ムラガキ ヨシヒロ   MURAGAKI Yoshihiro
  村垣 善浩
   所属   研究施設 研究施設
   職種   教授
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).