Tumor volume largely determines the success of local control of borderline resectable and locally advanced pancreatic cancer with current therapy. We hypothesized that a tumor-mass normalized dose ...

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.

Alternating magnetic field (AMF) tissue interaction models are generally not validated. Our aim was to develop and validate a coupled electromagnetic and thermal model for estimating temperatures i...

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

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.

Purpose: Develop a treatment planning framework for neurosurgeons treating high-grade gliomas with LITT to minimize the learning curve and improve tumor thermal dose coverage. Methods: Deidentified patient images were segmented using the image segmentation software Materialize MIMICS©. Segmented images were imported into the commercial finite element analysis (FEA) software COMSOL Multiphysics© to perform bioheat transfer simulations. The laser probe was modeled as a cylindrical object with radius 0.7 mm and length 100 mm, with a constant beam diameter. A modeled laser probe was placed in the tumor in accordance with patient specific patient magnetic resonance temperature imaging (MRTi) data. The laser energy was modeled as a deposited beam heat source in the FEA software. Penne’s bioheat equation was used to model heat transfer in brain tissue. The cerebrospinal fluid (CSF) was modeled as a solid with convectively enhanced conductivity to capture heat sink effects. In this study, thermal damage-dependent blood perfusion was assessed. Pulsed laser heating was modeled based on patient treatment logs. The stationary heat source and pullback heat source techniques were modeled to compare the calculated tissue damage. The developed bioheat transfer model was compared to MRTi data obtained from a laser log during LITT procedures. The application builder module in COMSOL Multiphysics© was utilized to create a Graphical User Interface (GUI) for the treatment planning framework. Results: Simulations predicted increased thermal damage (10–15%) in the tumor for the pullback heat source approach compared with the stationary heat source. The model-predicted temperature profiles followed trends similar to those of the MRTi data. Simulations predicted partial tissue ablation in tumors proximal to the CSF ventricle. Conclusion: A mobile platform-based GUI for bioheat transfer simulation was developed to aid neurosurgeons in conveniently varying the simulation parameters according to a patient-specific treatment plan. The convective effects of the CSF should be modeled with heat sink effects for accurate LITT treatment planning.