Zongchao Yi1,2, Bingwei He1,2, Zhen Deng3,4, Yuqing Liu5,2, Shengyue Huang5,2, Wenyao Hong5,2. 1. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, People's Republic of China. 2. Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, People's Republic of China. 3. School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, People's Republic of China. zdeng@fzu.edu.cn. 4. Fujian Engineering Research Center of Joint Intelligent Medical Engineering, Fuzhou, People's Republic of China. zdeng@fzu.edu.cn. 5. Department of Neurosurgery, Fujian Provincial Hospital, Fuzhou, People's Republic of China.
Abstract
PURPOSE: This work exploits virtual reality technique to analyse and optimize the preoperative planning of freehand external ventricular drain (EVD) insertion. Based on the three-dimensional (3D) virtual brain models, neurosurgeons can directly observe the anatomical landmarks and complete the simulated EVD insertion. Simulation data is used to optimize preoperative planning parameters to ensure the surgical performance. METHODS: We used the computed tomography (CT) scans to construct the 3D virtual brain models. A group of EVD insertions were simulated by inserting virtual catheters at different entry points. The key parameters including the location of entry point, the catheter orientation, the catheter tip position on lateral ventricles, and the insertion depth were recorded. A data analysis method was then applied to optimize these parameters, resulting in the optimal parameters for the EVD insertion. RESULTS: When the lateral distance of entry point ranged from 2.5 to 3 cm, the success rate of 204 cases was 97.79%, which was higher than that of the classic method (59.52%). The optimal insertion angle towards the sagittal plane ranged from 10.46° to 12.73°. To prevent penetrating the lateral ventricles, the insertion depth was optimized to be 3.28 to 4.58 cm. CONCLUSIONS: The proposed data analysis method is helpful to optimize the key parameters of the preoperative planning, and provides useful references for neurosurgeons to perform the freehand EVD insertion. The EVD insertion experiments on 3D printing model had a success rate of 93.75%, which verified the effectiveness of the data analysis.
PURPOSE: This work exploits virtual reality technique to analyse and optimize the preoperative planning of freehand external ventricular drain (EVD) insertion. Based on the three-dimensional (3D) virtual brain models, neurosurgeons can directly observe the anatomical landmarks and complete the simulated EVD insertion. Simulation data is used to optimize preoperative planning parameters to ensure the surgical performance. METHODS: We used the computed tomography (CT) scans to construct the 3D virtual brain models. A group of EVD insertions were simulated by inserting virtual catheters at different entry points. The key parameters including the location of entry point, the catheter orientation, the catheter tip position on lateral ventricles, and the insertion depth were recorded. A data analysis method was then applied to optimize these parameters, resulting in the optimal parameters for the EVD insertion. RESULTS: When the lateral distance of entry point ranged from 2.5 to 3 cm, the success rate of 204 cases was 97.79%, which was higher than that of the classic method (59.52%). The optimal insertion angle towards the sagittal plane ranged from 10.46° to 12.73°. To prevent penetrating the lateral ventricles, the insertion depth was optimized to be 3.28 to 4.58 cm. CONCLUSIONS: The proposed data analysis method is helpful to optimize the key parameters of the preoperative planning, and provides useful references for neurosurgeons to perform the freehand EVD insertion. The EVD insertion experiments on 3D printing model had a success rate of 93.75%, which verified the effectiveness of the data analysis.
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