ESTRO 2020 Abstract Book

S855 ESTRO 2020

redundant (r<0.85) and prognostic features (p<0.05 in univariate Cox models) was selected. The remaining radiomics features were sorted by hazard ratio and progressively added to a multivariate Cox regression to estimate the best features number for the final signature. A bootstrap sampling was used to select the pts of the training set (n=110), and the unsampled pts were used as a validation set (n=69). The association between the radiomics signatures and OS was investigated. The proportion of events in the training and validation sets was the same (12%). Feature selection and Cox model fitting were performed on the training set. Pts in the validation set were classified according to radiomics signature into high risk (HR) and low risk group (LR). The performance of the signature was evaluated in the validation set using the Harrel’s c-index (CI). Univariate analysis comparing Kaplan-Meier curves was performed using log-rank test. The possibility of a correlation with the primary gross tumor volume (GTV-T) was checked for the resulting radiomics signature. Results The median follow-up was 60.43 months (range: 44.23– 67.00). A signature including 2 features accounting for tumor intensity and texture ( T_T1w_waveletLLH_firstorder_Median and T_T2w_waveletLLH_glcm_Imc1 ) was identified. 5-years OS was 78.6% and 94.6% for HR and LR group, respectively. In the validation cohort the signature had a CI of 0.67±0.09 and a significant difference was found in the OS between HR and LR groups (p=0.04 for log-rank test, see Fig.1). A correlation was found between GTV-T and the radiomics signature (r=0.6), but GTV-T alone had no significant impact on OS curves (CI 0.57±0.1, log-rank p=0.28).

Conclusion MRI-based radiomics in PCa for the prediction of tumour phenotype is a feasible and promising approach. It might lead to a semi-automated definition of tumour characteristics and thus reduce the intra/inter-operator variability in the radiologic image interpretation. Although a significant association was found between the selected features and all the mentioned clinical and radiological scores, further validations on larger cohorts are needed before applying these findings in the clinical practice. PO-1577 Baseline MRI-radiomics can predict overall survival in non endemic nasopharyngeal cancer patients E. Orlandi 1 , G. Calareso 2 , C. Tenconi 3,4 , T. Rancati 5 , N.A. Iacovelli 1 , A. Cavallo 6 , N. Facchinetti 1 , R. Ingargiola 1 , E. Ivaldi 1 , D.A. Romanello 1 , V. Corino 7 , R. Valdagni 3,4,5 , S. Cavalieri 8 , S. Alfieri 8 , L. Licitra 8 , E. Pignoli 6 , L. Mainardi 9 , C. Fallai 1 , M. Bologna 7 1 Fondazione IRCCS Istituto Nazionale dei Tumori, Radiation Oncology 2, Milan, Italy ; 2 Fondazione IRCCS Istituto Nazionale dei Tumori, Department of Radiology, Milan, Italy ; 3 University of Milan, Department of Oncology and Haemato-oncology, Milan, Italy ; 4 Fondazione IRCCS Istituto Nazionale dei Tumori, Radiation Oncology 1, Milan, Italy ; 5 Fondazione IRCCS Istituto Nazionale dei Tumori, Prostate Cancer Program, Milan, Italy ; 6 Fondazione IRCCS Istituto Nazionale dei Tumori, Medical Physics, Milan, Italy ; 7 Politecnico di Milano, Dipartimento di Elettronica- Informazione e Bioingegneria DEIB, Milan, Italy ; 8 Fondazione IRCCS Istituto Nazionale dei Tumori, Head and Neck Medical Oncology Unit, Milan, Italy ; 9 Politecnico di Milano, Dipartimento di Elettronica- Informazione e Bioingegneria DEIB9, Milan, Italy Purpose or Objective To assess the ability of magnetic resonance imaging (MRI)- radiomics to provide a prognostic signature for overall survival (OS) in locoregionally advanced nasopharyngeal cancer (LANPC) patients (pts) in a non endemic area Material and Methods A mono-institutional series of 179 Epstein Barr Virus (EBV)– related non metastatic LANPC pts curatively treated with Intensity Modulated radiotherapy and chemotherapy (CHT) with or without induction CHT between 2004 and 2017 was considered for this retrospective analysis. The primary endpoint of the study was OS. All pts had pretreatment multi-MRI images. Texture features were extracted from the pretreatment T1- and T2-weighted images for each case. Regions Of Interest (ROIs) were considered in primary tumor and pathological nodes. A total of 2144 radiomics features was extracted from the ROIs by using software Pyradiomics (2.1.0). First, a set of stable, non

Conclusion The developed MRI-radiomics signature can be a valuable tool for the prognosis of LANPC pts in non endemic area. It could be integrated into a multidimensional nomogram including disease stage at diagnosis and baseline EBV-DNA plasma load. This might define pts’ prognosis more accurately and lead to the development of tailored treatment through radiomics, biological and clinical characteristics. PO-1578 Heart V10 is related to treatment-elicited inflammation and clinical response in esophageal cancer. Y. Ho 1 , J. Lin 1 , M. Ko 1 , T. Chou 1 , L. Hung 1 , C. Huang 1 , T. Chang 1 1 Changhua Christian Hospital, Department of Radiation Oncology, Changhua, Taiwan Purpose or Objective For esophageal cancer with cervical location or non- surgical candidate, definitive concurrent