KUSUDA Kaori
Department Research Institutes and Facilities, Research Institutes and Facilities Position |
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Language | Japanese |
Title | Proposal of Integration Method of Intra‒Operative Brain Functional Positions into the Standard Brain by Non‒Rigid Registration in Awake Surgery |
Conference | The 28th Annual Congress of Japan Society of Computer Aided Surgery |
Conference Type | Nationwide Conferences |
Presentation Type | Speech |
Lecture Type | Panelist at Symposium/Workshop (Appointed) |
Date | 2019/11/24 |
Society abstract | 日本コンピュータ外科学会誌 21(4),322 2019 |
Summary | Abstract:For glioma surgery, “future‒predicting glioma surgery” was suggested. Future‒predicting glioma surgery can
facilitate decision‒making for surgeons by predicting the post‒operative neurological complications with respect to the scheduled resection area. Due to its importance, past surgical data of numerous patients need to store and do statistical analyzed. This will enable the realization of evidence‒based resection surgery in glioma. For pre‒processing of data in future predicting glioma surgery, we need to create datasets for statistical analysis by integrating past surgical data in one coordinate system. In a previous study, digitized brain functional positions and methods for creation of datasets for statistical analysis were suggested. Using results of this study, we integrated brain functional positions into the standard brain1). However, the datasets for statistical analysis were not enough. In this study, we describe the methods of creating datasets of brain functional positions for statistical analysis in future‒predicting glioma surgery. These are made possible by integrating brain functional positions of many patients into the standard brain. Furthermore, intra‒operative MR images and brain function positions of 24 patients were integrated to the standard brain by non‒rigid registration. Subsequently, we evaluated the integration accuracy of these methods. In intra‒operative MRI to the standard brain registration, the overall registration error was 2.9±1.1[mm]. We believe that our proposal method can analyze brain functional positions with individual difference statistically in the future. Key words:Standard brain, Non‒rigid registration, Brain functional positions |