Medical Physics Department, School of Medicine, Iran University of Medical Sciences (IUMS), Tehran, Iran.
General, Organic and Biomedical Chemistry, NMR and Molecular Imaging Laboratory, University of Mons, Mons, Belgium.
J Photochem Photobiol B. 2019 Oct;199:111599. doi: 10.1016/j.jphotobiol.2019.111599. Epub 2019 Aug 22.
Despite the immense benefits of nanoparticle-assisted photothermal therapy (NPTT) in cancer treatment, the limited method and device for detecting temperature during heat operation significantly hinder its overall progress. Development of a pre-treatment planning tool for prediction of temperature distribution would greatly improve the accuracy and safety of heat delivery during NPTT. Reliable simulation of NPTT highly relies on accurate geometrical model description of tumor and determining the spatial location of nanoparticles within the tissue. The aim of this study is to develop a computational modeling method for simulation of NPTT by exploiting the theranostic potential of iron oxide‑gold hybrid nanoparticles (IO@Au) that enable NPTT under magnetic resonance imaging (MRI) guidance. To this end, CT26 colon tumor-bearing mice were injected with IO@Au nanohybrid and underwent MR imaging. The geometrical model description of tumor and nanoparticle distribution map were obtained from MR image of the tumor and involved in finite element simulation of heat transfer process. The experimental measurement of tumor temperature confirmed the validity of the model to predict temperature distribution. The constructed model can help to predict temperature distribution during NPTT and then allows to optimize the heating protocol by adjusting the treatment parameters prior to the actual treatment operation.
尽管纳米颗粒辅助光热疗法（NPTT）在癌症治疗中具有巨大的益处，但在热疗过程中用于检测温度的有限方法和设备极大地阻碍了其整体进展。开发用于预测温度分布的预处理规划工具将极大地提高 NPTT 过程中热传递的准确性和安全性。NPTT 的可靠模拟高度依赖于肿瘤的精确几何模型描述和组织内纳米颗粒的空间位置确定。本研究旨在通过利用氧化铁-金杂化纳米颗粒（IO@Au）的治疗潜力开发用于 NPTT 模拟的计算建模方法，使 NPTT 能够在磁共振成像（MRI）引导下进行。为此，将 IO@Au 纳米杂化物注射到携带 CT26 结肠肿瘤的小鼠中，并进行 MRI 检查。从肿瘤的 MRI 中获得肿瘤的几何模型描述和纳米颗粒分布图，并将其用于传热过程的有限元模拟。肿瘤温度的实验测量证实了模型预测温度分布的有效性。所构建的模型可以帮助预测 NPTT 过程中的温度分布，然后可以通过在实际治疗操作之前调整治疗参数来优化加热方案。
