ESTRO 36 Abstract Book

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Conclusion The E-learning environment Ortello is fully operational. On the Ortello website, RTTs can train their skills, maintain their knowledge, learn newly introduced technologies, and have the opportunity to learn techniques used in other departments. Furthermore, Ortello provides CS with the accreditation points to ensure RTTs continuous competence.

observer registration variation was minimal in the right- left (R-L) direction (mean, 2.8mm, sd 2.4 mm). Overall, on Anova analysis, there were no statistically significant differences in inter-observer registration (p = 0.8214, 0.3136, and 0.3270, in the R-L, A-P and C-C directions respectively). To determine intra-observer variability, each observer performed repeat image registrations on 5 patients at 3 separate time-points. The observers mean reproducibility of ≤ 4mm, 2.5 mm and 5 mm in all directions, respectively (Figure 1). Conclusion Despite the limitations in geometric fidelity of DW MRI, it is a potentially useful tool for the generation of BTV and image registration for adaptive bladder radiotherapy. In this study we quantified the inter-observer variation to <5mm +/- 5mm, in image registration of BTV generated using DW-MRI to planning CT. Current application to clinical practice may necessitate revision of PTV margins but further quantification of geometric distortions and validation is on going. We acknowledge NHS funding to the NIHR Biomedical Research Centre for Cancer and to Cancer Research UK (CRUK). PV-0462 E-learning in the Radiotherapy Department- Ortello J.P. De Jong 1 , P. De Boer 1 , D. Ages 2 , F. Telgenhof 3 , D. Hasken 3 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Radiotherapy, Amsterdam, The Netherlands 2 Leiden University Medical Center, Radiotherapy, Leiden, The Netherlands 3 University Medical Center Utrecht, Radiotherapy, Utrecht, The Netherlands Purpose or Objective In 2006 four Radiation therapy technologist (RTT) heads of Radiation Oncology departments agreed to create an E- learning environment. Their goal was to introduce a learning method for RTTs involved in new radiation techniques for whom the learning environment would be easily accessible, relatively cheap and offer new teaching and learning techniques. Material and Methods From 2006 till 2008 a dedicated group of four RTTs created a web-based environment called “Ortello”. By December 2015 Ortello had been fully revised and updated to current website standards. In 2008 Ortello started with 8 Radiotherapy case studies (CS), 3 games and a multiple- choice test. Radiotherapy was highlighted in these CS, but other treatment modalities, such as surgery and chemotherapy, were also represented. Each CS consists of a patient’s pathway during their cancer treatment. Ortello now contains 21 different E-learning CS, which are categorized in Radiotherapy, Techniques, Imaging, and Radiobiology, coupled to 21 multiple-choice tests to examine the gained knowledge. The e-learning environment is linked to the Dutch Register for Paramedics to automatically register credit points obtained after completing a CS and the corresponding test. Every 2 years, reapplication for accreditation is required to guarantee the quality and relevance of each CS. Results Since it’s introduction, Ortello has gained more than 1100 users in 21 departments; 19 in The Netherlands and 2 in Suriname and Curacao. Each year new CS are launched on the website. Up to now, Ortello contains 11 CS in the category Radiotherapy: prostate-, oropharyngeal-, larynx carcinoma, 2 in the category Technique: ”Photons vs electrons” and ”Teaching & Brachytherapy”, 2 in the category Imaging: MRI and MRI & bone tumors and 3 in the category Radiobiology: Radiobiology, Linac & Radioactivity and Radiotherapy side effects. Currently, Ortello is no longer exclusive for RTTs, but can also be used by Diagnostic radiographers.

Award Lecture: Donal Hollywood Award

OC-0463 In vitro prediction of DNA repair defects reveals association with poor clinical outcome in HNSCC P. Essers 1 , C. Verhagen 1 , M. Van der Heijden 1 , M. Van den Brekel 2 , H. Bartelink 3 , M. Verheij 3 , C. Vens 1 1 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Division of Biological Stress Response, Amsterdam, The Netherlands 2 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Department of Head and Neck Surgery / Department of Maxillofacial Surgery, Amsterdam, The Netherlands 3 Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Department of Radiation Oncology, Amsterdam, The Netherlands Purpose or Objective Recent studies highlight the relevance of DNA repair defects in genome instability and tumour development. Little is known about the impact of DNA repair aberrations on patient prognosis or treatment outcome. However, new targeted treatment options, such as PARP inhibitors, can exploit these repair defects if present. Here we tested whether gene expression analysis could identify DNA repair defects, with the ultimate aim to determine an association with clinical outcome and identify patients for Mitomycin C (MMC) or PARP inhibitor olaparib hypersensitivity is a hallmark of functional homologous recombination (HR) or Fanconi anaemia (FA) pathway DNA repair defects. We determined whole transcriptome expression and sensitivity to MMC and olaparib in a panel of 28 patient derived head and neck squamous cell carcinoma (HNSCC) cell lines. Based on their sensitivity (IC50 values), cell lines were classified as Normal (N) , hypersensitive to both drugs ( MOS ) or hypersensitive to mitomycin C but not olaparib ( MS ). To esta blish a “DNA repair defect” signature, relevant genes were extracted by differential expression analysis and used as input to various machine learning algorithms. Performance was evaluated using 20 repetitions of 5-fold int ernal cross validation. Probabilities of defects calculated by these m odels were used in a multivariate cox proportional hazard model to determine their prognostic capacity in a cohort of 84 HNSCC tumours, treated with chemo-radiation, and the TCGA HNSCC cohort. Results Expression analysis of the three groups yielded genes enriched for targets of transcription factors involved in DNA damage response, including p53, demonstrating its relevance to the system under study. The random forest model performed best, achieving a high sensitivity of 0.91 and specificity of 0.86. We validated our model in the Cancer Genome Project dataset of drug sensitivities in cell lines. The predicted repair defected groups had significantly lower IC50 values for DNA damage inducing agents, including cisplatin (MS: p=5.9e-05; MOS: p=0.042). Encouraged by this data, we used our model in the patient data sets. Increased probabilities of DNA repair defects targeted treatments. Material and Methods