Optimization of thermal dose delivery in magnetic nanoparticle hyperthermia, using novel simulation tools

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Παπαδόπουλος, Κωνσταντίνος
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The present thesis, entitled “Optimization of thermal dose delivery in magnetic nanoparticle hyperthermia, using novel simulation tools”, focuses on the exploitation of simulation tools to optimize different aspects of the multidimensional process of magnetic hyperthermia. These aspects include the optimization of magnetic fields, the experimental evaluation of magnetic fluids’ specific absorption rates, the determination of magnetic properties that lead to efficient nanoparticles for clinical hyperthermia, the prediction of geometrical characteristics associated with these properties, and the calculation of concentration fields that ensure homogenous temperature distributions in magnetically mediated thermotherapy. The relevant theoretical background is provided in an extensive review of the literature, which constitutes Part 1 (Chapters 1-8), and contains state-of-the-art practices, important advances in the field of magnetic hyperthermia, and relevant terminology required to properly introduce the reader to the studied field (Chapters 1-7). From the bibliographic review, challenges and open issues arise, to the solution of which this thesis attempts to contribute (Chapter 8). In Part 2 (Chapters 9-12), the research methodology is deployed. In Chapter 9, the development of numerical models for simulations of magnetic fields generated by induction coils is described. Magnetic field simulations for two commercial systems are validated, and subsequently, a methodology is presented for the optimization and construction of an induction coil designed for an in-house ZVS system. In Chapter 10, simulations are employed in the precise quantification of magnetic fluids’ power density, as well as in the evaluation of calorimetry-based methods typically used for specific absorption rate calculations. In the context of presented measurements three magnetic fluids are compared in terms of heating efficiency. Specific absorption rates of the samples are quantified through different calculation methods and simulations to delineate best practices in data analysis. Beyond the evaluation of conventional methods, simulations are also useful in expansion of quantification capabilities, enabling the prediction of temperature dependent power density functions. In Chapter 11, a theoretical study is conducted using Kinetic Monte Carlo simulations to determine the magnetic properties that deliver optimal heating efficiency in magnetite-based systems. A wide range of nanoparticle sizes and anisotropies are studied to identify efficient combinations under different magnetic field conditions. Obtained combinations are evaluated in terms of different factors that affect heating efficiency including interparticle interactions, thermal energy, and dispersion parameters, to extract conclusions and guidelines on the selection of the optimal magnetic properties. Subsequently, atomistic simulations are employed to determine geometrical specifications that deliver optimal magnetic properties, through shape manipulation. The product of this chapter is a robust methodology to design efficient magnetic nanoparticles. To provide a clinical translation of this thesis’ experimental and theoretical results, in Chapter 12, numerical models are developed to simulate biomedical applications. For the evaluation of magnetic fluids studied in Chapter 10 under biological system conditions, a preclinical study involving thermotherapy of small animal epidermal carcinoma was performed and a corresponding simulation model was developed. The model was based on micro-CT data, which allowed the import of the small animal’s detailed geometry, as well as the precise quantification of nanoparticles’ distribution. For the evaluation of the optimized nanoparticles obtained in Chapter 11 under biological system conditions, a numerical model was developed to simulate prostate cancer thermotherapy based on the anthropomorphic XCAT phantom. In both cases optimization of magnetic hyperthermia treatment planning was carried out by computing nanoparticle concentration fields that yielded homogenous temperature and thermal dose distributions in the region of interest. In Part 3 (Chapters 13-16) of the dissertation, all results of the research are apposed and explained, while in Part 4 (Chapters 17-18), a discussion on results, limitations, and contribution of the research is deployed (Chapter 17). Conclusions (Chapter 18) are extracted on the critical role of simulations in further comprehending nanosystems, as well as in the development of best practices and standardized protocols in magnetic hyperthermia. Finally, prospects for future research are envisioned.
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Magnetic hyperthermia, Magnetic nanoparticle hyperthermia, Magnetic nanoparticles, Magnetic fluid hyperthermia, Simulations, Finite element method, Bioheat transfer, Thermal dose, Optimization algorithms, Kinetic monte carlo simulations, Atomistic simulations, Magnetic fields
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