ESTRO 2023 - Abstract Book

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ESTRO 2023

Results Of the thirty-three structures evaluated, ten structures had a DSC above 0.8 and at the same time a HD95 below 3mm (EyeBack_LR, EyeFront_LR, Kidney_LR, Liver, Mandible, SpinalCord, Lung_LR, SpinalCord_C2, SpinalCord_C3 to end, Help_Inner Table Skull). Eight structures had DSC below 0.8 and HD95 above 3 mm (Parotid_LR, Esophagus, Pituitary, Help_Cribriform Plate, Help_ForamenMeck, Help_ForamenRot, Help_JugForamen, Help_OptCanal). The remaining fifteen structures had either a DSC below 0.8 or a HD95 above 3 mm (Cochlea_LR, LacrimalGland_LR, OpticNerve_LR, Heart, Iliac Bones, Thyroid, Lens_LR, SpinalCord_C1, CTV_Spine, Help_ForamenOv, Help_HypoglCanal, Help_IntAudMeat, Help_OpticNerves, Help_SupOrbFiss, Spinal Boes). (Figure 2)

Conclusion With the relative limited training set, of twenty-two patient scans available, we saw a good performance in ten annotations related to brain, eyes, mandible, spinal cord, liver and kidneys while we saw poor prediction quality mainly related to target help structures in the brain. The remaining structure had mediocre prediction quality. Including more patient scans into the training set would very likely improve the inductive bias of the model, but already with the current presented results we can identify relevant structures that are of high, mediocre and poor quality. This can guide us towards where the model requires improvement and in a clinical implementation what segmentations to be more or less trustworthy of.

PO-1640 MRI-based deep learning autocontouring: Evaluation and implementation for brain radiotherapy

N. Alzahrani 1,2 , A. Henry 3 , A. Clark 4 , B. Al-Qaisieh 4 , L. Murray 5 , M. Nix 4

1 Leeds Cancer Center and University of Leeds, Medical Physics and Clinical Engineering, Leeds, United Kingdom; 2 Diagnostic Radiology Department, Faculty of Applied Medical Sciences, King Abdulaziz University,KSA, Diagnostic Radiology , Jeddah,