MURAGAKI Yoshihiro    Department   School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine    Position   Visiting Professor
Language	English
Category	Chapter contribution
Title	Normalized Brain Datasets with Functional Information Predict the Glioma Surgery
Book title	Multidisciplinary Computational Anatomy Toward Integration of Artificial Intelligence with MCA-based Medicine
Responsible for	New Frontier of Technology in Clinical Applications Based on MCA Models: Cranial Nervous System
ISBN	9789811643248
Editor	HASHIZUME Makoto
Edition, Volume, Page	pp.173-180
Total page number	413
Publisher	Springer Singapore
Publication place (City and country)	Singapore
Author and coauthor	TAMURA Manabu, SATO Ikuma, MURAGAKI Yoshihiro
Publication date	2021/12/01
Summary	The goal of this study is to transform to the digitized intraoperative imaging and the compiled brain-function database for predicting glioma surgery that is based on the patient’s future perspective depending on the tumor resection rate as well as the postoperative complication rate. Firstly, we successfully acquired log data with the location of medical device integrated into intraoperative MR image and digitized brain function was converted to a normalized brain data format in 20 cases with acceptable accuracy. There were totally 22 speech arrest (SA), 10 speech impairment (SI), 12 motor, and 7 sensory responses (51 responses). Secondly, we simulated the projection of the normalized brain data to the individual pre- and intraoperative MR image. These image integration and transformation methods for brain normalization should facilitate practical intraoperative brain mapping. In the future, these methods may be helpful for preoperatively and/or intraoperatively predicting brain function.