Zhang, Ying;
McGowan Holloway, Stacey;
Wilson, Megan Zöe;
Alshaikhi, Jailan;
Tan, Wenyong;
Royle, Gary J;
Bär, Esther;
(2022)
DIR-based models to predict weekly anatomical changes in head and neck cancer proton therapy.
Physics in Medicine & Biology
10.1088/1361-6560/ac5fe2.
(In press).
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Abstract
PURPOSE: We proposed two anatomical models for head and neck patients to predict anatomical changes during the course of radiotherapy. METHODS: Deformable Image Registration was used to build two anatomical models: 1) The average model (AM) simulated systematic progression changes across the patient cohort; 2) The refined individual model (RIM) used a patient's CT images acquired during treatment to update the prediction for each individual patient. Planning CTs and weekly CTs were used from 20 nasopharynx patients. This dataset included 15 training patients and 5 test patients. For each test patient, a spot scanning proton plan was created. Models were evaluated using CT number difference, contours, proton spot location deviation and gamma index. RESULTS: If no model was used, the CT number difference between the planning CT and the repeat CT at week 6 of treatment was on average 128.9 HU over the test population. This can be reduced to 115.5 HU using the AM, and to 110.5 HU using the RIM3(RIM, updated at week 3). When the predicted contours from the models were used, the average mean surface distance of parotid glands can be reduced from 1.98 mm (no model) to 1.16 mm (AM) and 1.19 mm (RIM3) at week 6. Using proton spot range, the average anatomical uncertainty over the test population reduced from 4.47±1.23 mm (no model) to 2.41±1.12 mm (AM), and 1.89±0.96 mm (RIM3). Based on the gamma analysis, the average gamma index over the test patients was improved from 93.87±2.48 % (no model) to 96.16±1.84 % (RIM3) at week 6. CONCLUSIONS: The AM and the RIM both demonstrated the ability to predict anatomical changes during the treatment. The RIM can gradually refine the prediction of anatomical changes based on the AM. The proton beam spots provided an accurate and effective way for uncertainty evaluation.
| Type: | Article |
|---|---|
| Title: | DIR-based models to predict weekly anatomical changes in head and neck cancer proton therapy |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/1361-6560/ac5fe2 |
| Publisher version: | https://doi.org/10.1088/1361-6560/ac5fe2 |
| Language: | English |
| Additional information: | © 2022 IOP Publishing. 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 3.0 licence, this Accepted Manuscript is available for reuse under a CC BY 3.0 licence immediately (https://creativecommons.org/licenses/by/3.0/). |
| Keywords: | Anatomical model, proton therapy, uncertainty evaluation |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng UCL > Provost and Vice Provost Offices > UCL BEAMS UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10145964 |
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