Multiscale Modelling of Nanoparticle Distribution in a Realistic Tumour Geometry Following Local Injection.

Area of Science:

• Medical Physics
• Nanotechnology
• Computational Biology

Background:

• Radiotherapy outcomes can be improved using radiosensitizers.
• Effective radiosensitizer delivery relies on precise particle distribution due to their limited range.
• Nanoparticle transport within tumors is critical for targeted radiotherapy.

Purpose of the Study:

• To develop a computational model for nanoparticle transport in tumors.
• To assess the impact of particle surface charge and injection location on nanoparticle distribution.
• To optimize nanoparticle delivery for enhanced radiotherapy.

Main Methods:

• A computational model was developed to simulate nanoparticle transport.
• Fluid velocity and particle deposition were calculated.
• The convection-diffusion equation was used to determine spatio-temporal nanoparticle concentration.
• The effects of particle surface charge and injection site were analyzed.

Main Results:

• Negatively charged nanoparticles achieved more uniform tumor distribution than uncharged or positively charged particles.
• Negatively charged particles occupied 100% of tumor volume in the fluid and 44.5% deposited.
• Moving the injection site from the tumor edge to the middle reduced negatively charged particle volume by nearly 20%.

Conclusions:

• Negatively charged radiosensitizing particles are recommended for maximizing tumor spread and penetration.
• Strategic selection of injection locations can further optimize nanoparticle distribution.
• Computational modeling provides insights for improving nanoparticle-based radiotherapy.