating magnetic field (AMF). Thermal stress is either directly cytotoxic or increases the susceptibility of cancer cells to standard therapies, such as radiation. As with other thermal therapies, the challenge with nanoparticle hyperthermia is controlling energy delivery. Here, we describe the design and implementation of a prototype pre-clinical device, called HYPER, that achieves spatially confined nanoparticle heating within a user-selected volume and location.Design Spatial control of nanoparticle heating was achieved by placing an AMF generating coil (340 kHz, 0-15 mT), between two opposing permanent magnets. The relative positions between the magnets determined the magnetic field gradient (0.7 T/m-2.3 T/m), which in turn governed the volume of the field free region (FFR) between them (0.8-35 cm3). Both the gradient value and position of the FFR within the AMF ([-14, 14]x, [-18, 18]y, [-30, 30]z) mm are values selected by the user via the graphical user interface (GUI). The software then controls linear actuators that move the static magnets to adjust the position of the FFR in 3D space based on user input. Within the FFR, the nanoparticles generate hysteresis heating; however, outside the FFR where the static field is non-negligible, the nanoparticles are unable to generate hysteresis loss power.Verification We verified the performance of the HYPER to design specifications by independently heating two nanoparticle-rich areas of a phantom placed within the volume occupied by the AMF heating coil.

Abstract Magnetic Particle Imaging (MPI) directly detects superparamagnetic iron oxide (SPIO) labeled cells. We have used MPI to detect SPIO-labeled dendritic cells (DC) migrated to the popliteal lymph nodes (pLN) after injection into the hind footpads. However, in some cases the low pLN signal could not be resolved from nearby higher footpad signal where window leveling to pLN signal oversaturated the footpad signal. The same limitation occurs when SPIO is injected intravenously, accumulates in the liver, and prevents isolation of regions of interest with lower signals. Previous studies have reported on the issue of resolving a wide range of differing iron concentration. A small focused field of view (FOV), to exclude high sources of nearby signal cannot be performed with the standard reconstruction algorithm equipped on the MomentumTM MPI scanner because it is assumed that there is no signal at the edge of the FOV and these values are set to zero for each line along the transmit axis. However, when there is signal at the FOV edge, an inverted negative artifact is created. The multichannel joint reconstruction method uses an iterative reconstruction technique to recover edge information using information from an orthogonal axis, preventing this artifact and allowing the user to prescribe a small FOV on the region of interest. Here we describe the implementation of this method to isolate and quantify low regions of MPI signal from higher regions.

MPI directly detects superparamagnetic iron oxides (SPIONs), which should enable precise, accurate, and linear quantification. However, selecting a region of interest (ROI) has strong effects on MPI quantification results. Ideally, ROI selection should be simple, user-independent, and widely applicable. In this work, we describe and compare four MPI ROI selection methods and assess their performance in vitro and in vivo. To explore the effect of ROI selection, ten ferucarbotran phantoms were imaged, each contained the same amount of iron but varied in volume. Three users tested the accuracy of the ROI methods for quantification of these samples. Lastly, the four ROI methods were applied to quantify ferucarbotran in vivo after intravenous, intramuscular, and subcutaneous injections in mice. We demonstrate that each ROI method has strengths. We conclude there is an important trade-off between ROI size and the accuracy of iron quantification, therefore the choice of ROI selection method for each study must be carefully informed.

Magnetic nanomaterials that respond to clinical magnetic devices have significant potential as cancer nanotheranostics. The complexities of their physics, however, introduce challenges for these applications. Hyperthermia is a heat-based cancer therapy that improves treatment outcomes and patient survival when controlled energy delivery is combined with accurate thermometry. To date, few technologies have achieved the needed evolution for the demands of the clinic. Magnetic fluid hyperthermia (MFH) offers this potential, but to be successful it requires particle-imaging technology that provides real-time thermometry. Presently, the only technology having the potential to meet these requirements is magnetic particle imaging (MPI), for which a proof-of-principle demonstration with MFH has been achieved. Successful clinical translation and adoption of integrated MPI/MFH technology will depend on successful resolution of the technological challenges discussed. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > In Vivo Nanodiagnostics and Imaging