Multiscale modelling of nanoparticle distribution in a realistic tumour geometry following local injection
File(s)cancers-14-05729-v2.pdf (3.76 MB)
Published version
Author(s)
Caddy, George
Stebbing, Justin
Wakefield, Gareth
Adair, Megan
Xu, Xiao Yun
Type
Journal Article
Abstract
Radiosensitizers have proven to be an effective method of improving radiotherapy outcomes, with the distribution of particles being a crucial element to delivering optimal treatment outcomes due to the short range of effect of these particles. Here we present a computational model for the transport of nanoparticles within the tumour, whereby the fluid velocity and particle deposition are obtained and used as input into the convection-diffusion equation to calculate the spatio-temporal concentration of the nanoparticles. The effect of particle surface charge and injection locations on the distribution of nanoparticle concentration within the interstitial fluid and deposited onto cell surfaces is assessed. The computational results demonstrate that negatively charged particles can achieve a more uniform distribution throughout the tumour as compared to uncharged or positively charged particles, with particle volume within the fluid being 100% of tumour volume and deposited particle volume 44.5%. In addition, varying the injection location from the end to the middle of the tumour caused a reduction in particle volume of almost 20% for negatively charged particles. In conclusion, radiosensitizing particles should be negatively charged to maximise their spread and penetration within the tumour. Choosing an appropriate injection location can further improve the distribution of these particles.
Date Issued
2022-11-22
Date Acceptance
2022-11-14
Citation
Cancers, 2022, 14 (23)
ISSN
2072-6694
Publisher
MDPI AG
Journal / Book Title
Cancers
Volume
14
Issue
23
Copyright Statement
© 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
License URL
Publication Status
Published
Article Number
ARTN 5729