ESTRO 2022 - Abstract Book

S855

Abstract book

ESTRO 2022

Abstract not available

SP-0983 Accreditation for clinical trials: Dosimetry and audits

C. Clark

United Kingdom Abstract not available

Symposium: Modelling of complex systems and interactions

SP-0984 Prediction of radiotherapy-induced lymphopenia

R. Mohan 1

1 MD Anderson Cancer Center, Radiation Physics, Houston, USA

Abstract Text There is substantial evidence that radiation-induced lymphopenia (RIL) is commonly associated with conventional radiotherapy (3DCRT, IMRT or VMAT). It suppresses the immune system, which adversely impacts survival outcomes of (chemo)radiotherapy (CRT) and increases the risk of infections and normal tissue toxicities. Radiation therapy may also reduce the diversity of the immune system even if it seems to have recovered partially or wholly after CRT as assessed based on total lymphocyte counts. Such diversity is critical for protection against wide array pathogens. There is also increasing evidence that the effectiveness of immunotherapy following CRT, which depends on the wellbeing of the immune system, may be abrogated by RIL. Proton therapy, intensity modulated proton therapy (IMPT) in particular, because of its compact dose distributions (smaller “dose bath”) compared to photon therapy, appears to cause less damage to the immune system. To optimally mitigate immune suppression using dosimetric approaches with IMPT, or even with IMRT, it is essential to understand the dependence of RIL on underlying physical, biological and clinical factors, and develop “personalized” RIL models capable of predicting an individual patient’s risk. Personalized models are likely to be more accurate compared with the one--fits-all models employed in conventional radiotherapy practice that use standard dose-volume constraints. Further improvement in accuracy of models may be achieved with deep learning techniques compared to the traditional statistical techniques. Accurately predicted his/her RIL risk with such models may be among the important considerations for the selection of optimum treatment modality (protons or photons) for each patient. Furthermore, the incorporation of personalized models in the criteria of optimization IMRT or IMPT may allow further mitigation of RIL. Considering the power of IMPT due to the availability of an extra degree of freedom, that of energy, it may have a significant potential to achieve RIL risk reduction without compromising standard constraints on dose to tumor and normal tissues.

SP-0985 Mathematical Modeling of Combined Treatments for Sequencing and Scheduling Optimisation

C. Grassberger 1

1 Harvard Medical School / Massachusetts General Hospital, Radiation Oncology, Boston, USA

Abstract Text Mathematical modeling has played an important role in developing hypotheses to be tested in clinical trials using radiation therapy and for optimizing their design. Especially in the area of accelerated fractionation and hypofractionation, radiobiological models have played a central role in trial design and estimating the therapeutic benefit of different treatment approaches. However, the increasing complexity of treatment regimen and the use of biological agents in combination with radiotherapy have emphad the need for approaches encompassing the entire treatment, not only the radiotherapy. In this talk we will introduce available tools to perform dynamic simulations of blood flow to investigate radiation-induced lymphocyte depletion and its dependence on fractionation and dose rate. Furthermore we will discuss available mathematical frameworks for modeling immunotherapy - radiotherapy combination regimen and resistance development to oncogene-targeted agents.

SP-0986 Modelling (re) oxygenation

I. Toma-Dasu 1

1 Karolinska Institutet and Stockholm University, Medical Radiation Physics, Stockholm, Sweden

Abstract Text It is very well known that tumour environment, in general, and tumour oxygenation, in particular, have a significant impact on the treatment outcome with respect to both local control and long-term prognosis. The reduced oxygen partial pressure in the tumour microenvironment is expected to lead to angiogenesis, but also to restrained proliferation, apoptosis and