In Silico Approach to Model Heat Distribution of Magnetic Hyperthermia in the Tumoral and Healthy Vascular Network Using Tumor-on-a-Chip to Evaluate Effective Therapy

Abstract

Glioblastoma multiforme (GBM) is the most severe form of brain cancer in adults, characterized by its complex vascular network that contributes to resistance to conventional therapies. Thermal therapies, such as magnetic hyperthermia (MHT), emerge as promising alternatives, using heat to selectively target tumor cells while minimizing damage to healthy tissues. The organ-on-a-chip can replicate this complex vascular network of GBM, allowing for detailed investigations of heat dissipation in MHT, while computational simulations refine treatment parameters. In this in silico study, tumor-on-a-chip models were used to optimize MHT therapy by comparing heat dissipation in normal and abnormal vascular networks, considering geometries, flow rates, and concentrations of magnetic nanoparticles (MNPs). In the high vascular complexity model, the maximum velocity was 19 times lower than in the normal vasculature model and 4 times lower than in the low-complexity tumor model, highlighting the influence of vascular complexity on velocity and temperature distribution. The MHT simulation showed greater heat intensity in the central region, with a flow rate of 1 µL/min and 0.5 mg/mL of MNPs being the best conditions to achieve the therapeutic temperature. The complex vasculature model had the lowest heat dissipation, reaching 44.15 °C, compared to 42.01 °C in the low-complexity model and 37.80 °C in the normal model. These results show that greater vascular complexity improves heat retention, making it essential to consider this heterogeneity to optimize MHT treatment. Therefore, for an efficient MHT process, it is necessary to simulate ideal blood flow and MNP conditions to ensure heat retention at the tumor site, considering its irregular vascularization and heat dissipation for effective destruction.