MURAGAKI Yoshihiro    Department   School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine    Position   Visiting Professor
Language	English
Title	Integration of intra-operative brain functionalpositions into the standard brain using SPM
Conference	CARS 2019 – 33rd International Congress and Exhibition
Conference Type	International society and overseas society
Presentation Type	Poster notice
Lecture Type	General
Publisher and common publisher	OHSHIMA Kazuma, SATO Ikuma, NAMBU Y, FUJINO Yuichi, HORISE Yuki, KUSUDA Kaori, TAMURA Manabu, MURAGAKI Yoshihiro, MASAMUNE Ken
Date	2019/06/20
Venue (city and name of the country)	Rennes, France
Society abstract	CARS 2019 21(4) 2019 CARS 2019 – 33rd International Congress and Exhibition
Summary	Purpose ‘‘Future-predicting glioma surgery’’ has been suggested for glioma resection surgery [1]. Future-predicting glioma surgery can facilitate clinical decision-making by predicting the survival rate and postoperative neurological complications with respect to the set resection area. However, storage of evidenced-based information for realizing future-predicting glioma surgery has not yet been sufficiently done. To enable future-predicting glioma surgery, we need to create datasets for predicting the survival rate and post-operative neurological complications extracted from post-surgery information. In a previous study, digitized brain functional positions and methods for creation of datasets for statistical analysis and a method of integrating intra-operative electrical stimulation positions into the standard brain were suggested [1, 2]. As individual differences exist in intra-operative information among patients, position information is unified in the standard brain coordinate system, and individual differences can be eliminated by standardization. Using the intra-operative information obtained by these studies to integrate them into the standard brain allows the analysis of evidenced-based information. However, the available datasets for statistical analysis are not adequate. In this study, for creating analysis datasets to realize future prediction surgery, brain functional positions with individual differences of each patient were integrated into the standard brain by statistical parametric mapping (SPM) and were visualized. In addition, w