Literature DB >> 30955195

Integrated datasets of normalized brain with functional localization using intra-operative electrical stimulation.

Manabu Tamura1,2, Ikuma Sato3, Takashi Maruyama4,5, Kazuma Ohshima3, Jean-François Mangin6, Masayuki Nitta4,5, Taiichi Saito5, Hiroyuki Yamada4, Shinji Minami4, Ken Masamune4, Takakazu Kawamata5, Hiroshi Iseki4, Yoshihiro Muragaki4,5.   

Abstract

PURPOSE: The purpose of this study was to transform brain mapping data into a digitized intra-operative MRI and integrated brain function dataset for predictive glioma surgery considering tumor resection volume, as well as the intra-operative and postoperative complication rates.
METHODS: Brain function data were transformed into digitized localizations on a normalized brain using a modified electric stimulus probe after brain mapping. This normalized brain image with functional information was then projected onto individual patient's brain images including predictive brain function data.
RESULTS: Log data were successfully acquired using a medical device integrated into intra-operative MR images, and digitized brain function was converted to a normalized brain data format in 13 cases. For the electrical stimulation positions in which patients showed speech arrest (SA), speech impairment (SI), motor and sensory responses during cortical mapping processes in awake craniotomy, the data were tagged, and the testing task and electric current for the stimulus were recorded. There were 13 SA, 7 SI, 8 motor and 4 sensory responses (32 responses) in total. After evaluation of transformation accuracy in 3 subjects, the first transformation from intra- to pre-operative MRI using non-rigid registration was calculated as 2.6 ± 1.5 and 2.1 ± 0.9 mm, examining neighboring sulci on the electro-stimulator position and the cortex surface near each tumor, respectively; the second transformation from pre-operative to normalized brain was 1.7 ± 0.8 and 1.4 ± 0.5 mm, respectively, representing acceptable accuracy.
CONCLUSION: This image integration and transformation method for brain normalization should facilitate practical intra-operative brain mapping. In the future, this method may be helpful for pre-operatively or intra-operatively predicting brain function.

Entities:  

Keywords:  Brain mapping; Digitization; Normalization; Predictive glioma surgery; Transformation

Mesh:

Year:  2019        PMID: 30955195     DOI: 10.1007/s11548-019-01957-7

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  28 in total

1.  The guidelines for awake craniotomy guidelines committee of the Japan awake surgery conference.

Authors:  Takamasa Kayama
Journal:  Neurol Med Chir (Tokyo)       Date:  2012       Impact factor: 1.742

Review 2.  A framework to study the cortical folding patterns.

Authors:  J-F Mangin; D Rivière; A Cachia; E Duchesnay; Y Cointepas; D Papadopoulos-Orfanos; P Scifo; T Ochiai; F Brunelle; J Régis
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

3.  Intraoperative subcortical language tract mapping guides surgical removal of gliomas involving speech areas.

Authors:  Lorenzo Bello; Marcello Gallucci; Marica Fava; Giorgio Carrabba; Carlo Giussani; Francesco Acerbi; Pietro Baratta; Valeria Songa; Valeria Conte; Vincenzo Branca; Nino Stocchetti; Costanza Papagno; Sergio Maria Gaini
Journal:  Neurosurgery       Date:  2007-01       Impact factor: 4.654

4.  Improvement of a retinal blood vessel segmentation method using the Insight Segmentation and Registration Toolkit (ITK).

Authors:  M Martinez-Perez; Alun D Hughes; Simon A Thom; Kim H Parker
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2007

Review 5.  Selection of intraoperative tasks for awake mapping based on relationships between tumor location and functional networks.

Authors:  Alejandro Fernández Coello; Sylvie Moritz-Gasser; Juan Martino; Matteo Martinoni; Ryosuke Matsuda; Hugues Duffau
Journal:  J Neurosurg       Date:  2013-09-20       Impact factor: 5.115

6.  Efficient and robust nonlocal means denoising of MR data based on salient features matching.

Authors:  Antonio Tristán-Vega; Verónica García-Pérez; Santiago Aja-Fernández; Carl-Fredrik Westin
Journal:  Comput Methods Programs Biomed       Date:  2011-09-08       Impact factor: 5.428

Review 7.  VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

Authors:  Hao Chen; Qi Dou; Lequan Yu; Jing Qin; Pheng-Ann Heng
Journal:  Neuroimage       Date:  2017-04-23       Impact factor: 6.556

Review 8.  Proposal of an optimized strategy for intraoperative testing of speech and language during awake mapping.

Authors:  Emmanuel Mandonnet; Silvio Sarubbo; Hugues Duffau
Journal:  Neurosurg Rev       Date:  2016-05-19       Impact factor: 3.042

9.  Low Rate of Intraoperative Seizures During Awake Craniotomy in a Prospective Cohort with 374 Supratentorial Brain Lesions: Electrocorticography Is Not Mandatory.

Authors:  Julien Boetto; Luc Bertram; Gérard Moulinié; Guillaume Herbet; Sylvie Moritz-Gasser; Hugues Duffau
Journal:  World Neurosurg       Date:  2015-08-14       Impact factor: 2.104

Review 10.  Strategy of Surgical Resection for Glioma Based on Intraoperative Functional Mapping and Monitoring.

Authors:  Manabu Tamura; Yoshihiro Muragaki; Taiichi Saito; Takashi Maruyama; Masayuki Nitta; Shunsuke Tsuzuki; Hiroshi Iseki; Yoshikazu Okada
Journal:  Neurol Med Chir (Tokyo)       Date:  2015       Impact factor: 1.742

View more
  1 in total

1.  Combining Pre-operative Diffusion Tensor Images and Intraoperative Magnetic Resonance Images in the Navigation Is Useful for Detecting White Matter Tracts During Glioma Surgery.

Authors:  Manabu Tamura; Hiroyuki Kurihara; Taiichi Saito; Masayuki Nitta; Takashi Maruyama; Shunsuke Tsuzuki; Atsushi Fukui; Shunichi Koriyama; Takakazu Kawamata; Yoshihiro Muragaki
Journal:  Front Neurol       Date:  2022-01-20       Impact factor: 4.003

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.