Modelling Uncertainties in Radiation Therapy: The Clinical Impact on Prostate Bed Treatment

Advanced techniques in radiotherapy, including IMRT and VMAT offer methods to deliver highly conformal dose distributions to the target while sparing dose to organs at risk. However, these techniques are highly complex and therefore raise the potential for errors in radiotherapy planning and delivery. This thesis modelled the impact of the uncertainties in contouring and treatment planning on clinical outcomes for prostate bed radiotherapy, using data from the TROG 08.03 Clinical Trial. The first part developed auto-IMRT and auto-VMAT treatment plans without manual interventions to explore the potential of auto-planning as a planning quality assurance tool in clinical trials. This study demonstrated that the auto-planning tool has the potential to provide treatment planning quality assurance to ensure that only high-quality plans are included in clinical trials. The second part investigated correlations between contouring similarity metrics and modelled outcomes, aimed at identifying the clinical meaning of commonly used similarity metrics for prostate bed RT. No strong correlations were found between the considered similarity metrics and modelled outcomes in this work. When the range of the variation of the CTV delineation is smaller than 5mm, its impact on dosimetry can be considered minor. The third part proposed a framework to incorporate the impact of target motion on treatment plans and compared auto-IMRT and auto-VMAT treatment plans for prostate bed RT. The results demonstrated that both auto-IMRT and auto-VMAT plans are robust to inter-fraction motion, and the robustness of auto-IMRT and auto-VMAT are clinically comparable. The final part investigated whether contouring uncertainty or uncertainty due to target motion is the main factor influencing the decision on the magnitude of a planning safety margin. The target motion components were found to play a small role, compared to contour variation, in determining the optimal margin for prostate bed RT. As advances in radiotherapy strive to find key breakthroughs that will significantly improve the quality of care for cancer patients, it is essential to understand the uncertainties associated with radiotherapy planning and delivery. The work presented in this thesis will assist this goal with methods and analysis techniques which could be utilised in future studies.

Grantor dc:publisher

UNSW, Sydney

Year dc:date

2023

Author dc:creator

• Le, Bao Viet

Statement dc:rights

• open access
• CC BY 4.0
• free_to_read

Licence

• https://purl.org/coar/access_right/c_abf2
• https://creativecommons.org/licenses/by/4.0/

Language dc:language

en

Identifier

https://doi.org/10.26190/unsworks/24721

OAI identifier oai:identifier

oai:unsworks.library.unsw.edu.au:1959.4/101014