Abstract
This study presents a proof-of-concept for a novel Bayesian inverse method in a one-dimensional setting, aimed at proton beam therapy treatment verification. Our methodology is predicated on a hypothetical scenario wherein strategically positioned sensors detect prompt-𝛾s emitted from a proton beam when it interacts with defined layers of tissue. Using these data, we employ a Bayesian framework to estimate the proton beam’s energy deposition profile. We validate our Bayesian inverse estimations against a closed-form approximation of the Bragg Peak in a uniform medium and a layered lung tumour.
| Original language | English |
|---|---|
| Journal | Proceedings of the Royal Society A |
| Volume | 480 |
| Issue number | 2301 |
| Early online date | 6 Nov 2024 |
| DOIs | |
| Publication status | Published - 6 Nov 2024 |
Data Availability Statement
Code/data available online [28].Acknowledgements
We would like to thank our friends and colleagues who have generously offered their attention, thoughts and encouragement in the course of this work. We thank Colin Baker and Sarah Osman who kickstarted this work.Funding
All authors were supported by the EPSRC programme grant MaThRad EP/W026899/2. Furthermore, A.M.G.C. and A.E.K. are grateful for partial support from EP/P009220/1. T.P. is grateful for partial support from EPSRC (EP/X017206/1, EP/X030067/1) and the Leverhulme Trust (RPG-2021-238).
| Funders | Funder number |
|---|---|
| Faculty of Engineering and Physical Sciences | EP/W026899/2, EP/P009220/1, EP/X017206/1, EP/X030067/1 |
| The Leverhulme Trust | RPG-2021-238 |
