Tomoko Yamaguchi1,2, Atsushi Kuwano3, Toshihiko Koyama4, Jun Okamoto5, Shigeyuki Suzuki6, Hideki Okuda4,6, Taiichi Saito3, Ken Masamune5, Yoshihiro Muragaki5. 1. Faculty of Advanced Techno-Surgery, Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan. tomokoy@people.kobe-u.ac.jp. 2. Center for Advanced Medical Engineering Research & Development, Kobe University, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe City, Hyogo, 650-0017, Japan. tomokoy@people.kobe-u.ac.jp. 3. Department of Neurosurgery, Tokyo Women's Medical University Hospital, Tokyo, Japan. 4. DENSO Corporation, Aichi, Japan. 5. Faculty of Advanced Techno-Surgery, Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, Tokyo, Japan. 6. OPExPARK Inc., Tokyo, Japan.
Abstract
PURPOSE: Surgical devices or systems typically operate in a stand-alone manner, making it difficult to perform integration analysis of both intraoperative anatomical and functional information. To address this issue, the intraoperative information integration system OPeLiNK® was developed. The objective of this study is to generate information for decision making using surgical navigation and intraoperative monitoring information accumulated in the OPeLiNK® database and to analyze its utility. METHODS: We accumulated intraoperative information from 27 brain tumor patients who underwent resection surgery. First, the risk rank for postoperative paralysis was set according to the attenuation rate and amplitude width of the motor evoked potential (MEP). Then, the MEP and navigation log data were combined and plotted on an intraoperative magnetic resonance image of the individual brain. Finally, statistical parametric mapping (SPM) transformation was performed to generate a standard brain risk map of postoperative paralysis. Additionally, we determined the anatomical high-risk areas using atlases and analyzed the relationship with each set risk rank. RESULTS: The average distance between the navigation log corresponding to each MEP risk rank and the anatomical high-risk area differed significantly between the with postoperatively paralyzed and without postoperatively paralyzed groups, except for "safe." Furthermore, no excessive deformation was observed resulting from SPM conversion to create the standard brain risk map. There were cases in which no postoperative paralysis occurred even when MEP decreased intraoperatively, and vice versa. CONCLUSION: The time synchronization reliability of the study data is very high. Therefore, our created risk map can be reported as being functional at indicating the risk areas. Our results suggest that the statistical risks of postoperative complications can be presented for each area where brain surgery is to be performed. In the future, it will be possible to provide surgical navigation with intraoperative support that reflects the risk maps created.
PURPOSE: Surgical devices or systems typically operate in a stand-alone manner, making it difficult to perform integration analysis of both intraoperative anatomical and functional information. To address this issue, the intraoperative information integration system OPeLiNK® was developed. The objective of this study is to generate information for decision making using surgical navigation and intraoperative monitoring information accumulated in the OPeLiNK® database and to analyze its utility. METHODS: We accumulated intraoperative information from 27 brain tumor patients who underwent resection surgery. First, the risk rank for postoperative paralysis was set according to the attenuation rate and amplitude width of the motor evoked potential (MEP). Then, the MEP and navigation log data were combined and plotted on an intraoperative magnetic resonance image of the individual brain. Finally, statistical parametric mapping (SPM) transformation was performed to generate a standard brain risk map of postoperative paralysis. Additionally, we determined the anatomical high-risk areas using atlases and analyzed the relationship with each set risk rank. RESULTS: The average distance between the navigation log corresponding to each MEP risk rank and the anatomical high-risk area differed significantly between the with postoperatively paralyzed and without postoperatively paralyzed groups, except for "safe." Furthermore, no excessive deformation was observed resulting from SPM conversion to create the standard brain risk map. There were cases in which no postoperative paralysis occurred even when MEP decreased intraoperatively, and vice versa. CONCLUSION: The time synchronization reliability of the study data is very high. Therefore, our created risk map can be reported as being functional at indicating the risk areas. Our results suggest that the statistical risks of postoperative complications can be presented for each area where brain surgery is to be performed. In the future, it will be possible to provide surgical navigation with intraoperative support that reflects the risk maps created.
Authors: Junichi Tokuda; Gregory S Fischer; Xenophon Papademetris; Ziv Yaniv; Luis Ibanez; Patrick Cheng; Haiying Liu; Jack Blevins; Jumpei Arata; Alexandra J Golby; Tina Kapur; Steve Pieper; Everette C Burdette; Gabor Fichtinger; Clare M Tempany; Nobuhiko Hata Journal: Int J Med Robot Date: 2009-12 Impact factor: 2.547
Authors: Danielle D Langeloo; Arjan Lelivelt; H Louis Journée; Robert Slappendel; Marinus de Kleuver Journal: Spine (Phila Pa 1976) Date: 2003-05-15 Impact factor: 3.468