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Numerical Calculation Method for Brain Shift Based on Hydrostatics and Dynamic FEM
| Title: | Numerical Calculation Method for Brain Shift Based on Hydrostatics and Dynamic FEM |
| Authors: | Chen, Xiaoshuai Browse this author | | Shirai, Ryosuke Browse this author | | Masamune, Ken Browse this author | | Tamura, Manabu Browse this author | | Muragaki, Yoshihiro Browse this author | | Sase, Kazuya Browse this author | | Tsujita, Teppei Browse this author | | Konno, Atsushi Browse this author →KAKEN DB |
| Keywords: | Brain shift | | dynamic FEM | | neurosurgery simulation |
| Issue Date: | 18-Apr-2022 |
| Publisher: | IEEE (Institute of Electrical and Electronics Engineers) |
| Journal Title: | IEEE Transactions on Medical Robotics and Bionics |
| Volume: | 4 |
| Issue: | 2 |
| Start Page: | 368 |
| End Page: | 380 |
| Publisher DOI: | 10.1109/TMRB.2022.3168075 |
| Abstract: | 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 x 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. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/88018 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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