Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Inter-fraction motion management and offline adaptive radiotherapy
6029
Poster (digital)
Physics
Characterising anatomical changes of head and neck cancer patients during radiotherapy treatment
Poppy Nikou, United Kingdom
PO-1492

Abstract

Characterising anatomical changes of head and neck cancer patients during radiotherapy treatment
Authors:

Poppy Nikou1, Andrew Nisbet1, Anna Thompson2, Sarah Gulliford3, Jamie McClelland1

1University College London, Department of Medical Physics, London, United Kingdom; 2University College London Hospital, Department of Radiotherapy , London, United Kingdom; 3University College London Hospital, University College London, Department of Radiotherapy Physics, Department of Medical Physics, London, United Kingdom

Show Affiliations
Purpose or Objective

Inter-fractional anatomical changes can lead to uncertainties in the delivered dose distribution. To address this, there is an interest in modelling the anatomical changes which occur over the course of treatment. To inform the choice and complexity of the model, this project aimed to identify and quantify the inter-fractional anatomical changes of head and neck (H&N) cancer patients.

Material and Methods

A cohort of 20 H&N cancer patients treated with IMRT were studied. Each patient had a planning CT (pCT), a rescan CT (rCT) and a series of CBCTs (4-10). A diffeomorphic deformable image registration aligned each CBCT to the pCT. The transformation was used to warp the pCT structures to each CBCT. To test the accuracy of the DIR, two independent geometric validation tests were performed. The warped contours were compared to (1) the rCT contours, (2) contours which were manually delineated on CBCTs. A longitudinal volumetric analysis was performed on each structure. A leave one out cross validation analysis determined the best function to parameterise the changes.

Results

The geometric validation tests showed a good correspondence between the warped and ground truth contours. The average difference in distance was found to be on the order of the thickness of a CT slice (mm). A quadratic function was calculated as the best fit for the changes in parotid gland volume. In comparison, all other structures were best parameterised with a linear fit (high and low dose CTV, body). Structures can therefore be differentiated depending on their rate of volume change during treatment: constant or variable. Figure 1 shows the (a) individual and (b) mean fractional parotid gland volume changes. Figure 2 shows the average volume changes at the end of treatment (day 35), compared to the start of treatment, for all structures. Both figures indicate a broad patient variability within the population, especially in the final parotid gland volumes.




Conclusion

H&N cancer patients are subject to large anatomical changes during fractionated radiotherapy. For most patient structures the volume decreases during treatment. The rate of volume change over treatment however, is structure and patient dependent. Therefore, complex models are needed to account for the patient specific variability.