Research
Optimisation research advances adaptive proton therapy planning
On September 10th, Zihang Qiu successfully defended his PhD thesis, "Advancing proton therapy treatment plan optimisation under uncertainties", at the University of Amsterdam. His research develops new ways to use mathematical optimisation to adapt proton therapy plans when a patient’s anatomy or treatment conditions change.
Why is proton therapy an optimisation problem?
Proton therapy is a precise form of radiotherapy used to treat cancer. Treatment planning determines how radiation should be delivered so that the tumour receives the required dose while limiting radiation to surrounding healthy tissue.
That becomes more difficult when a patient’s anatomy changes during treatment or when other uncertainties affect how proton beams are delivered.
What did the research contribute?
Zihang developed optimisation methods designed to make treatment planning more responsive to these uncertainties. His thesis includes approaches for online adaptive treatment planning, where a plan can be re-optimised while the patient is still on the treatment table, a new K-adaptability approach for robust planning under uncertainty, and methods for identifying when replanning would be most useful as a patient’s anatomy changes.
The work was supervised by Prof. Dick den Hertog, Science-to-Impact Director at Analytics for a Better World and Professor at the Amsterdam Business School, and Prof. Thomas Bortfeld of Harvard Medical School and Massachusetts General Hospital. The PhD was funded through RAPTOR – Real-time Adaptive Particle Therapy of Cancer, a Marie Skłodowska-Curie programme focused on advancing real-time adaptive particle therapy.
Discover more of Dr Qiu's work on adaptive cancer radiation plans and proton therapy here.
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