Nikou, Poppy; (2025) Modelling progressive anatomical changes of head and neck cancer patients during radiotherapy for robust proton therapy treatment planning. Doctoral thesis (Ph.D), UCL (University College London).

Text Thesis_Corrections.pdf - Accepted Version Access restricted to UCL open access staff until 1 January 2026. Download (82MB)

Abstract

Anatomical changes during fractionated radiotherapy can lead to a difference in the delivered dose distribution from the planned dose distribution. Robust optimisation techniques could be used to create treatment plans that are robust against anatomical changes. To achieve this, patients' anatomical changes must be known in advance. Head and neck cancer patients have been reported to experience systematic and progressive anatomical changes during fractionated radiotherapy. This thesis presents the development of both patient-specific and population models that attempt to capture these changes. The models are built on irregular CBCT imaging data, and use a rigorous mathematical framework based on stationary velocity fields. The population models predict the most likely as well as likely trajectories of anatomical change for a specific patient, prior to treatment. Robust optimisation against likely systematic anatomical changes is a novel methodology in proton treatment planning. Determining the best parameters for the optimisation is a complex research question that would require many treatment plans to be made. To reduce the workload associated with producing multiple treatment plans, a method of automating treatment planning was developed. For a single case study, the population models were used to predict possible anatomical changes that a patient might experience. Each prediction was used as an uncertainty scenario in a robustly optimised treatment plan. The results of this study showed that the optimisation provides increased target coverage across treatment and delays the need for replanning. While a larger cohort of patients is needed to validate these results, this proof of principle study has demonstrated the potential clinical utility of the models developed in this thesis.

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