Magnetic particle imaging resolution needed for magnetic hyperthermia treatment planning: a sensitivity analysis

Purpose

Magnetic particle imaging (MPI) is a nascent tracer imaging modality that generates images from magnetic iron oxide nanoparticles (MIONs) in tissue. MPI resolution is a critical input parameter for defining the reliability of simulations-based temperature predictions for magnetic nanoparticle hyperthermia (MNPH). The objective of this study was to ascertain how spatial resolution provided by MPI data affects the reliability of predicted temperatures and thermal dose in simulations using MPI data as inputs.

Methods

Computed tomography (CT) and MPI scans obtained from a tumor injected with MIONs were co-registered to align their coordinates. Co-registered data were used to obtain geometry and volumetric heat sources for computational simulations of MNPH in phantom tumors. In addition to using the MPI-derived in vivo MION distribution (D1) we analyzed two mathematical MION distributions: uniform (D2) and Gaussian (D3). All distributions were discretized into cubic voxels and the data were imported into a commercial finite element bioheat transfer (FEBHT) software for thermal simulations. FEBHT simulations were conducted using the Pennes' bioheat equation using four different MION specific loss power (SLP) values in the range 300-600 [W/g Fe]. The impact on predicted temperature resolution and thermal dose of spatial resolution were assessed by varying the linear voxel density (LVD) from 0.36 to 4.06 [voxel/mm]. Results were compared against the simulation with the highest LVD [4.06(voxel/mm)], where deviations in temperature of ≤ ±1 [°C] and thermal dose coverage ≤ ±5 [%] were deemed acceptable.

Results

The D3 distribution resulted in the highest predicted temperatures, followed by D1 and D2; however, in terms of thermal dose, D1 showed lowest tumor coverage, requiring higher heat output from MIONs than was required for the other distributions studied. The results of the sensitivity analysis revealed that the predicted tumor temperature increased with LVD across all tested SLP values. Additionally, we observed that the minimum acceptable LVD increased with SLP.

Conclusion

Current (preclinical small animal) MPI scanners provide sufficient spatial resolution to predict temperature to within ±1 [°C], and thermal dose coverage to within ±5 [%] for MION formulations having heat output SLP = <370 [W/g Fe]. Higher spatial resolution is needed to achieve a similar precision when MION SLP exceeds 370 [W/g Fe]. We also conclude from the results that assuming a uniform MION distribution in tissue, which has been a common practice in MNPH simulations, overestimates the SLP needed to deposit meaningful thermal dose.

Recent advancements and clinical aspects of engineered iron oxide nanoplatforms for magnetic hyperthermia-induced cancer therapy

The pervasiveness of cancer is a global health concern posing a major threat in terms of mortality and incidence rates. Magnetic hyperthermia (MHT) employing biocompatible magnetic nanoparticles (MNPs) ensuring selective attachment to target sites, better colloidal stability and conserving nearby healthy tissues has garnered widespread acceptance as a promising clinical treatment for cancer cell death. In this direction, multifunctional iron oxide nanoparticles (IONPs) are of significant interest for improved cancer care due to finite size effect associated with inherent magnetic properties. This review offers a comprehensive perception of IONPs-mediated MHT from fundamentals to clinical translation, by elucidating the underlying mechanism of heat generation and the related influential factors. Biological mechanisms underlying MHT-mediated cancer cell death such as reactive oxygen species generation and lysosomal membrane permeabilization have been discussed in this review. Recent advances in biological interactions (in vitro and in vivo) of IONPs and their translation to clinical MHT applications are briefed. New frontiers and prospects of promising combination cancer therapies such as MHT with photothermal therapy, cancer starvation therapy and sonodynamic therapy are presented in detail. Finally, this review concludes by addressing current crucial challenges and proposing possible solutions to achieve clinical success.

