ESTRO 36 Abstract Book

S908 ESTRO 36 2017 _______________________________________________________________________________________________

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 parameters of 18F-FDG PET/CT image in patients with early stage non-small cell lung cancer (NSCLC) treated by stereotactic body radiation therapy (SBRT). Material and Methods Thirty patients with early stage NSCLC (T1-2N0M0) were retrospectively investigated. SBRT was delivered with total dose of 40-48Gy in 4 fractions for peripheral regions or 50-60Gy in 7-15 fractions for central regions or regions nearby other organ at risk. All patients underwent 18F- FDG PET/CT scan before treatment. Each tumor was delineated using PET Edge (MIM Software Inc., Cleveland) and texture parameters were calculated using open- source code CGITA (Fang, et.al., 2014). From 18F-FDG PET/CT image, three conventional parameters including metabolic tumor volume (MTV), maximum standardized uptake value (SUV) and total lesion glycolysis (TLG) and four textural parameters including entropy and dissimilarity derived from co-occurrence matrix and high-

intensity large-area emphasis and zone percentage derived from size-zone matrix were analyzed. Reproducibility was evaluated using two independent delineation conducted by two observers using intraclass correlation coefficients (ICC). The ability to predict local control (LC) was tested for each parameter using Cox proportional hazards model. Results Median follow-up period was 30.1 month and 8 (23%) patients occurred local relapse. Between two observers, six parameters besides zone percentage (ICC value 0.59) showed ICC value ranged between 0.81 and 1.00. In univariate analysis, there were significant correlations between LC and tumor diameter>30mm (hazard ratio 7.21, p=0.02), MTV≥5.14cm3 (HR 9.38, p=0.01), TLG≥59.7 (HR 5.86, p=0.04), entropy≥-34.3 (HR 0.13, p=0.02), dissimilarity≥2235 (HR 6.87, p=0.03) and treatment biological equivalent dose≥100Gy (HR 0.02, p=0.04), respectively. Maximum SUV≥10.4 was not a significant predictor for LC (p=0.09).

Conclusion Texture analysis based on gradient-based delineation method has high reproducibility in most parameters. Entropy and dissimilarity calculated from co-occurrence matrix is potentially beneficial to predict LC with reproducibility in patients with NSCLC treated by SBRT. To establish utility of texture analysis in 18F-FDG PET/CT image, further study including prospective trial will be needed. EP-1688 Voxelbased analysis of FMISO-PET and diffusion-weighted MRI of two different HNSCC models in mice R. Winter 1 , S. Boeke 2 , M. Krueger 3 , A. Menegakis 2 , E. Sezgin 2 , L. Wack 1 , G. Reischl 3 , B. Pichler 3 , D. Zips 2 , D. Thorwarth 1 1 University Hospital Tübingen, Section for Biomedical Physics, Tübingen, Germany 2 University Hospital Tübingen, Radiation Oncology, Tübingen, Germany 3 Werner Siemens Imaging Center, Preclinical Imaging and Radiopharmacy, Tübingen, Germany Purpose or Objective Hypoxia is an important prognostic marker for radiotherapy (RT) response, particularly for head and neck squamous cell carcinoma (HNSCC) and may be measured