ESTRO 2020 Abstract book
S141 ESTRO 2020
Fig.2 DVH for the TG119 phantom, prostate, brain and liver patients. Results are displayed for B = 0T (solid lines) and B = 1T (dashed lines). Conclusion The in-house developed PB model implemented in the research TPS matRad provides highly accurate dose distributions for protons in transverse magnetic fields for homogenous phantoms and exemplary treatments. More complex benchmarking studies are foreseen to identify the limits of applicability of the proposed model. Sunday 5 April 2020 Day 2 SP-0245 How can Artificial Intelligence improve contouring W. Van Elmpt 1 1 Maastricht University, Department of Radiation Oncology, Maastricht, The Netherlands Abstract text Artificial Intelligence based solutions are becoming more wide-spread in many domains including health care. Contouring of organs-at-risk (and in a later stage also tumours) is a well-defined task that is perfectly suited for artificial intelligence techniques. The methods commonly applied for auto segmentation are based on deep-learning / convolutional neural networks based on large amount of pre-contoured clinical cases taken from clinical practice. Various in-house developed and commercial solutions are currently implemented in clinical practice in a growing number of clinics. This teaching lecture will focus on the various aspects of artificial intelligence for auto-contouring: from the basic technology and methods used, towards the clinical implementation (training, (big) data-sets and commissioning), QA and validation of the results in routine practice. SP-0246 How does radiotherapy change the tumor ecosystem? F. Paris 1 1 inserm- Cancer Research Centre Umr1232, Department Of Oncology, Nantes, France Abstract text Ecological ecosystem is characterized by a community of living organisms in conjunction with the non-living components of their environment, interacting as a homeostatic system. In this sense, tumour mass including cancer cells, supporting cells from the host (fibroblasts or endothelial cells or mesenchymal cells), immune cells and extracellular matrix should be viewed as an ecosystem. Indeed, the dialogue that exists between those different compounds plays a major role in processes such as survival, tumour progression and resistance to treatment. Such as in nature, tumour ecosystems are temporally dynamic, subject to disturbances and should adapt from those disturbance to ensure the survival and growth of cancer. This concept of ecosystem’s perturbance can match up with the deleterious effect of radiotherapy by altering the Teaching Lecture: How can Artificial Intelligence improve contouring? Teaching Lecture: How does radiotherapy change the tumour ecosystem
homeostasis of the different cells from the microenvironment. As example, radiation-induced vascular remodeling or arrival of proinflammatory immune cells, might acutely limit tumour growth, but also enhance later its aggressiveness This lecture proposes to overview the concept of the radiation perturbance of tumour ecosystem with a special focus of the long-term consequence of radiation-induced cellular aging.
Teaching Lecture: Oligometastatic cancer scenarios: from biology to treatments
SP-0247 Oligometastatic cancer scenarios: from biology to treatments M. Nowee 1 1 netherlands Cancer Institute, Department Of Radiation Oncology, Amsterdam, The Netherlands Abstract text Until recently, patients with metastatic disease were typically treated with palliative intent either with systemic therapy or best supportive care. However, since evidence of the existence of an oligometastatic disease state is increasing, this has changed. The concept of oligometastatic disease was first proposed in 1995 when Hellman and Weichselbaum hypothesized that there is an intermediate state between a localized tumour and widely spread metastatic lesions. Patients with oligometastatic disease have only one or a limited number of metastatic lesions. Due to the assumed different nature of this disease, they suggested that oligometastases should be treated with local therapy. Clinically, there are different definitions of oligometastatic disease and different local treatment options are explored. Initially, local aggressive treatment was studied in oligometastases treated with surgery. For patients with colorectal cancer and one or a limited number of liver metastases, resection showed improved overall survival. With the increasing use of SBRT, a potentially very effective radiotherapy technique for oligometastatic disease has evolved. However, although side effects are often reasonably manageable, the risk of serious toxicity is not negligible. Most clinical data on oligometastatic disease are based on single center, retrospective series of patients. Few randomized phase 2 trials showed that local aggressive treatment can postpone toxic systemic or hormonal treatment and improve progression free survival compared to patients receiving maintenance treatment or active surveillance. Some phase 2 RCTs also showed improved overall survival by local aggressive treatment in an oligometastatic disease setting. The biology of oligometastases is however, poorly understood. And until today, we are not able to identify true oligometastases from microscopic polymetastases before the start of treatment. In order to better identify patients that truly benefit from local aggressive treatment and to aim for a personalized approach for oligometastatic disease, we need a better understanding of the biology and search for biomarkers to predict outcome. In this lecture, clinical evidence for the existence of oligometastases and knowledge on the biology will be reviewed, and treatment options discussed. Moreover, outcome data of SBRT treatment for oligometastases will
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