ESTRO 2020 Abstract Book

S149 ESTRO 2020

number of patient in the analysis, we envision that the observed relationship between alopecia and dose can be used to set soft constraints during treatment planning to improve quality of life for patients with primary or metastatic brain tumours.

Poster discussion: CL: Breast 2

PD-0290 Efficacy of internal mammary nodal irradiation in T1-2N1 breast cancer in the modern era C. Jen 1 , J. Yen 1 1 Koo Foundation Sun Yat-Sen Cancer Center, Department of Radiation Oncology, Taipei, Taiwan Purpose or Objective This study aims to assess the efficacy of internal mammary nodal irradiation (IMNI) in patients with T1-2N1 breast cancer in the modern era and identify the specific subsets that benefit more from IMNI. Material and Methods Patients with T1-2N1 breast cancer treated during 1999 to 2016 at our institute were included. In order to determine the efficacy of IMNI, we only included patients received breast/chest wall and medial supraclavicular fossa irradiation. Patients not received adjuvant chemotherapy or treated with neoadjuvant chemotherapy were excluded. Patients with HER-2 overexpression disease not received Herceptin as adjuvant treatment were also excluded. The primary outcome was overall survival. Results A total 928 patients were included. The median follow-up was 98 months (range, 7 – 235 months). Among these patients, 649 patients received IMNI. The overall survival rates were similar between patients treated with IMNI and those not (HR 1.1, P = 0.58). In the subgroup analysis, patients with central/medial tumor (n = 321) did not significantly benefit from IMNI (HR 1.2, P = 0.7). IMNI also had no significant survival benefit in the subgroup of patients with ER negative disease, T2 disease or 2-3 metastatic axillary lymph nodes but had a trend for improved survival for patients with lymphovascular invasion disease (HR 0.61, P = 0.184). Patients aged between 45 and 54 years old (n = 332) treated with IMNI had improved overall survival. The 10-year overall survival for patients aged between 45 and 54 years old received IMNI was 95.1% compared to 79.6% for patients not (HR 0.3, P = 0.002). Among patients aged between 45 and 54 years old, only patients with nuclear grade 3 disease or 2-3 metastatic axillary lymph nodes significantly benefited from IMNI (HR 0.13, P < 0.001). The 10-year overall survival for this patient group (n = 246) was 96.3% for patients received IMNI and 65.8% for those not. After 1:1 propensity matching for this patients group, the survival benefit of IMNI remained.

Conclusion For patients with T1-2N1 breast cancer, a subset of patients aged between 45 and 54 years old, with nuclear grade 3 or 2-3 metastatic axillary lymph nodes may benefit from IMNI more. Further external validation is necessary. PD-0291 Comparison of different autosegmentation software for left-sided breast cancer patients J. Heikkilä 1 , T. Viren 1 , H. Virsunen 1 , K. Vuolukka 1 , L. Voutilainen 1 , R. Sawabi 2 , H. Abouelazm 2 , M. Kauppila 3 , J. Baeza 4 , W. Van Elmpt 4 , S.U. Akram 5,6 , J. Korhonen 3 , J. Seppälä 1 1 Kuopio University Hospital, Center of Oncology, Kuopio, Finland ; 2 University of Eastern Finland, Department of Applied Physics, Kuopio, Finland ; 3 Kymenlaakso Central Hospital- Kymenlaakso Social and Health Services Kymsote, Medical Imaging and Radiation Therapy, Kotka, Finland ; 4 GROW - School for Oncology and Developmental Biology- Maastricht University Medical Centre, Department of Radiation Oncology MAASTRO, Maastricht, The Netherlands ; 5 Aalto University, Department of Computer Science, Helsinki, Finland ; 6 MVision AI, MVision, Helsinki, Finland Purpose or Objective Autosegmentation of organs at risk (OAR) and target volumes (CTV) can be used to reduce contouring time and decrease inter- and intra-operator variation in the contouring task. The purpose of this study is to compare the accuracy of different autosegmentation software for delineation of CTVs and OARs of left-sided breast cancer patients. Material and Methods Breast CTV and OARs where manually contoured for 25 breast cancer patients according to the ESTRO guideline by expert radiation oncologists. Subsequently, patients were divided in to atlas/training set (n=20) and the test set (n=5). An artificial intelligence (AI) and four atlas- based segmentation software were used: MVision (Mvision AI Oy, Helsinki, Finland), ABAS (Elekta AB, Stockholm, Sweden), MIM (MIM Software Inc, OH, USA), Eclipse (Varian Medical Systems Inc, PA, USA) and Mirada (Mirada Medical Ltd, Oxford, UK). The contours created to five test patients were evaluated by calculating six different metrics to quantify the similarity between the automatically and manually delineated volumes: Dice similarity coefficient (DSC), Jaccard index (Jac), volume similarity (VS), average distance (AVE), BF score (BF) and Hausdorff distance (HD). Results CTV Breast, Heart, Left Lung and left anterior descending artery (LAD) structures were selected for the analysis. The autosegmented contours were compared to the manual delineation. An example of delineations for one test