In Silico Approach to Model Heat Distribution of Magnetic Hyperthermia in the Tumoral and Healthy Vascular Network Using Tumor-on-a-Chip to Evaluate Effective Therapy

Glioblastoma multiforme (GBM) is the most severe form of brain cancer in adults, characterized by its complex vascular network that contributes to resistance to conventional therapies. Thermal therapies, such as magnetic hyperthermia (MHT), emerge as promising alternatives, using heat to selectively target tumor cells while minimizing damage to healthy tissues. The organ-on-a-chip can replicate this complex vascular network of GBM, allowing for detailed investigations of heat dissipation in MHT, while computational simulations refine treatment parameters. In this in silico study, tumor-on-a-chip models were used to optimize MHT therapy by comparing heat dissipation in normal and abnormal vascular networks, considering geometries, flow rates, and concentrations of magnetic nanoparticles (MNPs). In the high vascular complexity model, the maximum velocity was 19 times lower than in the normal vasculature model and 4 times lower than in the low-complexity tumor model, highlighting the influence of vascular complexity on velocity and temperature distribution. The MHT simulation showed greater heat intensity in the central region, with a flow rate of 1 µL/min and 0.5 mg/mL of MNPs being the best conditions to achieve the therapeutic temperature. The complex vasculature model had the lowest heat dissipation, reaching 44.15 °C, compared to 42.01 °C in the low-complexity model and 37.80 °C in the normal model. These results show that greater vascular complexity improves heat retention, making it essential to consider this heterogeneity to optimize MHT treatment. Therefore, for an efficient MHT process, it is necessary to simulate ideal blood flow and MNP conditions to ensure heat retention at the tumor site, considering its irregular vascularization and heat dissipation for effective destruction.

Model predictive control (MPC) applied to a simplified model, magnetic nanoparticle hyperthermia (MNPH) treatment process

Magnetic nanoparticle hyperthermia (MNPH) has emerged as a promising cancer treatment that complements conventional ionizing radiation and chemotherapy. MNPH involves injecting iron-oxide nanoparticles into the tumor and exposing it to an alternating magnetic field (AMF). Iron oxide nanoparticles produce heat when exposed to radiofrequency AMF due to hysteresis loss. Minimizing the non-specific heating in human tissues caused by exposure to AMF is crucial. A pulse-width-modulated AMF has been shown to minimize eddy-current heating in superficial tissues. This project developed a control strategy based on a simplified mathematical model in MATLAB SIMULINK®to minimize eddy current heating while maintaining a therapeutic temperature in the tumor. A minimum tumor temperature of 43 [°C] is required for at least 30 [min] for effective hyperthermia, while maintaining the surrounding healthy tissues below 39 [°C]. A model predictive control (MPC) algorithm was used to reach the target temperature within approximately 100 [s]. As a constrained MPC approach, a maximum AMF amplitude of 36 [kA/m] and increment of 5 [kA/m/s] were applied. MPC utilized the AMF amplitude as an input and incorporated the open-loop response of the eddy current heating in its dynamic matrix. A conventional proportional integral (PI) controller was implemented and compared with the MPC performance. The results showed that MPC had a faster response (30 [s]) with minimal overshoot (1.4 [%]) than PI controller (115 [s] and 5.7 [%]) response. In addition, the MPC method performed better than the structured PI controller in its ability to handle constraints and changes in process parameters.

Magnetically Enhanced Intracellular Uptake of Superparamagnetic Iron Oxide Nanoparticles for Antitumor Therapy

Superparamagnetic iron oxide nanoparticles (SPIONs) have been widely employed in biomedical fields, including targeted delivery of antitumor therapy. Conventional magnetic tumor targeting has used simple static magnetic fields (SMFs), which cause SPIONs to linearly aggregate into a long chain-like shape. Such agglomeration greatly hinders the intracellular targeting of SPIONs into tumors, thus reducing the therapeutic efficacy. In this study, we investigated the enhancement of the intracellular uptake of SPIONs through the application of rotating magnetic fields (RMFs). Based on the physical principles of SPION chain disassembly, we investigated physical parameters to predict the chain length favorable for intracellular uptake. Our prediction was validated by clear visualization of the intracellular distributions of SPIONs in tumor cells at both cellular and three-dimensional microtissue levels. To identify the potential therapeutic effects of enhanced intracellular uptake, magnetic hyperthermia as antitumor therapy was investigated under varying conditions of magnetic hyperthermia and RMFs. The results showed that enhanced intracellular uptake reduced magnetic hyperthermia time and strength as well as particle concentration. The proposed method will be useful in the development of techniques to determine the optimized physical conditions for the enhanced intracellular uptake of SPIONs in antitumor therapy.

