Modelling of Tissue Temperature in Cancer Treatments with Quantum Molecular Resonance

This thesis represents a pioneering contribution in the field of thermal modelling applied to cutting-edge oncological technologies, developed in collaboration with Telea Electronic Engineering S.r.l., patent holder of Quantum Molecular Resonance (QMR) technology. The research is situated within a context of exceptional clinical relevance, in light of recent findings published in the British Journal of Cancer that have documented a selective cytostatic effect of the QMR signal on Glioblastoma Multiforme cells, a deadly cerebral neoplasm with a five-year survival rate below 5%. In order to translate this promising discovery into a safe therapeutic application, controlling tissue heating induced by the Joule effect during QMR signal delivery is fundamental: without precise temperature monitoring, the anti-tumour benefits of QMR treatment would risk being compromised by potential thermal damage to surrounding healthy tissues. The methodological innovation presented addresses this challenge through the creation of a sophisticated lumped-parameter mathematical model that predicts temperature evolution in QMR-treated tissues. This model constitutes an elegant compromise between representational fidelity and computational efficiency, an indispensable quality for implementing advanced thermal control strategies. Beginning with an analysis of bio-heat transfer literature, and following a rigorous scientific approach, progressive model refinement was achieved, integrating: differentiated tissue stratification, electrode-tissue interface modelling, geometric adaptation to experimental scenarios, and advanced calibration through parametric optimisation techniques. Simulations revealed excellent theoretical behaviour of the model, while calibration efforts identified the critical need for improved measurement techniques. Model's computational efficiency renders it ideal for implementing model-based controllers, capable of modulating QMR signal delivery parameters in real-time to maximise anti-tumour effects whilst maintaining safe temperatures. This original contribution thus marks a fundamental advancement for QMR technology applications in oncology, opening perspectives for an innovative therapeutic approach in contexts where effective solutions are currently lacking.