ESTRO 2023 - Abstract Book

S269

Saturday 13 May

ESTRO 2023

Islands removal was applied as image post-processing. Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95th) were calculated against clinical delineations inside the ground truth rectum extension. The generation time of the segmented volume for each patient was also computed. Results Table 1 reports the DSC and HD95th across the test patients for the two investigated networks. The mean and standard deviation values for the DSC were 0.84 ± 0.04 for 2D and 0.82 ± 0.04 for 3D architecture, while for the HD95th were 8.85 ± 4.13 and 10.36 ± 5.35, respectively. Figure 1 shows an example of the generated contours for both 2D and 3D GANs. As regards the networks’ delineation time, the mean value for the 3D GAN was 1.03 s, while for the 2D GAN was 3.17 s (compared to an average time of up to 1 minute for the manual expert's contouring).

Conclusion As far as the authors know, this is the first attempt to apply 3D GAN on 0.35 T MR images for auto-contouring purposes, with comparison against the corresponding 2D architecture. Quantitative results showed that the networks’ performances are comparable inside the ground truth extension of the rectum, providing a useful tool for the clinician to speed up the delineation during online adaptive MRgRT. Further developments will be implemented to extend these AI-based approaches to other OARs and tumors.