マサムネ　ケン   Masamune Ken   正宗　賢    所属   医学研究科 医学研究科 (医学部医学科をご参照ください)    職種   教授
論文種別	原著
言語種別	英語
査読の有無	査読あり
表題	Numerical Calculation Method for Brain Shift Based on Hydrostatics and Dynamic FEM
掲載誌名	正式名：IEEE Transactions on Medical Robotics and Bionics ISSNコード：25763202
掲載区分	国外
出版社	IEEE
巻・号・頁	4(2),pp.368-380
著者・共著者	CHEN Xiaoshuai†, SHIRAI Ryosuke, MASAMUNE Ken, TAMURA Manabu, MURAGAKI Yoshihiro, SASE Kazuya , TSUJITA Teppei , KONNO Atsush
発行年月	2022/04/18
概要	During neurosurgery, brain deformation occurs because of gravity and leakage of the cerebrospinal fluid (CSF), which is referred to as brain shift. Brain shift is a serious problem in neuronavigation because neuronavigation relies on preoperatively taken medical images. This paper presents a brain shift estimation method based on hydrostatics and dynamic FEM, assuming that gravity and leakage of CSF are the main reasons for brain shift. The accuracy of the proposed method was verified via basic experiments conducted using elastic gelatin cubes. In addition, a 3D brain model was created using preoperative medical images of a patient and brain shift estimation simulations were performed. Their accuracy was verified by comparing the simulation results with the actual brain shift during neurosurgery. Assuming that the node in the most anterior position of the frontal lobe and the node in the highest position of the parietal lobe before the brain shift respectively remain in the most anterior position and the highest position even after the brain shift, the corresponding regions before and after the brain shift were searched and the deformations were evaluated. In this error analysis, the maximum estimation error was 4.4 mm. Furthermore, a region of 40 mm × 30 mm in the frontal lobe was chosen as the region of interest (ROI), and the surface errors in the ROI between the intraoperative MRI images and the simulated shifted brain were analyzed. The mean absolute error (MAE) between the surfaces along the z-axis (the direction of gravity) in the ROI was 3.7 mm (maximum absolute error was 8.8 mm). The proposed method was sufficiently simple for computing the brain shift in real-time. The expected contribution of this study toward improving the neuronavigational error and enhancing the safety of neurosurgery will be beneficial for hospitals, especially when the intraoperative MRI cannot be performed. Index Terms—Brain shift, dynamic FEM, neurosurgery simulation
DOI	10.1109/TMRB.2022.3168075