ESTRO 2020 Abstract book

S451 ESTRO 2020

predominantly poorly differentiated tumors occurred (72.7%). In the cox-regression model the textural features Busyness (p<0.01; Exp. B=1.56), ContrastM3 (p<0.01; Exp. B=9.34) and SUVmax (p=0.019; Exp. B=0.93) were significantly associated with OS. We observed a significant prognosis deterioration for a value >1.76 for Busyness and a value >0.407 for Contrast respectively. Conclusion In our analysis, only tumor differentiation was significantly associated with response to nCRT. However, the 18F-FDG- PET/CT derived textural features Busyness, Contrast and SUVmax provide statistical value for predicting overall survival in ESCC patients undergoing nCRT and surgery and should therefore be further investigated in future studies. PH-0720 delta-radiomics based on MRI predicts response to concurrent chemoradiotherapy in esophageal cancer D. An 1 , B. Li 1 , Q. Cao 2 , W. Yin 3 1 Shandong Cancer Hospital and Institute- Shandong First Medical University and Shandong Academy of Medical Sciences, department of radiation oncology, Jinan, China ; 2 Southeast University, Laboratory of Image Science and Purpose or Objective This study aimed to investigate the association between the radiomics features (RFs) extracted from the whole- tumor apparent diffusion coefficient (ADC) map during the early treatment course and response to concurrent chemoradiotherapy (cCRT) in patients with esophageal squamous cell carcinoma (ESCC). Material and Methods In this prospective, observational study, ESCC patients treated with cCRT were enrolled and assigned to the training set and the validation set according to the beginning of radiotherapy in a 2:1 ratio. Each patient underwent sequential diffusion-weighted magnetic resonance imaging (DW-MRI) at pretreatment, 5th radiation completed and 10th radiation completed. Whole- tumor ADC values and 851 RFs were extracted within a volume of interest. Bland-Altman method and the minimum redundancy/maximum relevance algorithm were performed in pretreatment images on the training set for selecting RFs. The changes in those selected values were calculated as relative differences between each time point (delta-ADC values and delta-RFs). Afterwards, the identified RFs were used to train Support Vector Machine (SVM) classifiers for building a radiomics signature, to associate the treatment response and validated in the validation set. Radiomics signatures were developed from both RFs extracted from pretreatment images and delta- RFs calculated during 1st week, 2nd week and 2 weeks, respectively. Receiver operating characteristic (ROC) curve analysis was performed in the training and validation sets. Univariate analysis was performed to explore association between clinical characteristics, ADC values, radiomics signature and their changes with treatment response. The meaningful results were used to build treatment response-related multivariate logistic regress models. Finally, the performances of each model was assessed by the ROC curves. Technology, Nanjing, China ; 3 Inspur Electronic Information Industry Co.-Ltd, Department of Architecture Research, Jinan, China

Conclusion Change in ADC, a quantitative MRI parameter seems to be a potential prognostic marker in uterine cervix cancer with strong correlation in advanced stages. This study shows that low change in ADC in advanced stages is a poor prognostic marker and needs treatment intensification to improve clinical outcomes. PH-0719 18F-FDG-PET/CT parameters as predictors of survival and response to nCRT in esophageal cancer L. Marr 1 , T. Pyka 2 , J.C. Peeken 1 , B. Haller 3 , M. Jesinghaus 4 , W. Weichert 4 , W. Weber 5 , S.E. Combs 1 , S. Münch 1 1 Technical University Munich TUM, Department of Radiation Oncology, Munich, Germany ; 2 Technical University Munich TUM, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany ; 3 Technical University Munich TUM, Institute of Medical Informatics, Munich, Germany ; 4 Technical University Munich TUM, Institute of Pathology, Munich, Germany ; 5 Technical University Munich TUM, Department of Nuclear Medicine, Munich, Germany Purpose or Objective In patients with advanced esophageal squamous cell carcinoma (ESCC) a multimodal therapy including neoadjuvant chemoradiation (nCRT) and subsequent surgery is the treatment of choice. The aim of this study was to validate the predictive potential of clinical parameters and 18F-FDG-PET/CT derived textural features in ESCC patients undergoing nCRT + surgery. Material and Methods Between 2005 and 2014, 38 ESCC patients (18 females and 20 males, median age 62 years) with pre-treatment 18F- FDG-PET/CT scans were treated with nCRT and esophagectomy at our department. All patients received neoadjuvant treatment including platinum-based chemotherapy and a total radiation dose of 45Gy. Response to nCRT was evaluated by histomorphological workup of the resected specimen as described by Becker et al. [1]. Good response was defined as <10% residual tumor (Becker 1a + 1b), while poor response was defined as ≥10% residual tumor (Becker 2 + 3). Regression analyses were used to identify parameters predicting overall survival (OS) and response to nCRT. The optimal cut-off value of significant parameters was determined by the maximally selected LogRank test and a test on association using the R package maxstat.test. [1] Becker et al., Histomorphology and grading of regression in gastric carcinoma treated with neoadjuvant chemotherapy. Cancer, 2003. 98(7): p. 1521-30. Results The histopathologic analysis of the resected specimen reported good response in 28 patients (71%) and poor response in 11 patients (29%). After a median follow-up of 68 months for surviving patients, median overall survival was 40 months. Using binary logistic regression analysis, we saw no significant predictive potential for any of the PET/CT parameters regularly described in the literature in terms of treatment response (e.g. maximum standardized uptake value (SUVmax), Metabolic tumor volume (MTV) and texture features). While clinical parameters T-stage, N-stage, tumor length, and sex were not associated with response, only tumor grading was seen to predict response to nCRT significantly (p=0.034). Thereby, the rate of patients with moderately differentiated primary tumors was significantly higher in the subgroup of responders (67%) than in the subgroup of non-responders, where