ESTRO 2021 Abstract Book

S35

ESTRO 2021

eHR that captures the patient’s data before the diagnosis and then, through Natural Language Processing (NLP), analysis and categorization of all data to transform source information into structured data has been performed. Thereafter, an Artificial Intelligence method was developed to support the clinical staff in their decision with regards to tumor staging and to help them identifying the most complex cases where deeper analysis and discussion were required (e. g. conflicting information from different exams) (Figure 1).

Results In the first round, the system has been used to retrieve all the eHR for the 96 patients with LACC. This was the training set of the study, with validated 2009 FIGO staging classification ranging from I B2 to IV A as output. For these patients, available eHR included MR, EUA, and PET-CT diagnostic reports. The system has been able to classify all patients belonging to the training set and - through the NLP procedures - the clinical features were analyzed and classified for each patient. A second important result was the setup of a predictive model to evaluate the patient’s staging. Our approach has led to predict patient’s staging within an accuracy of 94%. Lastly we created a user-oriented operational tool targeting the MTB who are confronted with the challenge of large volumes of patients to be diagnosed in the most accurate way. The resulting decision support system is summarized in Figure 1. Furthermore, the MTB Smart DA was tested in a 13 LACC patients validation cohort showing an accuracy of 93%, in line with the training set performances. Conclusion This is the first proof of concept concerning the possibility of creating a smart virtual assistant for the MTB. A significant benefit could come from the integration of these automated methods in the collaborative, crucial decision stages. OC-0060 Clinical adoption patterns of 0.35 Tesla MR-guided radiation therapy in Europe and Asia M.A. Clark 1 , B. Slotman 2 , E. Ozyar 3 , M. Kim 4 , J. Itami 5 , A. Tallet 6 , J. Debus 7 , R. Pfeffer 8 , P. Gentile 9 , Y. Hama 10 , N. Andratschke 11 , D. Azria 12 , P. Camilleri 13 , C. Belka 14 , M. Quivrin 15 , B. Kim 16 , A. Pedersen 17 , M. van Overeem Felter 18 , K. Young 19 , J.H. Kim 20 , V. Valentini 21 1 ViewRay Technologies, Inc., Health Economics, Mountain View, USA; 2 Amsterdam University medical centers, Radiation Oncology, Amsterdam, The Netherlands; 3 Acibadem, Radiation Oncology, Acibadem, Turkey; 4 The Catholic University of Korea Incheon Saint Mary's Hospital, Radiation Oncology, Incheon, Korea Republic of; 5 National Cancer Center Japan, Radiation Oncology, Tokyo, Japan; 6 Institute Paoli Calmettes, Radiation Oncology, Marseille, France; 7 Heidelberg University Hospital, Radiation Oncology, Heidelberg, Germany; 8 Assuta Medical Centers , Radiation Oncology, Tel Aviv, Israel; 9 Opsedale San Pietro Fatebenefratelli di Roma, Radiation Oncology, Rome, Italy; 10 Edogawa Hospital, Radiation Oncology, Tokyo, Japan; 11 University Hospital Zurich, Radiation Oncology, Zurich, Switzerland; 12 Institut Regional du Cancer Montpellier, Radiation Oncology, Montpellier, France; 13 GenesisCare-Oxford, Radiation Oncology, Oxford, United Kingdom; 14 Klinkum der Universitat Munchen, Radiation Oncology, Munich, Germany; 15 Centre Georges-Francois Leclerc, Radiation Oncology, Dijon, France; 16 Sheikh Khalifa Specialty Hospital, Radiation Oncology, Ras Al Khaimah, United Arab Emirates; 17 Rigshospitalet, Radiation Oncology, Copenhagen, Denmark; 18 Herlev Hospital, Radiation Oncology, Herlev, Denmark; 19 Chungnam National University Sejong Hospital, Radiation Oncology, Daejeon, Korea Republic of; 20 Seoul National University Hospital, Department of Radiation Oncology, Seoul, Korea Republic of; 21 Università Cattolica S.Cuore, Fondazione Policlinico Universitario A.Gemelli IRCCS, Radiation Oncology and Hematology, Rome, Italy Purpose or Objective Magnetic resonance imaging-guided radiation therapy (MRgRT) utilization is rapidly expanding worldwide, driven by advanced capabilities including better soft tissue imaging, continuous intrafraction visualization, automatic triggered beam delivery, and on-table adaptive replanning. Our objective was to describe patterns of 0.35T-MRgRT utilization in Europe and Asia among early adopters of this novel technology. Materials and Methods