ESTRO 2023 - Abstract Book

S157

Saturday 13 May

ESTRO 2023

quality and for autocontouring. Further work is needed to improve the generalisability across imaging sequences and validate it for additional structural analysis tasks. [1] https://arxiv.org/abs/1803.01417 MO-0223 Implementation of an MR-Only radiotherapy workflow for CNS: from commissioning to clinical use S. Emin 1 , E. Rossi 2 , G. Gagliardi 1,3 , M. Hedman 2,3 , F. Villegas 1,3 1 Karolinska University Hospital, Medical Radiation Physics and Nuclear Medicine, Stockholm, Sweden; 2 Karolinska University Hospital, Department of Radiation Oncology, Stockholm, Sweden; 3 Karolinska Institute, Department of Oncology-Pathology, Stockholm, Sweden Purpose or Objective Magnetic Resonance (MR) images are widely used alongside computed tomography (CT) images for radiotherapy (RT) planning, introducing geometrical uncertainties due to the image registration process. An MR-only workflow avoids these uncertainties by eliminating the CT step and providing a synthetic CT (sCT) image which is generated directly from MRI. This study describes the clinical implementation process, from commissioning (retrospective study) to validation (prospective study) of the commercial sCT product MRCAT brain (Koninklijke PHILIPS N.V.). The artificial intelligence software is now used clinically in an MR-only workflow designed for glioblastoma patients in our center. Materials and Methods A total of 100 CNS patients were enrolled in the commissioning phase, where a specific sequence was acquired for the generation of the sCT, alongside routine imaging for CT based RT workflow. The contouring capability of the sCT was evaluated by comparing clinical target volumes (CTV) and normal tissue delineated on sCT/MR images versus routine delineation on CT/MR. Dose planning performance was evaluated for 24 glioma patients by dosimetric comparison of relevant DVH points. A set of quality control (QC) guidelines was developed based on the results of the commissioning phase to assess sCT image and dose plan quality. Once in place, 24 glioblastoma grade IV patients were enrolled in the validation phase, receiving treatment with the MR-only workflow. A backup CT simulation was taken in case sCT failed the QC. Retrospective dose comparison between CT and sCT was performed to verify dosimetric agreement seen during the commissioning phase. Results Comparison of CT and sCT based structures yielded a mean Dice coefficient of 0.95 ± 0.02 and 0.93 ± 0.05 for brain and CTV structures respectively. The average Hausdorff distance was calculated to be less than 0.05 mm for both structures. Dosimetric comparison between CT- and sCT-based RT plans showed an average dose difference of 0.60% in the mean dose to CTV, both for the commissioning and validation data. The average difference in the dose to normal tissue was less than 1.90% for the measures shown in figure 1. However, the interpatient variation was larger for the normal tissue compared to the CTV with dose differences up to 8.90% for an individual patient. Bone artefacts were observed in post-operative patients with metal implants, which led to an erroneous thickening of the artefact in the sCT. Dose comparison for cases where the CTV was located adjacent to the metal implant, showed no impact on the mean dose.

Conclusion The dosimetric results obtained in the commissioning and validation process of the commercial sCT product demonstrated that it can be used for RT planning with equal clinical confidence as in CT/MR based workflow. Moreover, the large cohort of patients in the study provided a big enough sample of image artefacts, which in turn facilitated the development of a robust QC program for MR-only workflow. MO-0224 Uncertainty-aware MR-base CT synthesis for robust proton planning of skull-based tumour X. Li 1,2 , R. Belloti 1,3 , G. Meier 1 , D. Weber 4,5,6 , A. Lomax 1,3 , J. Buhmann 2 , Y. Zhang 1 1 Paul Scherrere Institut, Center for Proton Therapy, Villigen, Switzerland; 2 ETH Zurich, Department of Computer Science, Zurich, Switzerland; 3 ETH Zurich, Department of Physics, Zurich, Switzerland; 4 Paul Scherrer Institut, Center for Proton Therapy, Villigen, Switzerland; 5 University Hospital of Zurich, Department of Radiation Oncology, Zurich,