ESTRO 2021 Abstract Book

S732

ESTRO 2021

probabilistic ITV can be calculated. This makes the target definition less susceptible to outlier breath cycles and irregularities. Materials and Methods 4DCT data from three lung-cancer patients was unsorted according to each slice's time stamp and aligned with the breathing trace, then used to fit a motion model and generate an MCR. An ITV was contoured on the 4DCT data (phase images and maximum-intensity projection) following standard clinical practice (ITV-4DCT), and a corresponding GTV on the MCR (GTV-MCR). The GTV-MCR was transformed by the motion model to predict its position for every time point of the breathing trace. For each voxel, the probability that it belonged to the GTV-MCR was calculated, and this was used to form probabilistic ITVs encompassing all voxels with a probability >10%, >5%, >1%, and >0% (ITV-10%, ITV-5%, ITV-1%, ITV-0%). Results The MCR image quality is visually superior to the standard 4DCT phase images in terms of sharpness and shows no sorting artefacts (fig 1). Fig 2 shows a coronal slice and a close-up of the model generated GTV-MCR probability map and the contour of ITV-4DCT for all three patients. For patient 1 and 2 the ITV-4DCT is smaller than all probabilistic ITVs, and for patient 3 ITV-4DCT is similar in size to ITV-5%, (39.7 and 40.0ccm respectively) but is a different shape to ITV-5%.

Conclusion We have demonstrated the feasibility of generating probabilistic ITVs from a motion model built on unsorted 4DCT data and the subject’s breathing trace. Our initial results indicate that the widely used ITV-4DCT may