The Feasibility and Accuracy of Holographic Navigation with Laser Crosshair Simulator Registration on a Mixed-Reality Display
Ziyu Qi,
Haitao Jin,
Qun Wang,
Zhichao Gan,
Ruochu Xiong,
Shiyu Zhang,
Minghang Liu,
Jingyue Wang,
Xinyu Ding,
Xiaolei Chen,
Jiashu Zhang,
Christopher Nimsky,
Miriam H. A. Bopp
Affiliations
Ziyu Qi
Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany
Haitao Jin
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Qun Wang
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Zhichao Gan
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Ruochu Xiong
Department of Neurosurgery, Division of Medicine, Graduate School of Medical Sciences, Kanazawa University, Takara-machi 13-1, Kanazawa 920-8641, Japan
Shiyu Zhang
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Minghang Liu
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Jingyue Wang
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Xinyu Ding
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Xiaolei Chen
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Jiashu Zhang
Department of Neurosurgery, First Medical Center of Chinese PLA General Hospital, Beijing 100853, China
Christopher Nimsky
Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany
Miriam H. A. Bopp
Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany
Addressing conventional neurosurgical navigation systems’ high costs and complexity, this study explores the feasibility and accuracy of a simplified, cost-effective mixed reality navigation (MRN) system based on a laser crosshair simulator (LCS). A new automatic registration method was developed, featuring coplanar laser emitters and a recognizable target pattern. The workflow was integrated into Microsoft’s HoloLens-2 for practical application. The study assessed the system’s precision by utilizing life-sized 3D-printed head phantoms based on computed tomography (CT) or magnetic resonance imaging (MRI) data from 19 patients (female/male: 7/12, average age: 54.4 ± 18.5 years) with intracranial lesions. Six to seven CT/MRI-visible scalp markers were used as reference points per case. The LCS-MRN’s accuracy was evaluated through landmark-based and lesion-based analyses, using metrics such as target registration error (TRE) and Dice similarity coefficient (DSC). The system demonstrated immersive capabilities for observing intracranial structures across all cases. Analysis of 124 landmarks showed a TRE of 3.0 ± 0.5 mm, consistent across various surgical positions. The DSC of 0.83 ± 0.12 correlated significantly with lesion volume (Spearman rho = 0.813, p < 0.001). Therefore, the LCS-MRN system is a viable tool for neurosurgical planning, highlighting its low user dependency, cost-efficiency, and accuracy, with prospects for future clinical application enhancements.
