ESTRO 2022 - Abstract Book

S1660

Abstract book

ESTRO 2022

performed. RTTs are responsible for ensuring reproducibility throughout treatment. It is only for the first session that the radiation oncologist validates the fusion. During the treatment process, visible differences in the image fusion occur. The doctor is called when the RTTs see a major difference and assess the need to replan. Materials and Methods Retrospective analysis of the time between the treatment start date and the CT replanning date, as well the analysis of the weight change. Reproduction of the dose distribution on the MVCT of the day before the decision to replan (on Raystation), and analysis of the differences observed in the dose distribution, concerning the coverage of PTVs, the dose on OARs and hot/cold possible areas. New H&N cases that started in a period corresponding to 4 months will be analyzed. Results Of 44 H&N patients, 12 (27%) underwent replanning. The average weight loss is 2.8 kg. The average number of days elapsed between the treatment start date and the replanning CT date is 21 days. On the dose distribution evaluating plans applied on the MVCTs, we observe considerable hot regions at the PTVs level and therefore also at the skin level with an average relative max isodose of 111% and absolute max doses up to 78.91 Gy. Generally, the dose on OARs remains under the dose constraints. On the brachial plexus, we see an increase that exceeds the dose constraints limits, with D1 max at 70.55 Gy in one case. Note that these values correspond to a potentially extreme situation, only if we did not do the replanning. We also see a difference in the volume of the external contour of the patient, especially in the neck region, with a visible decrease in the external contour on the MVCT compared to the initial planning CT. Conclusion This analysis shows the importance of controlling the weight for H&N patients but also of being vigilant to visible differences on image fusion process. RTTs should be aware of the potential dosimetric implications demonstrated in this analysis. The difference observed between the volume of the external contour on the MVCT and the planning CT, we will call it "intersection volume", could give us more information for a future analysis, in particular, from what difference of the "intersection volume” we would have significant differences (PTV with hot areas, doses on OAR excessive compared to the initial distribution) and create an indicator to help in the decision to replan or not the treatment for H&N patients. Purpose or Objective Improvements in radiotherapy techniques and precision has meant there is more demand for delineation accuracy locally. Target volume (TV) delineation is subject to inter-observer variability (IOV) and is a major contributor to uncertainty in radiotherapy planning. Delineation for the TVs and organs at risk (OARs) is a time-consuming process and is primarily done manually. Automated methods can be more efficient and reduce IOV, but its use within radiotherapy is limited. This project aimed to produce an auto-segmentation model to delineate the TVs and OARs for patients receiving radiotherapy to the prostate and evaluate the efficiency and accuracy of using automated delineation methods in the workflow. The OARs and TV were manually delineated on 20 datasets by five radiographers and three clinicians, and the timings were manually recorded. The model was loaded onto the same datasets, and the OARs on 5 cases were manually modified; by 1 radiographer; as required, and the time manually recorded for comparison. Seven radiographers scored OARs for 20 cases using a 1-5 scale; one being completely acceptable, and five completely unacceptable. Comparison metrics, such as DSC were used to evaluate statistical significance, comparing the auto structures to the participants’ and to compare the participants. Results The TVs generated were not acceptable for use in the first version of the model and required additional time to be trained, so they were excluded in the full analysis. Six hundred seventy structures were manually delineated, and 628 times were manually recorded. The overall mean time to complete all structures for a prostate and node patient is 80.4 minutes (33.8 minutes for radiographers and 46.5 minutes for clinicians). The mean time for a radiographer to edit 5 cases was 21.0 minutes, a time-saving of 12.8 minutes. There is a 79% agreement between clinicians, and 86% agreement between the radiographers, and an 83% agreement between the auto and the radiographers. The median scores were 2 for the femoral heads and 3 for the bladder, bowel, and rectum, with two requiring insignificant modification and three minor modification. Conclusion A significant time-saving can be made by using auto-segmentation methods to delineate the structures for prostate patients. Although the model requires refinement, as a first version, it does offer a good starting point for OARs. Training is still required to develop the model so that the TVs are more acceptable, to see a more significant time-saving. Although the model could not create structures that do not require at least some manual editing, a time saving was seen for OARs in this study. The magnitude of this saving is currently limited by the requirement for practitioners to check and modify the structures to ensure they are acceptable for planning. Materials and Methods The model was first created with 150 anonymised prostate datasets. PO-1873 Is auto-segmentation in prostate radiotherapy efficient and accurate? V. Chapman 1 1 Clatterbridge Cancer Centre, Radiotherapy, Liverpool, United Kingdom

PO-1874 Evaluating the use of SGRT in supraclavicular fossa positioning of mastectomy patients.