Impact of different infusion rates on mass diffusion and treatment temperature field during magnetic hyperthermia

In a magnetic hyperthermia treatment, malignant cells are ablated by the heat produced by power dissipation of magnetic nanoparticles (MNPs) under an alternating magnetic field. MNPs need to be placed inside the tumor region and a prominent method for doing this is to inject magnetic fluid directly into tumor. When this alternative is used, the efficiency of a magnetic hyperthermia treatment depends on factors such as the infusion rate and diffusion duration, since they affect the shape of MNP distribution inside tumor, which affects the temperature distribution during treatment. This paper analyzes the impact of different shapes of MNP distribution, caused by different infusion rates, on mass diffusion and treatment temperature field during magnetic hyperthermia. Three different shapes of MNP distribution were assumed based on images of experiments presented in literature, which used an agarose gel with different concentrations to represent different tissues. In addition, the distribution for a very low infusion rate, obtained from a model proposed in this paper, is used for comparison purposes. A proposed geometric model is used to numerically evaluate the impact of injection and diffusion parameters on a liver tumor considering the four different shapes of MNPs produced by different infusion rates. The simulation results demonstrate that the longer the diffusion duration and the larger the infusion rate are, the better the therapeutic effects are when a proper power dissipation of MNPs is used to control the maximum temperature reached during hyperthermia. To further improve the effective therapeutic area inside tumor, two alternative methods are also evaluated using the model proposed in this paper: multi-site injection and low Curie temperature MNPs. The results show that both of them can significantly improve the tumor area which is subjected to the therapeutic temperature, especially the latter one. (C) 2018 Elsevier Ltd. All rights reserved.