ESTRO 2021 Abstract Book

S731

ESTRO 2021

Conclusion An approach that gives individual pre-treatment estimation of the potential dosimetric impact of the interplay between organ motion and the dynamic beam was introduced. Although the interplay effect assessment disclosed the impact to be more severe for patients with longer breathing periods, this may be patient and plan dependent. Our approach can further be used for verification of ITV-based treatment plans using the patient respiratory pattern in order to identify whether the clinical goals can be achieved without explicit use of a respiratory management technique. PD-0893 Probabilistic lung tumour target definition from 4DCT data: A motion model based approach B. Eiben 1 , E. Chandy 2 , A. Abravan 3 , V. Rompokos 4 , H. Grimes 4 , D. D'Souza 4 , A. Poynter 4 , M. van Herk 3 , J.R. McClelland 1 1 University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom; 2 Univeristy College London, UCL Cancer Institute, London, United Kingdom; 3 The Christie NHS Foundation Trust, Department of Radiotherapy Related Research, Manchester, United Kingdom; 4 University College London Hospitals NHS Foundation Trust, Department of Radiotherapy Physics, London, United Kingdom Purpose or Objective Respiratory motion is one of the largest sources of uncertainty in RT for thoracic and upper abdominal tumours. 4DCT is commonly used to define an ITV which encompasses the GTV’s shape and motion, however, this modality is prone to artefacts due to irregular breathing. Furthermore, GTV positions as seen in the sorted 4DCT images only represent its position for one or two breath cycles, i.e. when the tumour is in the field of view (FOV) of the scanner detector making it susceptible to outliers resulting in potential geometrical miss. Instead, we propose to use a motion model based target definition. We utilise our unified motion modelling and image registration framework that – instead of generating a fixed number of phase (or amplitude) images – uses the unsorted 4dCT data to generate a single, motion-compensated-reconstruction (MCR) image and a motion model that describes the subject’s internal motion as function of their breathing trace. Hence, a GTV outlined on the MCR can be animated over the entire 4DCT acquisition using the model, from which a