SU-D-16A-02: A Novel Methodology for Accurate, Semi-Automated Delineation of Oral Mucosa for Radiation Therapy Dose-Response Studies




The significant morbidity caused by radiation-induced acute oral mucositis means that studies aiming to elucidate dose-response relationships in this tissue are a high priority. However, there is currently no standardized method for delineating the mucosal structures within the oral cavity. This report describes the development of a methodology to delineate the oral mucosa accurately on CT scans in a semi-automated manner.


An oral mucosa atlas for automated segmentation was constructed using the RayStation Atlas-Based Segmentation (ABS) module. A radiation oncologist manually delineated the full surface of the oral mucosa on a planning CT scan of a patient receiving radiotherapy (RT) to the head and neck region. A 3mm fixed annulus was added to incorporate the mucosal wall thickness. This structure was saved as an atlas template. ABS followed by model-based segmentation was performed on four further patients sequentially, adding each patient to the atlas. Manual editing of the automatically segmented structure was performed. A dose comparison between these contours and previously used oral cavity volume contours was performed.


The new approach was successful in delineating the mucosa, as assessed by an experienced radiation oncologist, when applied to a new series of patients receiving head and neck RT. Reductions in the mean doses obtained when using the new delineation approach, compared with the previously used technique, were demonstrated for all patients (median: 36.0%, range: 25.6% – 39.6%) and were of a magnitude that might be expected to be clinically significant. Differences in the maximum dose that might reasonably be expected to be clinically significant were observed for two patients.


The method developed provides a means of obtaining the dose distribution delivered to the oral mucosa more accurately than has previously been achieved. This will enable the acquisition of high quality dosimetric data for use in dose-response studies.

We would like to thank the Engineering and Physical Sciences Research Council for funding. We acknowledge support from the NIHR RM/ICR Biomedical Research Centre. RayStatation was used under an evaluation agreement with RaySearch Laboratories AB.