ESTRO 36 Abstract Book

S947 ESTRO 36 _______________________________________________________________________________________________

Conclusion Our results suggested that Body6x1 might provide better SNR and image uniformity for T2-weighted abdominal MR- simulation scan than other two settings. EP-1725 Predicting radiation-induced pneumonitis in NSCLC: a radiobiological and texture analysis study W. Nailon 1 , W. Lu 2 , D. Montgomery 1 , L. Carruthers 1 , J. Murchiston 3 , A.W. Yong 3 , G. Ritchie 3 , T. Evans 4 , F. Little 4 , S.C. Erridge 4 , A. Price 4 , D.B. McLaren 4 , S. Campbell 4 1 Edinburgh Cancer Centre Western General Hospital, Department of Oncology Physics, Edinburgh, United Kingdom 2 School of Engineering University of Edinburgh, Institute of Digital Communications, Edinburgh, United Kingdom 3 Royal Infirmary of Edinburgh, Department of Radiology, Edinburgh, United Kingdom 4 Edinburgh Cancer Centre Western General Hospital, Department of Clinical Oncology, Edinburgh, United Kingdom Purpose or Objective In patients with inoperable non-small cell lung cancer (NSCLC) reliably estimating susceptibility to radiation- induced pneumonitis is challenging. Typically dose-volume histogram (DVH) parameters, normal tissue complication probability (NTCP) and changes in lung density are used, however, there is still considerable uncertainty in predicting individual patient susceptibility. The aim of this work was to investigate the presence of patient-specific density patterns that predict the likelihood of pneumonitis based on image analysis of radiotherapy planning CT images. The predictive image analysis measures were compared to NTCP models that predict the risk of pneumonitis. Material and Methods A cohort of 9 NSCLC patients made up of 4 patients (ID 71 to 74) that developed pneumonitis after radiotherapy and 5 patients that remained asymptomatic after radiotherapy (ID 10 to 14) was selected. Radiotherapy planning CT images were acquired at 3 mm slice thickness with a pixel resolution of 1 mm. 6 patients were treated with 55 Gy in 20 fractions and 3 patients with 60 Gy in 30 fractions. Treatment plans were produced on Eclipse using a pencil beam convolution dose calculation algorithm. 7 radiobiological models were used to calculate NTCP on the whole, right and left lungs. Image texture analysis was used to calculate 99 unique features on 32x32 and 20x20 pixel 2 subimages within the whole lung volume. Redundant texture features were removed and a neural network (NN) trained to classify the results. Results The predicted NTCP values are shown in Figure 1 for the analysis of the whole lung volume (normal lung tissue excluding the GTV). Similar results were obtained for the right and left lungs. Although model 5, symptomatic or radiographic pneumonitis <=6 months, showed high NTCP values this was not specific to patients with confirmed pneumonitis. Similar values were obtained in patients showing no signs of pneumonitis. The image texture analysis results identified the risk of pneumonitis most notably in the right lung (87.49%).

Figure 1 : NTCP results on the 9 patients (ID 10-14 asymptomatic, 71-74 symptomatic).

Table 1 : Texture analysis classification on the whole lung and right and left lung volumes. Conclusion These preliminary results show that it is possible to predict radiation-induced pneumonitis, both prior to treatment and independently of dosimetric evaluation, using image texture analysis of the radiotherapy planning CT images. However further validation on a larger patient cohort is required. EP-1726 Efficacy of vendor supplied distortion correction algorithms for a variety of MRI scanners E.P. Pappas 1 , I. Seimenis 2 , D. Dellios 2 , A. Moutsatsos 1 , E. Georgiou 1 , P. Karaiskos 1 1 National and Kapodistrian University of Athens, Medical Physics Laboratory - Medical School, Athens, Greece 2 Democritus University of Thrace, Medical Physics Laboratory - Medical School, Alexandroupolis, Greece Purpose or Objective Although inherently distorted, Magnetic Resonance Images (MRIs) are being increasingly used in stereotactic radiosurgery (SRS) treatment planning in order to take advantage of the superior soft tissue contrast they exhibit. MR scanner manufacturers have equipped their units with distortion correction algorithms to mainly compensate for gradient nonlinearity induced spatial inaccuracies. The purpose of this study is to assess the accuracy of these algorithms by comparing distortion maps deduced with and without the optional distortion correction schemes enabled for a variety of MRI scanners. Material and Methods A custom acrylic-based phantom was designed and constructed in-house. Its external dimensions were limited to approximately 17x16x16 cm 3 in order to accurately fit in a typical head coil while extending to the edges of the available space. On eleven axial planes, a total of 1978 holes were drilled, the centers of which serve as control points (CPs) for distortion detection. Center-to-center CP distance is 10 mm on x and y axis and 14 mm on z axis, resulting in adequately high CP density. The phantom was filled with copper sulfate solution and MR scanned at 1.5T (SIEMENS Avanto, Philips Achieva) and 3.0T (SIEMENS Skyra) using the corresponding standard clinical MR protocol for SRS treatment planning. All scans were