脳神経外科手術トレニングシステム開発のための小脳圧排シミュレーションの研究

  • 長谷川 悠
    神戸大学大学院工学研究科機械工学専攻
  • 安達 和彦
    神戸大学大学院工学研究科機械工学専攻
  • 東 洋平
    神戸大学大学院工学研究科機械工学専攻
  • 藤田 敦史
    神戸大学大学院医学研究科外科系講座脳神経外科学分野
  • 甲村 英二
    神戸大学大学院医学研究科外科系講座脳神経外科学分野
  • 神吉 博
    神戸大学名誉教授

書誌事項

タイトル別名
  • A Study on Cerebellar Retraction Simulation for Developing Neurosurgical Training System
  • ノウ シンケイ ゲカ シュジュツ トレーニング システム カイハツ ノ タメ ノ ショウノウアツハイシミュレーション ノ ケンキュウ

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抄録

This study aims at presenting the biomechanical brain tissue deformation simulation for development of the virtual reality surgical training system using haptic device. In the training system, it is necessary to generate not only visual view of the surgical scene similar to the surgical field but also tactile sensation due to intraoperative interaction between the brain tissue and the surgical instruments (brain spatula, suction, forceps, scissors, etc.). In this paper, the simulation capability for the intraoperative cerebellum tissue deformation due to retraction with brain spatula for the operation on the posterior fossa surgery by using authors'developed three-dimensional finite element model is demonstrated. The illustrative results successfully demonstrate the interaction between the cerebellum tissue and brain spatula. After retracting the tissue, significant surface deformation was obtained toward the retraction direction and deep structures such as root exit zone of the cranial nerves around pons were exposed in the surgical field. In addition, the results that the spatula retraction speed affected the deformation field show the capability of the evaluation of surgical skill level. Furthermore, the cerebellum model consists of the cerebellum, pons, and medulla oblongata was proposed for achieving drastic computation time reduction of the cerebellum tissue retraction simulation. The retraction simulation using the proposed model successfully achieved up to 83% reduction of computation time compared with that using the whole brain model. All results show that the feasibility of the neurosurgical training system based on the biomechanical brain tissue deformation computation. Authors are now working on developing the new three-dimensional brain deformation model for rendering the deformed tissue surface which can be built into the haptic device.

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