Magnetic Particle Imaging-Guided Thermal Simulations for Magnetic Particle Hyperthermia.

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.

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.

HYPER: pre-clinical device for spatially-confined magnetic particle hyperthermia.

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.

MONITORING PERFUSION-BASED CONVECTION IN CANCER TUMOR TISSUE UNDERGOING NANOPARTICLE HEATING BY ANALYZING TEMPERATURE RESPONSES TO TRANSIENT PULSED HEATING.

The dynamic nature of perfusion in living tissues, such as solid tumors during thermal therapy, produces challenging spatiotemporal thermal boundary conditions. Changes in perfusion can manifest as changes in convective heat transfer that influence temperature changes during cyclic heating. Herein, we propose a method to actively monitor changes in local convection (perfusion) in vivo by using a transient thermal pulsing analysis.

Development of a Treatment Planning Framework for Laser Interstitial Thermal Therapy (LITT).

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.