Nikou, Poppy;
Thompson, Anna;
Nisbet, Andrew;
Gulliford, Sarah;
McClelland, Jamie R;
(2024)
Modelling systematic anatomical uncertainties of head and neck cancer patients during fractionated radiotherapy treatment.
Physics in Medicine & Biology
10.1088/1361-6560/ad611b.
(In press).
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Abstract
Head and neck cancer patients experience systematic anatomical changes as well as random day to day anatomical changes during fractionated radiotherapy treatment. Modelling the expected systematic anatomical changes could aid in creating treatment plans which are more robust against such changes. A patient specific (SM) and population average (AM) model are presented which are able to capture the systematic anatomical changes of some head and neck cancer patients over the course of radiotherapy treatment. 
Inter- patient correspondence aligned all patients to a model space. Intra- patient correspondence between each planning CT scan and on treatment cone beam CT scans was obtained using diffeomorphic deformable image registration. The stationary velocity fields were then used to develop B-Spline based SMs and AMs. The models were evaluated geometrically and dosimetrically. A leave-one-out method was used to compare the training and testing accuracy of the models. 
Both SMs and AMs were able to capture systematic changes. The average surface distance between the registration propagated contours and the contours generated by the SM was less than 2mm, showing that the SM are able to capture the anatomical changes which a patient experiences during the course of radiotherapy. The testing accuracy was lower than the training accuracy of the SM, suggesting that the model overfits to the limited data available and therefore also captures some of the random day to day changes. For most patients the AMs were a better estimate of the anatomical changes than assuming there were no changes, but the AMs could not capture the variability in the anatomical changes seen in all patients. No difference was seen in the training and testing accuracy of the AMs. These observations were highlighted in both the geometric and dosimetric evaluations and comparisons. The large patient variability highlights the need for more complex, capable population models.
| Type: | Article |
|---|---|
| Title: | Modelling systematic anatomical uncertainties of head and neck cancer patients during fractionated radiotherapy treatment |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/1361-6560/ad611b |
| Publisher version: | http://doi.org/10.1088/1361-6560/ad611b |
| Language: | English |
| Additional information: | As the Version of Record of this article is going to be / has been published on a gold open access basis under a CC BY 4.0 licence, this Accepted Manuscript is available for reuse under a CC BY 4.0 licence immediately. Everyone is permitted to use all or part of the original content in this article, provided that they adhere to all the terms of the licence https://creativecommons.org/licences/by/4.0 Although reasonable endeavours have been taken to obtain all necessary permissions from third parties to include their copyrighted content within this article, their full citation and copyright line may not be present in this Accepted Manuscript version. Before using any content from this article, please refer to the Version of Record on IOPscience once published for full citation and copyright details, as permissions may be required. All third party content is fully copyright protected and is not published on a gold open access basis under a CC BY licence, unless that is specifically stated in the figure caption in the Version of Record. |
| Keywords: | Head and neck cancer, image registration, proton therapy treatment planning, robust treatment planning, statistical population model |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10194803 |
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