ESTRO 36 Abstract Book

S247 ESTRO 36 _______________________________________________________________________________________________

were associated with increased mortality, recurrence and disease progression in chemo-radiated patients with advanced tumours in our cohort (shown in figure) and with survival in the TCGA HNSCC cohort.

using the ECM to determine the search area and projections of the 3D voxel model as templates. The ECM is continuously updated with the latest estimated 3D marker position. The method was validated using Calypso- recorded internal motion and simultaneous camera- recorded external motion of 10 liver SBRT patients. The validation included both experiments with a programmable motion stage and simulations hereof for the first patient as well as simulations for the remaining patients. The real-time estimated 3D motion was compared to the known tumor motion. For comparison, the position estimation error was also calculated without ECM updates. Results The segmentation rate was 90% with a mean 2D segmentation error of 1.5pixels. Fig. B compares the estimated and actual target motion for a portion of the phantom experiment for Patient 1. The simulations agreed with the experimental root-mean-square error within 0.4mm (Table 1). For all patients, the mean 3D root-mean- square error was 1.74mm with ECM updates and 2.47mm without ECM updates (Table 1).

Conclusion We developed a model that exposes DNA repair defects as it predicts hypersensitivity to DNA crosslinking agents caused by such defects in vitro . The model successfully predicted sensitivity in an independent dataset. We found that increased probabilities of DNA repair defects were associated with poorer outcome in patients, possibly a result of the impact on genomic instability.

Proffered Papers: Highlights of proffered papers

OC-0464 Validation of a fully automatic real-time liver motion monitoring method on a conventional linac J. Bertholet 1 , R. Hansen 1 , E.S. Worm 1 , J. Toftegaard 1 , H. Wan 2 , P.J. Parikh 2 , M. Høyer 1 , P.R. Poulsen 1 1 Aarhus University Hospital, Department of oncology, Aarhus C, Denmark 2 Washington University- School of Medicine, Department of Radiation Oncology, St-Louis, USA Purpose or Objective Intrafraction motion is a challenge for accurate liver radiotherapy delivery. Real-time treatment adaptation (gating, tracking) may mitigate the detrimental effects of motion, but requires reliable target motion monitoring. In this study, we develop and validate a framework for fully automatic monitoring of thoracic and abdominal tumors on a conventional linac by combining real-time marker segmentation in kV images with internal position estimation by an external correlation model (ECM). The validation is based on experiments and simulations using known external and internal motion for 10 liver SBRT patients. Material and Methods A fully automatic real-time motion monitoring framework was developed. The framework combines auto- segmentation of arbitrarily shaped implanted fiducial markers in CBCT projections and intra-treatment kV images with simultaneous streaming of an external optical motion signal. Fig. A illustrates the workflow: A pre- treatment CBCT is acquired with simultaneous recording of the motion of an external block on the abdomen. The markers are segmented in every CBCT projection and a 3D voxel model of each marker is generated. The 3D marker motion is estimated from the observed 2D motion and used to optimize an ECM of the 3D internal marker motion INT(t) as a function of the external motion EXT(t). During treatment, INT(t) is estimated from EXT(t) at 20Hz, while MV-scatter-free kV images are acquired every 3s during beam pauses. The markers are segmented in real-time

Conclusion A real-time 3D tumor motion monitoring method was established and validated in experiments and simulations using known Calypso-recorded liver tumor motion. The method is fully automatic and can be used for arbitrarily shaped fiducial markers in the thorax or abdomen on a conventional linac without additional time or hardware. The internal position estimation can also be performed for non-coplanar fields where there is no room to deploy the kV imaging system.