LeBrun Alexander, Ma Ronghui, Zhu Liang
Department of Mechanical Engineering, University of Maryland Baltimore County, Baltimore, MD 21250, United States.
Department of Mechanical Engineering, University of Maryland Baltimore County, Baltimore, MD 21250, United States.
J Therm Biol. 2016 Dec;62(Pt B):129-137. doi: 10.1016/j.jtherbio.2016.06.025. Epub 2016 Jul 7.
OBJECTIVES: The objective is to design heating protocols to completely damage PC3 tumors after a single magnetic nanoparticle hyperthermia session with minimal collateral thermal damage, based on microCT image generated tumor and mouse models. METHODS: Tumor geometries and volumetric heat generation rate distributions that are generated from microCT scans in our previous study are imported into COMSOL 4.3® multiphysics for heat transfer simulations and heating protocol design using the Arrhenius damage model. Then, parametric studies are performed to evaluate how significantly the infusion rate affects the protocol design and its resulted collateral thermal damage. RESULTS: The simulated temperature field in the generated tumor geometry and volumetric heat generation rate distribution are reasonable and correlates well with the amount of the total thermal energy deposited into the tumors. The time needed for complete thermal damage is determined to be approximately 12min or 25min if one uses the Arrhenius integral Ω equal to 1 or 4 as the damage threshold, when the infusion rate is 3μL/min. The heating time increases 26% or 91% in the higher infusion rate groups of 4 or 5μL/min, respectively. Collateral thermal damage to the surrounding tissue is also assessed. Although the two larger infusion rate groups can still cause thermal damage to the entire tumor, the collateral thermal damage would have exceeded the design criterion of 5%, while the assessment criterion is acceptable only in the infusion rate group of 3μL/min. Based on the results of this study, we identify an injection strategy and heating protocols to be implemented in future animal experiments to evaluate treatment efficacy for model validation.
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