MRI-based numerical modeling strategy for simulation and treatment planning of nanoparticle-assisted photothermal therapy

• Published in: Physica medica 2019-10, Vol.66, p.124-132
• Main Authors: Asadi, Mohamadreza, Beik, Jaber, Hashemian, Reza, Laurent, Sophie, Farashahi, Ali, Mobini, Mehri, Ghaznavi, Habib, Shakeri-Zadeh, Ali
• Format: Article
• Language: English
• Subjects: Animals; Computational modeling; Computer Simulation; Ferric Compounds - chemistry; Gold - chemistry; Magnetic Resonance Imaging; Metal Nanoparticles; Mice; MRI; Nanomedicine; Nanotechnology; Phototherapy; Photothermal therapy; Radiotherapy Planning, Computer-Assisted - methods; Temperature; Treatment planning
• ISSN: 1120-1797; 1724-191X
• DOI: 10.1016/j.ejmp.2019.10.002

Schematic workflow diagram of the present study. [Display omitted] •Nanoparticle-assisted photothermal therapy (NPTT) is firstly described.•A treatment planning system for NPTT is essential for clinical translation of this modality.•An MRI-based numerical modeling strategy for treatment planning is proposed.•The model was validated in CT26 colon tumors in vivo.•There was a satisfactory agreement between the numerical and experimental results. Nanoparticle-assisted photothermal therapy (NPTT) has recently emerged as a promising alternative to traditional thermal therapy methods. Computational modeling for simulation and treatment planning of NPTT seems to be essential for clinical translation of this modality. Non-invasive identification of nanoparticle distribution within the tissue is a key perquisite for accurate prediction of NPTT in real conditions. In the present study, we have developed a magnetic resonance imaging (MRI)-based numerical modeling strategy for simulation and treatment planning of NPTT. To this end, we have utilized the core-shell γ-Fe2O3@Au nanoparticle comprising a gold layer with plasmonic properties and a magnetic core that enables to track the location of this structure via MRI. The map of nanoparticle distribution in the tumor derived from T2-weighted MR image was imported into a finite element simulation software, and Pennes bioheat equation and Arrhenius damage model were applied to simulate the temperature and damage distributions, respectively. The validation of the model developed herein was assessed by monitoring the superficial and the central temperature variations of the tumor in experiment. Both the numerical modeling and experimental study proved that a localized heating and then a focused damage could be achieved due to nanoparticle inclusion. There is quite satisfactory agreement between the numerical and experimental results. The model developed in this study has a good capability to be used as a promising planning method for NPTT of cancer.