ESTRO 2022 - Abstract Book

S367

Abstract book

ESTRO 2022

Materials and Methods In this prospective Danish phase II study, participants were recruited from Departments of Oncology in Denmark. Eligible patients had locally advanced histologically or cytological proven adenocarcinoma of the pancreas and were medically operable. All patients were aged ≥ 18 years with a performance status of 0-1, with adequate organ function, and had received prior combination chemotherapy (FOLFIRINOX, Gemcitabine/Abraxane, Gemcitabine/Capecitabine or Gemcitabine/S1) for at least 2 months with no sign of progressive disease. Patients were screened, staged and evaluated at the local multi-disciplinary team conference before inclusion in the protocol. A delay of at least two weeks between systemic chemotherapy and SBRT was recommended. The first 6 included patients received intensity-modulated radiotherapy initially on a standard accelerator. Since July 2019, the treatment was given on the MR-linac, where the treatment plan was adapted daily, adjusted for the anatomy of the day (tumor as well as organs at risk (OAR)), to maximize the dose delivered to the tumor and minimize the dose to OAR. The primary endpoint was resection rate for patients starting SBRT. Secondary endpoints were 1-year survival for patients starting SBRT, PFS, OS (time from inclusion to death), adverse events and surgical complications. The cutoff date was 01.10.2021. Results Twenty-seven patients were enrolled between August 2018 and September 2021. The median age was 68 years (range 39- 80), and 70% (n=19) were females. The majority of patients (n=20, 74%) had T4-disease. All 27 patients completed the planned SBRT, and 25 patients received 50 Gray over 5 fractions. Due to OAR and tumor size, 2 patients received 60 Gray over 8 fractions. Twenty-one patients were treated on the MR-Linac. Five patients (19%) have been resected, 2 patients declined surgical exploration. Sixteen patients are still alive. The median overall survival was 19.1 months (95% CI 10.7- 21.2). Overall, the treatment was well tolerated with nausea and abdominal pain as the most common adverse events. Two patients had severe adverse events (1 patient had duodenal perforation after treatment on the standard accelerator, 1 patient experienced upper GI bleeding due to progression of the tumor). Conclusion MR guided adaptive SBRT in patients with locally advanced or borderline pancreatic cancer has shown promising efficacy with acceptable toxicity. A national randomized trial, investigating whether adding SBRT in the treatment course will increase the chance of resection, is being planned. 1 Uppsala University Hospital, Medical Physics, Uppsala, Sweden; 2 Uppsala University, Department of Information Technology, Uppsala, Sweden Purpose or Objective Devices combining MR-scanners and Linacs for radiotherapy, called MR-Linacs, requires contouring on a daily basis to be used to its fullest. Currently, deformable image registration (DIR) algorithms propagate contours from reference scans, however large shape and size changes can be troublesome. Artificial neural network (ANN) based contouring models not relying on DIR algorithms alleviate this issue. However, the requirement of similarity of the training and inference dataset poses an issue with potential highly variable contrast of MR-images, along with patient specific target definition not present in training dataset. To alleviate this problem of scarcity of data, we propose patient specific networks, trained on a single dataset for each patient, for contouring onto the following datasets in a adaptive MR-Linac workflow. Materials and Methods MR-scans from eight prostate patients treated on the MR-Linac (6.1 Gy x 7 fx) at our institution along with contours of Clinical Target Volume (CTV), bladder and rectum were utilized. U-net shaped models were trained based on the image from the first fraction of each patient, and subsequently applied onto the following treatment images. Results were compared with manual contours in terms of the DICE overlap as well as Added Path Length (APL) which correlates with recontouring time. As benchmark, contours propagated through the clinical DIR algorithm were similarly evaluated. OC-0423 Patient specific deep learning contour propagation on prostate magnetic resonance linac patients S. Fransson 1 , D. Tilly 1 , R. Strand 2

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