Despite the immense benefits of nanoparticle-assisted photothermal therapy (NPTT) in cancer treatment, the limited method and device for detecting temperature during heat operation significantly hinder its overall progress. Development of a pre-treatment planning tool for prediction of temperature distribution would greatly improve the accuracy and safety of heat delivery during NPTT. Reliable simulation of NPTT highly relies on accurate geometrical model description of tumor and determining the spatial location of nanoparticles within the tissue. The aim of this study is to develop a computational modeling method for simulation of NPTT by exploiting the theranostic potential of iron oxide‑gold hybrid nanoparticles (IO@Au) that enable NPTT under magnetic resonance imaging (MRI) guidance. To this end, CT26 colon tumor-bearing mice were injected with IO@Au nanohybrid and underwent MR imaging. The geometrical model description of tumor and nanoparticle distribution map were obtained from MR image of the tumor and involved in finite element simulation of heat transfer process. The experimental measurement of tumor temperature confirmed the validity of the model to predict temperature distribution. The constructed model can help to predict temperature distribution during NPTT and then allows to optimize the heating protocol by adjusting the treatment parameters prior to the actual treatment operation.
Keywords: Iron oxide-gold nanoparticle; Magnetic resonance imaging; Nano-photothermal therapy; Pre-treatment planning; Temperature distribution.
Copyright © 2019. Published by Elsevier B.V.