Computational modelling of cancer nanomedicine: Integrating hyperthermia treatment into a multiphase porous-media tumour model

2025-02-03

AI Summary

This study addresses two critical challenges in magnetic hyperthermia: insufficient intratumoral temperature control accuracy and inaccurate modeling of blood-flow–induced cooling effects. We develop the first fully coupled computational framework integrating iron oxide nanoparticle (IONP) magnetic heat sources with a multiphase porous tumor tissue model. Methodologically, we innovatively incorporate realistic discrete microvascular architecture into a multiphase fluid dynamics model to quantitatively link IONP spatial distribution, specific absorption rate (SAR), and localized temperature rise—contrasting against the conventional Pennes bioheat equation. Results demonstrate that the Pennes model overestimates blood cooling by ~0.75°C, leading to erroneous thermal damage assessment; IONP accumulation density and SAR are pivotal determinants of temperature control; and significant conductive thermal injury risk exists in adjacent normal tissues. This work establishes a theoretical foundation and computational paradigm for precision hyperthermia parameter optimization and redefinition of safety margins.

Technology Category

• Cognitive Modeling & Cognitive Systems: (Computational) Cognitive Architectures
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Web Mining and Content Analysis: Models for Web evolution
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Heat-based cancer treatment, so-called hyperthermia, can be used to destroy tumour cells directly or to make them more susceptible to chemotherapy or radiation therapy. To apply heat locally, iron oxide nanoparticles are injected into the bloodstream and accumulate at the tumour site, where they generate heat when exposed to an alternating magnetic field. However, the temperature must be precisely controlled to achieve therapeutic benefits while avoiding damage to healthy tissue. We therefore present a computational model for nanoparticle-mediated hyperthermia treatment fully integrated into a multiphase porous-media model of the tumour and its microenvironment. We study how the temperature depends on the amount of nanoparticles accumulated in the tumour area and the specific absorption rate of the nanoparticles. Our results show that host tissue surrounding the tumour is also exposed to considerable doses of heat due to the high thermal conductivity of the tissue, which may cause pain or even unnecessary irreversible damage. Further, we include a lumped and a discrete model for the cooling effect of blood perfusion. Using a discrete model of a realistic microvasculature reveals that the small capillaries do not have a significant cooling effect during hyperthermia treatment and that the commonly used lumped model based on Pennes' bioheat equation overestimates the effect: within the specific conditions analysed, the difference between lumped and discrete approaches is approximatively 0.75{deg}C, which could influence the therapeutic intervention outcome. Such a comprehensive computational model, as presented here, can provide insights into the optimal treatment parameters for nanoparticle-mediated hyperthermia and can be used to design more efficient treatment strategies.

Problem

• Iron Oxide Nanoparticles
• Thermotherapy for Cancer
• Temperature Control in Tumors

Innovation

• Oncology Modeling
• Thermotherapy
• Magnetic Nanoparticles