マルヤマ タカシ
MARUYAMA Takashi
丸山 隆志 所属 医学部 医学科(東京女子医科大学病院) 職種 非常勤講師 |
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言語種別 | 英語 |
発表タイトル | Predicting surgery using normalized brain-function database and the application of tele-surgery support in 5G network |
会議名 | Computer Assisted Radiology and Surgery 36th International Congress and Exhibition Tokyo |
学会区分 | 国際学会及び海外の学会 |
講演区分 | シンポジウム・ワークショップ パネル(公募) |
発表者・共同発表者 | ◎TAMURA Manabu, SATO Ikuma, YAMAGUCHI Tomoko, YOSHIMITSU Kitaro, HORISE Yuki, MARUYAMA Takashi, NITTA Masayuki, KOBAYASHI Tatsuya, SAITO Taiichi, FUJINO Yuichi, MASAMUNE Ken, KAWAMATA Takakazu, ISEKI Hiroshi, MURAGAKI Yoshihiro |
発表年月日 | 2022/06/08 |
開催地 (都市, 国名) |
Tokyo |
開催期間 | 2022/06/07~2022/06/10 |
学会抄録 | International Journal of Computer Assisted Radiology and Surgery 17(Suppl 1),S76-77 2022 |
概要 | We have clinically operated an intraoperative MRI-guided navigation
system since 2000 in more than 2000 cases, and since 2004, we have performed intraoperative examination monitoring in awake mapping, that provided navigation images, electrical stimulation, and patient response on simultaneous video in more than 475 cases. Recently, mapping data was added to intraoperative MRI as digital brain function information, and the reaction points on intraoperative MRI were converted to preoperative MRI and standard brain, and the analysis results of 20 cases (reaction point 51) were summarized (JAMIT, 2020). The image conversion accuracy of the reaction points was 2.6 ± 1.5 mm for preoperative MRI and 1.7 ± 0.8 mm for standard brain, and we simulated the projection of the normalized brain data to the individual pre- and intra-operative MR image. In the future, we are planning predicting glioma surgery that includes AI analysis database intraoperatively by adding the tumor removal rate, the incidence of motor / language function complications, the degree of home / social rehabilitation, etc. to the mapping information [1]. |