Mathematical modelling of nanoparticle transport through tumours for application in radiotherapy
File(s)
Author(s)
Caddy, George Edward Jaques
Type
Thesis
Abstract
Radio-sensitizing nanoparticles have proven to be an effective method of increasing the damage caused to cancerous cells during the course of radiotherapy. Xerion Healthcare have developed a titania-based nanoparticle that can be directly injected into the tumour, increasing the effectiveness of radiotherapy. Due to the short range of effect of the particles, their distribution within the tumour is an important factor in determining the efficacy of treatment, and at present, there is uncertainty about the exact intratumoural distribution. The overarching aim of this thesis is to develop a computational model for the transport of nanoparticles within tumours, evaluate the factors affecting particle transport and assess the conditions leading to an optimal particle distribution following local injection.
The computational model consists of three sub-models that combine to calculate intratumoural nanoparticle transport. The model can calculate nanoparticle concentration within the injected fluid and deposited onto cells during, and after, local injection. Initially, the model is used to investigate the impact of tumour properties and particle characteristics on nanoparticle distribution. Simulation results from an idealised geometry demonstrate that particle surface charge is an important parameter affecting particle transport within the tumour This result is confirmed in a further study utilising a realistic murine geometry and accurate particle parameters from Xerion. Simulations varying tumour properties also found significant changes in the proportion of particles deposited to those remaining in the injected fluid at the end of injection.
The model is then used to determine the impact of various injection parameters on nanoparticle distribution, in realistic murine and human tumour geometries. The choice of injection location affects the volume of particle spread. Concentration dose, injection amount and injection rate are investigated, their effects on particle distribution are judged by calculations of particle spread volumes and concentration non-uniformity.
The computational model consists of three sub-models that combine to calculate intratumoural nanoparticle transport. The model can calculate nanoparticle concentration within the injected fluid and deposited onto cells during, and after, local injection. Initially, the model is used to investigate the impact of tumour properties and particle characteristics on nanoparticle distribution. Simulation results from an idealised geometry demonstrate that particle surface charge is an important parameter affecting particle transport within the tumour This result is confirmed in a further study utilising a realistic murine geometry and accurate particle parameters from Xerion. Simulations varying tumour properties also found significant changes in the proportion of particles deposited to those remaining in the injected fluid at the end of injection.
The model is then used to determine the impact of various injection parameters on nanoparticle distribution, in realistic murine and human tumour geometries. The choice of injection location affects the volume of particle spread. Concentration dose, injection amount and injection rate are investigated, their effects on particle distribution are judged by calculations of particle spread volumes and concentration non-uniformity.
Version
Open Access
Date Issued
2023-11-14
Date Awarded
2024-03-01
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Xu, Xiao Yun
Sponsor
Engineering and Physical Sciences Research Council
Xerion Healthcare
Grant Number
EP/R513052/1
Publisher Department
Chemical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)