ホリセ　ユキ   Horise Yuki   堀瀬　友貴    所属   医学研究科 医学研究科 (医学部医学科をご参照ください)    職種   非常勤講師
言語種別
発表タイトル	Clinical Information Analyzer system to supportsurgery toward realization of AI surgery
会議名	CARS 2019 – 33rd International Congress and Exhibition
学会区分	国際学会及び海外の学会
発表形式	ポスター掲示
講演区分	一般
発表者・共同発表者	KUSUDAKaori, OKAMOTOJun, HORISEYuki, TAMURAManabu, KOBAYASHIEtsuko, MURAGAKIYoshihiro, MASAMUNEKen
発表年月日	2019/06/20
開催地 （都市, 国名）	Rennes, France
学会抄録	CARS 2019 21(4)  CARS 2019 – 33rd International Congress and Exhibition
概要	Purpose In operation room, there are a lot of data such as biological information, medical information, surgical process information, pathology report. In generally, surgeons integrate information and make experience-based decision during surgery. To support effective decision making, it require that ‘‘data’’ in operation room is integrated and managed as ‘‘information’’. In our hospital, intelligent operating room using intraoperative MRI and navigation system was developed. MRI (0.4T, Open MRI, APERTO Lucent, Hitachi, Ltd.) in operating room (OR) was installed, and it realized high precision and maximal extraction of brain tumor. One thousand nine hundred surgeries in the room from 2000 to 2018 were operated. Additionally, Smart Cyber Operating Theater (SCOT) is developed based on Intelligent OR. To realize information-guided surgery, by packaging basic surgical equipment such as MRI and various medical devices, the system was able to network equipment. These medical devices data are time synchronized. SCOT is a ‘‘treatment room interface’’ that connects various devices in the treatment room, and Smart Cyber Operation Link (OPeLiNK) was developed based on the industrial middleware ORiN. It has the role of networking the application used by the user and the device connected to the system. To improve the clinical value of SCOT, utilize the data of various devices obtained during surgery is required. Furthermore, it is necessary to construct a foundation for analyzing huge amount of information including clinical data of electronic medical record (EMR) and surgical records by statistical processing and machine learning. The purpose of this study is development of a clinical information analysis system to analyze a lot of data and support decision making during surgery. Methods In this study, Clinical Information Analyzer (C.I.A.) as the foundation software for data is developed. By realizing an integrated system of SCOT and C.I.A., we aim to improve safety by risk avoidance and improve a quality of life by quantitative prediction of treatment effect (shown in Fig. 1).