ESTRO 36 Abstract Book

S920 ESTRO 36 _______________________________________________________________________________________________

Results Each of the selected six radiomics features (1 texture and 5 first order statistics), which were normalized to be comparable, showed higher predictive power compared to FMISO TMR max at the moment of predicting outcomes univariately. AUC-ROC curves demonstrated that a model created out of only six dominant CT-radiomics features can discriminate groups better with respect to local control in HNC using the logistic regression models (AUC = 0.904) than FMISO TMR max (AUC = 0.800). Nevertheless, a combination of FMISO-PET TMR max values and only two CT- radiomics features (Small Zone Emphasis texture and Minimum Grey Level first-order statistics) can reach an AUC of 0.886 in our classification model.

strategy. Several recent studies [1, 2] have shown that this is possible without compromising survival and with significantly reduced comorbidities. A significant challenge in this strategy is selecting the patients who are candidates for this strategy. We wish to examine whether diffusion weighted MRI (DWI) can be used as an early biomarker for tumor response to CRT. Material and Methods Here we present data from 25 patients treated for distal T3 or T4 rectal tumors. Patients were treated with long course CRT, including a brachytherapy boost to the tumor, followed by surgery. Patients were DWI scanned before start of CRT and again after 2 weeks of CRT. The DWI sequence included 11 b-values from 0 to 1100. Regions of interest (ROI) were drawn using an algorithm to locate areas with atypically high signal on high b-value images. ROI volumes where then analyzed using a radiomics approach where 67 image features were extracted from each volume. Tumor response to treatment was determined by pathologists examining the surgical specimen and scoring the tumor response using the Mandard Tumor Regression Grade (TRG). Data were analyzed both by visual examination of the data and by applying a decision tree algorithm. Results From visual inspection of the data we found that using only initial entropy and mean values for the ADC image as well as their change during the first 2 weeks of treatment, we could correctly classify 24 of the 25 patients as either major response (TRG 1 or 2) or minor response (TRG 3 or 4). This was confirmed by building a decision tree for the entire dataset. Applying machine learning techniques where the data are divided into a training and a test sample, we were hampered by the small data set, which meant building a model on only part of the data set and using the remaining patients to test the model gave large variations in both the selected parameters and the ability of the model to correctly predict the response of the remaining patients (from 40% to 100%). Conclusion DWI imaging can provide information on the tumor response as early as 2 weeks into CRT. Further work is needed to improve the model and especially testing on an larger data set is necessary. [1] High-dose chemoradiotherapy and watchful waiting for distal rectal cancer: a prospective observational study Appelt, Ane L et al. The Lancet Oncology , Volume 16 , Issue 8 , 919 - 927 [2] Watch-and-wait approach versus surgical resection after chemoradiotherapy for patients with rectal cancer (the OnCoRe project): a propensity-score matched cohort analysis Renehan, Andrew G et al. The Lancet Oncology , Volume 17 , Issue 2 , 174 - 183 EP-1687 Texture analysis of 18F-FDG PET/CT predicts local control of stage I NSCLC treated by SBRT K. Takeda 1 , K. Takanami 2 , Y. Shirata 1 , T. Yamamoto 1 , N. Takahashi 1 , K. Ito 1 , K. Takase 2 , K. Jingu 1 1 Tohoku University Graduate School of Medicine, Radiation Oncology, Sendai, Japan 2 Tohoku University Graduate School of Medicine, Diagnostic Radiology, Sendai, Japan Purpose or Objective Recently, there are some reports that texture analysis of 18F-FDG PET/CT has better potential to predict outcome of radiotherapy than existing PET parameters such as maximum SUV. We evaluated reproducibility and predictive value of some texture parameters based on gradient-based delineation method and existing

Conclusion CT radiomics proved to have better prognostic power with respect to local control in HNC than FMISO-PET TMR max . Nonetheless, a combination of TMR max and the two most significant features of CT radiomics reaches high prognostic power with fewer features to assess. Consequently, analysing tumour heterogeneity using CT radiomics features may have the power to determine substitute measures of tumour hypoxia and might therefore be used as a basis for personalized RT adaptations in the future. EP-1686 Diffusion weighted imaging for treatment response prediction in advanced rectal cancer H.D. Nissen 1 1 Nissen Henrik D., Department of Oncology - Section for Radiotherapy, Vejle, Denmark Purpose or Objective The standard treatment of locally advanced distal rectal cancer is chemoradiotherapy (CRT) followed by surgery. Based on pathologic examination of the surgery specimen, a significant number of patients are found to be without remaining tumor at the time of surgery. This has led to an increasing interest in whether, for a select group of patients, surgery can be replaced by a wait-and-see