A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice

Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that can form both structural and functional connections with an organotypic hippocampal slice (OHS) is assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicate that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells are significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays shows that the delivered Mag-Neurobot is functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.

Validation of a Temperature-Feedback Controlled Automated Magnetic Hyperthermia Therapy Device

We present in vivo validation of an automated magnetic hyperthermia therapy (MHT) device that uses real-time temperature input measured at the target to control tissue heating. MHT is a thermal therapy that uses heat generated by magnetic materials exposed to an alternating magnetic field. For temperature monitoring, we integrated a commercial fiber optic temperature probe containing four gallium arsenide (GaAs) temperature sensors. The controller device used temperature from the sensors as input to manage power to the magnetic field applicator. We developed a robust, multi-objective, proportional-integral-derivative (PID) algorithm to control the target thermal dose by modulating power delivered to the magnetic field applicator. The magnetic field applicator was a 20 cm diameter Maxwell-type induction coil powered by a 120 kW induction heating power supply operating at 160 kHz. Finite element (FE) simulations were performed to determine values of the PID gain factors prior to verification and validation trials. Ex vivo verification and validation were conducted in gel phantoms and sectioned bovine liver, respectively. In vivo validation of the controller was achieved in a canine research subject following infusion of magnetic nanoparticles (MNPs) into the brain. In all cases, performance matched controller design criteria, while also achieving a thermal dose measured as cumulative equivalent minutes at 43 °C (CEM43) 60 ± 5 min within 30 min.

Design of a temperature-feedback controlled automated magnetic hyperthermia therapy device

Introduction

Magnetic hyperthermia therapy (MHT) is a minimally invasive adjuvant therapy capable of damaging tumors using magnetic nanoparticles exposed radiofrequency alternating magnetic fields. One of the challenges of MHT is thermal dose control and excessive heating in superficial tissues from off target eddy current heating.

Methods

We report the development of a control system to maintain target temperature during MHT with an automatic safety shutoff feature in adherence to FDA Design Control Guidance. A proportional-integral-derivative (PID) control algorithm was designed and implemented in NI LabVIEW^®. A standard reference material copper wire was used as the heat source to verify the controller performance in gel phantom experiments. Coupled electromagnetic thermal finite element analysis simulations were used to identify the initial controller gains.

Results

Results showed that the PID controller successfully achieved the target temperature control despite significant perturbations.

Discussion and Conclusion

Feasibility of PID control algorithm to improve efficacy and safety of MHT was demonstrated.

Current Challenges in Image-Guided Magnetic Hyperthermia Therapy for Liver Cancer

For patients diagnosed with advanced and unresectable hepatocellular carcinoma (HCC), liver transplantation remains the best option to extend life. Challenges with organ supply often preclude liver transplantation, making palliative non-surgical options the default front-line treatments for many patients. Even with imaging guidance, success following treatment remains inconsistent and below expectations, so new approaches are needed. Imaging-guided thermal therapy interventions have emerged as attractive procedures that offer individualized tumor targeting with the potential for the selective targeting of tumor nodules without impairing liver function. Furthermore, imaging-guided thermal therapy with added standard-of-care chemotherapies targeted to the liver tumor can directly reduce the overall dose and limit toxicities commonly seen with systemic administration. Effectiveness of non-ablative thermal therapy (hyperthermia) depends on the achieved thermal dose, defined as time-at-temperature, and leads to molecular dysfunction, cellular disruption, and eventual tissue destruction with vascular collapse. Hyperthermia therapy requires controlled heat transfer to the target either by in situ generation of the energy or its on-target conversion from an external radiative source. Magnetic hyperthermia (MHT) is a nanotechnology-based thermal therapy that exploits energy dissipation (heat) from the forced magnetic hysteresis of a magnetic colloid. MHT with magnetic nanoparticles (MNPs) and alternating magnetic fields (AMFs) requires the targeted deposition of MNPs into the tumor, followed by exposure of the region to an AMF. Emerging modalities such as magnetic particle imaging (MPI) offer additional prospects to develop fully integrated (theranostic) systems that are capable of providing diagnostic imaging, treatment planning, therapy execution, and post-treatment follow-up on a single platform. In this review, we focus on recent advances in image-guided MHT applications specific to liver cancer.