ESTRO 36 Abstract Book

S80 ESTRO 36 2017 _______________________________________________________________________________________________

presence of metal artefacts. To eliminate left-right bias, each combination was shown twice.

methods for CT and CBCT radiomics features in rectal cancer, and to provide a harmonization evaluation method. Material and Methods Three harmonization strategies were tested in this study, including no correction, simple correction and phantom based correction. 50 rectal cancer patients with both planning CT images and positioning CBCT images before the first fraction of treatment were collected for harmonization performance evaluation. 203 features were extracted from CT and CBCT images. For the phantom based correction, a texture phantom comprised of 30 different materials was designed for features selection and nonlinear functions generation for normalizing CT and CBCT features.The Main workflow was shown in Figure 1. Mixed datasets consisting of CT and CBCT features were generated for harmonization performance evaluation using cluster analysis. The harmonization performance was evaluated by Chi-square testing between clustering results and scanner machines, and the clustering consistency with original CT feature. These tests were repeated for 50 times with randomized sample generation. Figure 1. Main Workflow. Four steps of this study:(I) Feature selection by features range comparison. (II)Feature selection by spearman correlation test. (III) Nonlinear mapping function generation using texture phantom. (IV)Correction methods performance evaluation on patients. Results 41 of the 203 radiomics features were selected by range comparison and spearman correlation test. Among 50 randomized sampling processes, all clustering (100%) results without any correction showed high correlation with imaging machine (p>0.05, χ^ 2 test), while this probability reduced to 0 % and 42% respectively when simple correction or phantom based correction were applied. Average accuracy and Kappa index increased significantly (p<0.05, t-test), respectively to 0.71±0.07 and 0.42±0.12 for simple correction method and 0.68±0.06 and 0.36±0.14 for phantom based correction method, from 0.61±0.06 and 0.23±0.13 without any correction.

Results VMDE images reconstructed at energies in the range 60 to 70 keV showed improved CNR for all soft tissue regions when compared to the standard CBCT. On average, the reconstruction energy corresponding to the maximum CNR improvement is 65.5 ± 2.4 keV. The increase in maximum CNR varied from 29% to 78%. The clinical observer comparison gave a series of rankings for each image series for each patient (see table 1). Using signed rank Wilcoxon comparison test, the observers found the VMDE images at 65 keV preferable to the standard CBCT image. The p-value was found to be < 0.01, where p < 0.05 is considered significant. An estimate of inter- observer variability test was done with Fleiss’ kappa and found to be moderate with a κ-value of 0.47, where values above 0.4 is considered acceptable and 1 is perfect agreement. Occasionally, an observer ranked the 75 keV reconstruction as the most preferable image while the overall preferred image was the 65 keV reconstruction. Except in the case of patient one where the standard CBCT image was ranked the highest of all.

Conclusion VMDE images can increase soft tissue contrast and improve clinical image quality for image-guided radiotherapy compared to the standard CBCT protocol. OC-0160 Radiomics Features Harmonization for CT and CBCT in Rectal Cancer R. Luo 1 , J. Wang 1 , H. Zhong 1 , J. Gan 1 , P. Hu 1 , L. Shen 1 , W. Hu 1 , Z. Zhang 1 1 Fudan University Cancer Hospital, Radiation Oncology, Shanghai, China Purpose or Objective Inter-scanner variability can lead to degradation of radiomics model quality. Therefore, feature harmonization is necessary for consistent findings in radiomics studies, especially for multi-institution studies. The purpose of this study is to establish harmonization

Table1. Performance evaluation result for different harmonization strategies. Conclusion This is the first study focused on feature harmonization for CT images. Two proposed correction methods, simple correction and phantom based correction, were verified to be feasible for CT and CBCT harmonization, which could significantly improve the modeling consistency.

Proffered Papers: Novelties in image guidance

OC-0161 patient tolerance of stereotactic MR-guided adaptive radiation therapy: an assessment using PRO’s