ESTRO 2020 Abstract Book

S857 ESTRO 2020

for soft tissue sarcomas in an automatic fashion. Such a network could be applied to automatic GTV segmentation which would help to speed up the process of STS treatment planning. PO-1580 CBCT-Based Radiomics of Prostate Cancer N. Dogan 1 , R. Delgadillo 1 , C. Ford 1 , F. Yang 1 , M. Studenski 1 , A. Pollack 1 , M. Abramowitz 1 1 University of Miami- Sylvester Comprehensive Cancer Center, Department of Radiation Oncology, Miami- Florida, USA Purpose or Objective Prostate Cancer is the sixth leading cause of male cancer death in the world. Recent publications have demonstrated that a variety of radiomics features extracted from different imaging modalities may have predictive value in prostate cancer. Currently, no studies have investigated the usefulness of imaging features extracted from Cone Beam CT (CBCT) images for patients treated with prostate cancer. The purpose of this work is to test the reproducibility of CBCT-Based radiomics texture features to reconstruction and pre-processing settings. Material and Methods Radiomics texture features were extracted from the gross tumor volume (GTV) from both the planning CT (pCT) and the first fraction CBCT for 20 prostate cancer patients. Parallel CBCT data sets were generated from the raw image projection data using different reconstruction types (iterative and standard), convolution filters (Sharp, Standard, and Smooth), and noise suppression filters (very high, high, medium, low, and very low). Texture features were extracted using different pre-processing settings including different quantization algorithms, quantization bins, and normalization. Forty-two texture features were calculated from five texture features classes, including gray-level run length matrix (GLRLM), gray-level co- occurrence matrix (GLCOM), neighborhood gray-level difference matrix (NGTDM), and gray-level size zone matrix (GLSZM). The first fraction CBCT texture features were correlated to the default CBCT (DCBCT) used for clinically (iterative reconstruction type, standard convolution filter, and medium noise suppression) using the spearman correlation. The first fraction CBCT and pCT texture features were also correlated using the spearman correlation. Results The texture feature from the DCBCT and the various reconstruction and pre-processing settings have a strong correlation across a variety of reconstruction and pre- processing settings. The median spearman R revealed a moderate correlation between the pCT and CBCT texture features. In terms of pre-processing settings, equal quantization algorithms with 256 quantization bins produced the most consistent and highest correlations across all texture features between pCT and CBCT images. In term of reconstruction settings, the most consistent and highest correlations between pCT across all texture features occur for sharp convolution filters and very high noise suppression. Six texture features were found to be highly correlated (R>0.85 and P<0.05) across many different reconstruction and pre-processing methods. Conclusion This work demonstrated that prostate CBCT radiomics texture features are robust to many different reconstruction and pre-processing settings and correlate highly across various different reconstruction and pre- processing settings. Such texture features are the most suitable for CBCT-Based radiomics texture feature analysis and model development for prostate cancer.

PO-1581 Prospectively scored pulmonary toxicities from a non-small cell lung cancer dose escalation trail C.M. Lutz 1 , M.M. Knap 2 , L. Hoffmann 2 , D.S. Moeller 2 , O. Hansen 3 , C. Brink 4 , T. Schytte 3 , C. Nyhus 5 , T. McCulloch 6 , S. Borissova 7 , M. Alber 8 , A. Khalil 2 1 Aarhus University Hospital, Department of Oncology, Aarhus C, Denmark ; 2 Aarhus University Hospital, Department of Oncology, Aarhus, Denmark ; 3 Odense University Hospital, Department of Oncology, Odense, Denmark ; 4 Aarhus University Hospital, Department of Oncology, Odense, Denmark ; 5 Vejle Hospital, Department of Oncology, Vejle, Denmark ; 6 Aalborg Hospital, Department of Oncology, Aalborg, Denmark ; 7 Herlev University Hospital, Department of Oncology, Herlev, Denmark ; 8 Heidelberg University Hospital, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany Purpose or Objective Local control and overall survival are poor in locally- advanced non-small cell lung cancer (LA-NSCLC). Unfortunately, intensified radiotherapy (RT) is limited by a high risk of pulmonary toxicities. This study investigated the prospectively scored pulmonary toxicities observed in a multicenter randomized phase II trial (NARLAL). Material and Methods Patients with stage IIB-IIIB histologically proven LA-NSCLC were recruited May 2009-August 2013 at five Danish RT centers. A total of 117 patients were treated with concomitant chemo-RT at 60Gy/30fx (arm A–59pts) and 66Gy/33fx (arm B–58pts). Pulmonary function tests (FEV1, FVC) were recorded. Pulmonary toxicities were reported as radiation pneumonitis (RP), dyspnea and cough (CTCAE v3.0). RP was reported when observed, while dyspnea and cough were frequently scored before, during and after RT.