Estimating the heating of complex nanoparticle aggregates for magnetic hyperthermia

Understanding and predicting the heat released by magnetic nanoparticles is central to magnetic hyperthermia treatment planning. In most cases, nanoparticles form aggregates when injected in living tissues, thereby altering their response to the applied alternating magnetic field and preventing the accurate prediction of the released heat. We performed a computational analysis to investigate the heat released by nanoparticle aggregates featuring different sizes and fractal geometry factors. By digitally mirroring aggregates seen in biological tissues, we found that the average heat released per particle stabilizes starting from moderately small aggregates, thereby facilitating making estimates for their larger counterparts. Additionally, we studied the heating performance of particle aggregates over a wide range of fractal parameters. We compared this result with the heat released by non-interacting nanoparticles to quantify the reduction of heating power after being instilled into tissues. This set of results can be used to estimate the expected heating in vivo based on the experimentally determined nanoparticle properties.

Automated summary

Understanding and predicting the heat released by magnetic nanoparticles is crucial for magnetic hyperthermia treatment planning. We conducted a computational analysis to examine the heat released by nanoparticle aggregates with different sizes and fractal geometry factors. Our findings show that the average heat released per particle stabilizes from moderately small aggregates, allowing for estimates of heat release for larger aggregates. We also investigated the heating performance of particle aggregates with various fractal parameters and compared it with non-interacting nanoparticles to quantify the reduction in heating power after injection into tissues.