S102 ESTRO 36 _______________________________________________________________________________________________ physiological environment than conventional 2D cell cultures. Unfortunately, validation of their suitability to do so and to fit to a particular scientific question is mostly missing. In this teaching lecture I will discuss validation strategies and data of comparative analyses between 2D, 3D and tumor xenografts of various processes such as signal transduction, DNA repair and others. Based on our long-standing experience, a large variety of endpoints can be determined and many methods can be conducted in 3D cell cultures. While this is sometimes not as easy as in 2D and also requires a bit more financial invest, the generated data reflect cell behavior in-vivo and thus have a higher clinically relevance. Further, we are able to address specific tumor features in detail. For example, malignant tumors show great genetic/epigenetic and morphological/cell biological heterogeneity. Another important point is the sparing of animal experiments based on our broad knowledge that human (patho)physiology is significantly different from mice (or other species). Many decades of in-vivo research have demonstrated that only a negligible proportion of therapeutic approaches could be translated from rodents to humans. In conclusion, 3D cell culture models can elegantly support our efforts to gain more knowledge for precision cancer medicine as they present powerful tools for generating more clinically relevant information. A broader implementation of the 3D methodology is likely to underscore our efforts to better understand tumor and normal cell radiation responses and foster identification of most critical cancer targets. Teaching Lecture: Commissioning of dose calculations in brachytherapy TPS
Symposium: New developments Radiation Oncology (PRO)
in
Personalised
SP-0200 Commissioning of dose calculations in brachytherapy TPS J. Steenhuijsen1 1 Catharina Ziekenhuis, Eindhoven, The Netherlands
SP-0201 E-health and Personalised Radiation Oncology: cloud technologies and advanced sensing S. Kyriazakos1 1 Innovation Sprint, Brussels, Belgium
When commissioning a Treatment Planning System for brachytherapy, most attention is given to the accurate calculation of the absolute dose and the dose distribution. The goal of the TPS however is to devise a treatment with an optimal dose distribution to both targets and organs at risk with the use of an applicator or needles. Thus, when commissioning the TPS, not only accurate calculation of the dose distribution has to be established. It is equally important to verify the correctness (size, rotation, order, reconstruction) of the images (CT, MR, US) used and to check the accuracy of (automatic) contouring, the resulting Regions Of Interest, ROImathematics and the Dose Volume Histograms based on these ROIs. The user should also be aware of specific behavior of the planning system (for instance with respect to extremely small volumes or volumes defined on one slice). Also definitions of sources and applicators and accurate reconstruction of applicators have to be verified. On the other hand, the time available to spend on TPScommissioning is limited, so an intelligent choice of tests to has to be made. A prospective risk analysis can help with this choice. The teaching lecture gives an overview on literature on commissioning of TPS for brachytherapy and provides practical methods to check the various parts of the TPS.
eHealth solutions have started in the past decade to attract the attention of several markets, as they support both healthy adults and patients of chronic diseases. However, the level of maturity of eHealth solutions targeting cancer patients is very low. Among the reasons is the highly regulated environment, the cost of the service and the technical challenges to offer accurate, intelligent, personalized applications, respecting the privacy of the patient. In this talk, the best-of-breed of Internet technologies, such as cloud infrastructures, Big Data analytics, advanced sensing and smart applications will be presented and it will be demonstrated how integrated approaches can break the entry barriers, thus improving the daily life and the treatment of cancer patients. SP-0202 Integration and analysis of complex data for Personalised Radiation Oncology A. Dekker1 1 Maastricht Radiation Oncology MAASTRO GROW - School for Oncology and Developmental Biology- University Maastricht, Maastricht, The Netherlands Personalised radiation oncology requires a prediction of the outcome of an individual cancer patient treated with radiation oncology with or without additional treatment modalities. This outcome prediction should include prediction of tumour outcomes (e.g. survival, local control, distant metastasis), toxicity outcomes affecting quality of life (e.g. radiation induced and non-radiation induced toxicities, overall quality of life) and ideally should also predict expected cost, both for the treatment itself and additional societal costs during the lifetime of a patient.