Abstract Book

S1188

ESTRO 37

presented for the left parotid, right parotid, and spinal cord (B). The Human-2 (C), AI-1 (D), Human-1 (E), and AI- 2 (F) contours are presented for the mandible, (pink), left parotid (teal), and right parotid (orange). Note: Voxels above a prediction threshold of 0.5 are considered to be part of the structure under consideration.

Table 1. The clinician scores for the average of all 13 patients are presented for every OAR for each contouring style.

Conclusion Distortion Correction software was proved in our study as a helpful tool to detect and adequately correct brain MR distortions. EP-2153 The primary X-ray source: reconstruction and characterization of six Varian TrueBeam sources P. Papaconstadopoulos 1 , K. O'Grady 2 , S. Aldelaijan 1 , S. Devic 1 , I.R. Levesque 3 , J. Seuntjens 3 1 The Jewish General Hospital- McGill University, Radiation Oncology, Montreal, Canada 2 Montefiore Medical Center, Radiation Oncology, New York, USA 3 The Cedars Cancer Institute- McGill University, Medical Physics, Montreal, Canada Purpose or Objective the primary X-ray source size and shape, as generated in the entrance of the linac target, is one of the most important parameters for accurate beam characterization and modeling. In this work we apply a recently suggested and clinically applicable method [1] to fully characterize the primary X-ray source of six Varian TrueBeam (TB). Material and Methods A series of crossplane and inplane photon fluence profile measurements were performed on six clinical linear accelerators (Varian TB including two Stx). The photon fluence profiles were measured using radiochromic film (average of five repetitions) in air with a 2 mm lead (Pb) foil as a build-up layer. A deconvolution kernel was applied to account for the non-zero electron range and photon scattering in the foil. The measurements were performed using the smallest jaw-defined field size (5 mm) in order to maximize the differentiation among the various source sizes and eliminate the impact of scatter sources and other beam parameters. An iterative MLEM reconstruction algorithm was then applied to estimate the source distribution, using a projection/back- projection approach by ray-tracing, to converge on the final source estimate. The exact jaw position was determined by repeating the reconstruction for all possible jaw positions in the range of 4 – 6 mm (step = 0.1 mm) and minimizing the error between reconstructed and measured profile. The technique’s predictive accuracy in reproducing the correct source size and shape was benchmarked using a commissioned Monte Carlo (MC) model (EGSnrc/BEAMnrc) of a Varian TrueBeam with predefined input Gaussian source sizes (FWHM = 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2 mm) and fixed jaw position of 5 mm projected at 100 cm. Results At the MC benchmarking stage the MLEM reconstruction algorithm reproduced the Gaussian profile with a root- mean-squared-error (RMSE) of 1.8-4.9 %. The reconstructed source size (FWHM) and jaw position were determined with an accuracy of 0.1 mm in all cases. The algorithm’s ability to reach a unique solution was best for source sizes of FWHM less than 1.5 mm. Experimentally, reconstructed sources presented FWHM values of 1.02 – 1.5 mm (1 sigma=0.04 - 0.18 mm) and 1.08-1.42 mm (1 sigma=0.04 – 0.13 mm) in the crossplane and inplane

Electronic Poster: Physics track: Implementation of new technology, techniques, clinical protocols or trials (including QA & audit)

EP-2152 Validation Of A Novel Software For Correcting Distortion In Cranial Magnetic Resonance (Mr) Images J.F. Calvo Ortega 1 , J. Mateos 2 , A. Alberich 3 , S. Moragues 1 , J. Casals 1 1 HOSPITAL QUIRON BARCELONA, Radiotherapy, Barcelona, Spain 2 Imagen Ensayos Clínicos IEC- Hospital Quirón, Imagen Ensayos Clínicos IEC- Hospital Quirón, Barcelona, Spain 3 Biomedical Imaging Research Group GIBI230- La Fe Health Research Institute, Biomedical Imaging Research Group GIBI230- La Fe Health Research Institute, Valencia, Spain Purpose or Objective The accuracy of the Brainlab Elements Cranial Distortion software was investigated. Material and Methods Five MR datasets (used for vestibular schwannoma radiosurgery planning) were intentionally distorted. Two types of distortions were applied: 1) dist1: s=r(1+0.1r^2) and dist2: s= r(1+0.5r), where s and r are the distance from the center of distortion in the undistorted and distorted images, respectively. Each distorted MR dataset was corrected using the Cranial Distortion software, resulting a new corrected MR dataset (MRcorr). The accuracy of the correction was quantified by calculating the target registration error (TRE) for six anatomical landmarks identified in the co-registered MRcorr and planning CT (pCT) images. The chosen landmarks were points marked at of the two vestibules, at the two internal auditory canals and at the cochleas. The pCT dataset was selected as the reference to specify the 'true” position of each selected landmark. Results Figure 1 and 2 show the TRE values obtained for each type of forced distortion. In overall, the TRE values (0.6 mm ± 0.3 mm) were within the voxel size dimension of the pCT scan (1 x 1 x 1 mm 3 ). Legend of Figures 1 and 2: Red columns: average target registration error between the distorted MR set and the planning CT (TREdist). Blue columns: average target registration error between the corrected MR set and the planning CT (TREcorr). Mean ± standard deviation (SD) is displayed as a bar on each column of the plot. C: ipsilateral cochlea, V: ipsilateral vestibule, IAC: ipsilateral internal acoustic canal; Cc: contralateral cochlea, Vc: contralateral vestibule, IACc: contralateral internal acoustic canal.