ESTRO 36 Abstract Book

S944 ESTRO 36 _______________________________________________________________________________________________

EP-1721 A new calibration method of an Elekta XVI (R.5.0.2) system able to achieve superior image quality. D. Oborska-Kumaszynska 1 1 Royal Wolverhampton NHS Trust, MPCE Department, Wolverhampton, United Kingdom Purpose or Objective During acceptance testing of an Elekta XVI system, it is standard practice to only test system performance using SFOV. The focus of this work was to develop and introduce an extended customer acceptance test (AT) procedure as a foundation for introducing a new calibration method of an Elekta XVI (R.5.0.2) system. With optimal image quality achieved for all FOVs during AT, more appropriate optimisation of clinical XVI protocols can then be performed. Material and Methods Following a significant service of the system (X-ray tube replacement and calibration of the detector SDD), it was first calibrated in line with the standard manufacturer procedure. Extended ATs were then performed for all FOVs. A CATPHAN 600 phantom was used to assess spatial resolution, uniformity, contrast and geometry. The parameters used by the reconstruction algorithm can change depending on which AT you are performing (e.g. spatial resolution, uniformity or contrast). It was therefore necessary to assess all combinations of FOVs and each test (e.g. MFOV with spatial resolution, LFOV with uniformity…). Results The performed ATs showed unacceptable image quality for MFOV and LFOV. Spatial resolution tests revealed images with significant artefacts (Fig.1). The contrast results were worse than 3%. The uniformity test results were worse than 5%. The calibration procedure of the system was repeated a few times but results were still unacceptable. Investigations pointed to a few reasons: very rigid reconstruction algorithm (FDK) with regards to geometry, an exactly defined geometrical relation between X-ray source (focal spot position) and the coordinate system of pixels of the detector for each FOV, and correction of flexmap offset required for each FOV. This led to additional steps in the XVI system calibration: X-ray beam axis alignment perpendicular to the imaging panel surface and to “the centre” of that panel for each FOV; calibration of lateral panel position and re-setting of pots readings; re-calibration of flexmaps, badpixel maps and gains of the imaging panel. The spatial resolution test results showed for SFOV=13 lp/cm, MFOV=12.5 lp/cm, LFOV=13 lp/cm and clear visibility of the spatial pattern. The results for contrast were 1.85%; 2.39%; 2.91%, respectively and for uniformity were 0.52%; 2.00%; 3.64%, respectively.

planning of AVM’s. This negates the need to perform an invasive localised DSA in the majority of cases thereby reducing risks associated with this procedure. EP-1720 Framework for Statistical Cone-Beam CT Reconstruction with Prior Monte-Carlo Scatter Estimation J. Mason 1 , M. Davies 1 , W. Nailon 2 1 University of Edinburgh, Institute for Digital Communications, Edinburgh, United Kingdom 2 Oncology Physics Department, Edinburgh Cancer Centre, Edinburgh, United Kingdom Purpose or Objective Scatter from the patient and detector leads to significant inaccuracies and artefacts in cone-beam computed (CBCT). Monte-Carlo (MC) methods may allow the scatter signal to be accurately estimated based on a prior scan, but this must be matched and calculated for the new cone- beam measurements, and incorporated appropriately into a reconstruction method. We investigate a framework for statistical reconstruction with these prior MC estimates, under various work-flows. Material and Methods The framework consists of statistical iterative reconstruction with knowledge of a MC scatter estimate from the planning CT. The estimate can be generated with the scheme proposed by Xu et al. (PMB 2015) with online registration and approximate MC of the prior, or by calculating an accurate scatter off-line and warping to match the new measurements, which will be faster. We supplement the reconstruction with regularisation spatially and between the prior image, hereby utilising the planning image twice. Results The method was applied to data from repeat CT scanning of a neck cancer patient, with a low-dose repeat CBCT to form the new measurements. The figure shows reconstructions from the framework along with alternative approaches for comparison. The norm of the error in attenuation coefficient through the region containing the specimen is: 2.94 for no scatter estimate FDK , which has no scatter correction; 1.74 for uniform estimate statistical , which is statistical reconstruction with a simple scatter estimate; 2.41 for proposed estimate FDK, with prior scatter estimation; and 0.835 for proposed estimate statistical , which is the proposed framework combining double regularised statistical reconstruction with prior scatter estimation. We note that using the estimation strategy of Xu et al. in our framework yields an error of 0.792.

Conclusion We show that the general framework of statistical reconstruction with prior scatter estimation is accurate under low-dose acquisitions. The choice of our off-line scatter estimation or the on-line approximate estimate of Xu et al. is a trade-off in computational time and added accuracy, but either perform well. We suggest this quantitatively accurate method should be suitable for adaptive radiotherapy, and we are planning further testing with more applicable data.

Conclusion Introducing extended AT for the Elekta XVI (R.5.0.2) system provides full evaluation of the system before introducing it in to clinical practice and ensures that image quality is acceptable for all FOVs. The new calibration procedure was able to realise the full and proper reconstruction of image information and resulted in a significant improvement of image quality for all FOVs, as assessed by the above parameters.