ESTRO 37 Abstract book

S1164

ESTRO 37

EP-2112 How accurate should a GTV delineation be for radiomics? A study in NSCLC patients J.E. Van Timmeren 1 , R.T.H. Leijenaar 1 , W. Van Elmpt 2 , P. Lambin 1 1 The D-Lab: Decision Support for Precision Medicine, GROW - School for Oncology and Developmental Biology- Maastricht University Medical Center, Maastricht, The Netherlands 2 Department of Radiation Oncology MAASTRO, GROW - School for Oncology and Developmental Biology- Maastricht University Medical Center, Maastricht, The Netherlands Purpose or Objective Radiomics shows high potential for performing outcome predictions for non-small cell lung cancer (NSCLC) patients. However, delineations of the region of interest (ROI) are prone to interobserver variability which limits the reproducibility and robustness. Moreover, the introduction of new concepts based on longitudinal radiomics, are hampered by the time-consuming semi- automatic delineation of the ROI. Therefore, we investigated the prognostic value of a previously validated radiomic signature after eroding the original GTV. Material and Methods A dataset of 102 NSCLC patients was used in this study to extract radiomic features from the treatment planning CT images. For each patient, the GTV was eroded using a 3D structuring element with radius’ of 3, 5, 7 and 9 mm using the open-source platform REGGUI (http://openreggui.org). Due to the small size of some patients’ GTV, the eroded contours could be calculated for 97, 87, 79 and 66 patients, respectively. The radiomic feature values of the four features of a previously published radiomic signature (Aerts et al., 2014) were calculated for each GTV. Subsequently, the coefficients of the model were rescaled based on the slope of a linear regression of the radiomic features extracted from the original GTV and the eroded GTV. Harrell’s concordance index (c-index) and calibration slope of the models were calculated. Results Linear regression of radiomic features values extracted from original and eroded contours resulted in slope values that increased linearly with the size of the 3D structuring element used to erode the contours. The slopes with corresponding coefficients of determination (R 2 ) are summarized in Figure 1.

These slopes were used to correct to model coefficients prior to signature validation. The results of validation are shown in Table 1.

Conclusion The radiomic signature remains prognostic for NSCLC even after large erosion of the original GTV, provided that new model coefficients are derived based on a linear correction factor of the radiomic features. This implies that prognostic information is still captured and in the center of the GTV. This makes it possible to reduce the interobserver variability between delineations which will improve the reproducibility of radiomics. Moreover, these results will help to reduce the workload for the cumbersome delineation process, which is especially important for longitudinal or delta radiomics approaches were tumor shrinkage plays a role or datasets where no tumor lesions are delineated (e.g. non-radiotherapy). EP-2113 Reduction in the bone marrow 18F-FDG uptake during thoracic radiotherapy of lung cancer A. Abravan 1 , H. Eide 2 , A.M. Løndalen 3 , A. Helland 4 , E. Malinen 5 1 University of Oslo, Department of Physics, Oslo, Norway 2 Oslo University Hospital, Department of Oncology-, Oslo, Norway 3 Oslo University Hospital, Department of Radiology and Nuclear Medicine-, Oslo, Norway 4 Oslo University Hospital, Institute for Cancer Research-, Oslo, Norway 5 University of Oslo, Department of Physics-, Oslo, Norway Purpose or Objective Both cancer and cancer treatment can affect bone marrow (BM) metabolism, which may further contribute to hematologic toxicity. In this study, we longitudinally assessed how treatment of advanced non-small cell lung