Heat Transfer Simulation for Optimization and Treatment Planning of Magnetic Hyperthermia Using Magnetic Particle Imaging

TL;DR

This paper presents a heat transfer simulation system using magnetic particle imaging (MPI) to optimize magnetic hyperthermia treatment (MHT), demonstrating high correlation with experimental data and potential for personalized treatment planning.

Contribution

The study develops a novel simulation framework integrating MPI and finite element modeling for precise MHT planning, validated with experimental data.

Findings

High correlation (r=0.956) between MPI pixel value and SAR.

Good agreement between simulated and experimental temperature rise.

Simulation can model temperature distribution under various conditions.

Abstract

This study was undertaken to develop a system for heat transfer simulation for optimization and treatment planning of magnetic hyperthermia treatment (MHT) using magnetic particle imaging (MPI). First, we performed phantom experiments to obtain the regression equation between the MPI pixel value and the specific absorption rate (SAR) of magnetic nanoparticles (MNPs), from which the MPI pixel value was converted to the SAR value in the simulation. Second, we generated the geometries for use in the simulation by processing X-ray computed tomography (CT) and MPI images of tumor-bearing mice injected intratumorally with MNPs (Resovist). The geometries and MPI images were then imported into software based on a finite element method (COMSOL Multiphysics) to compute the time-dependent temperature distribution for 20 min after the start of MHT. There was an excellent correlation between the MPI pixel value and the SAR value (r = 0.956). There was good agreement between the time course of the temperature rise in the tumors obtained by simulation and that obtained experimentally. The time-dependent temperature distributions under various blood perfusion rates in the tumors and at various locations could be simulated, which cannot be easily obtained experimentally. These results suggest that our system for heat transfer simulation using MPI will be useful for the optimization and treatment planning of MHT.