论文标题
估计磁性高温的复合纳米颗粒聚集体的加热
Estimating the heating of complex nanoparticle aggregates for magnetic hyperthermia
论文作者
论文摘要
理解和预测磁性纳米颗粒释放的热量是磁性高温治疗计划的核心。当注入活组织中时，这些纳米颗粒倾向于形成聚集体，从而改变它们对应用的交替磁场的反应，并防止准确预测释放的热量。我们进行了一项计算机分析，以研究具有不同大小和分形几何因子的纳米颗粒聚集体释放的热量。通过在生物组织中看到的数字反映聚集体，我们发现，每个粒子的平均热量从中等小的聚集体开始稳定，从而促进了其较大对应物的估计值。此外，我们研究了粒子聚集体在各种分形参数上的加热性能。我们将该结果与非相互作用纳米颗粒释放的热量进行了比较，以量化被灌输到组织中后的加热能力的降低。这组结果可用于根据实验确定的纳米颗粒特性来估计体内预期的加热。
Understanding and predicting the heat released by magnetic nanoparticles is central to magnetic hyperthermia treatment planning. These nanoparticles tend to form aggregates when injected in living tissues, which alters their response to the applied alternating magnetic field and prevents predicting the released heat accurately. We performed an in silico analysis to investigate the heat released by nanoparticle aggregates featuring different size 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, facilitating the 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.
