Bowei Zeng1, Fanle Meng1, Hui Ding1, Guangzhi Wang2. 1. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, People's Republic of China. 2. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, People's Republic of China. wgz-dea@tsinghua.edu.cn.
Abstract
PURPOSE: Using existing stereoelectroencephalography (SEEG) electrode implantation surgical robot systems, it is difficult to intuitively validate registration accuracy and display the electrode entry points (EPs) and the anatomical structure around the electrode trajectories in the patient space to the surgeon. This paper proposes a prototype system that can realize video see-through augmented reality (VAR) and spatial augmented reality (SAR) for SEEG implantation. The system helps the surgeon quickly and intuitively confirm the registration accuracy, locate EPs and visualize the internal anatomical structure in the image space and patient space. METHODS: We designed and developed a projector-camera system (PCS) attached to the distal flange of a robot arm. First, system calibration is performed. Second, the PCS is used to obtain the point clouds of the surface of the patient's head, which are utilized for patient-to-image registration. Finally, VAR is produced by merging the real-time video of the patient and the preoperative three-dimensional (3D) operational planning model. In addition, SAR is implemented by projecting the planning electrode trajectories and local anatomical structure onto the patient's scalp. RESULTS: The error of registration, the electrode EPs and the target points are evaluated on a phantom. The fiducial registration error is [Formula: see text] mm (max 1.22 mm), and the target registration error is [Formula: see text] mm (max 1.18 mm). The projection overlay error is [Formula: see text] mm, and the TP error after the pre-warped projection is [Formula: see text] mm. The TP error caused by a surgeon's viewpoint deviation is also evaluated. CONCLUSION: The presented system can help surgeons quickly verify registration accuracy during SEEG procedures and can provide accurate EP locations and internal structural information to the surgeon. With more intuitive surgical information, the surgeon may have more confidence and be able to perform surgeries with better outcomes.
PURPOSE: Using existing stereoelectroencephalography (SEEG) electrode implantation surgical robot systems, it is difficult to intuitively validate registration accuracy and display the electrode entry points (EPs) and the anatomical structure around the electrode trajectories in the patient space to the surgeon. This paper proposes a prototype system that can realize video see-through augmented reality (VAR) and spatial augmented reality (SAR) for SEEG implantation. The system helps the surgeon quickly and intuitively confirm the registration accuracy, locate EPs and visualize the internal anatomical structure in the image space and patient space. METHODS: We designed and developed a projector-camera system (PCS) attached to the distal flange of a robot arm. First, system calibration is performed. Second, the PCS is used to obtain the point clouds of the surface of the patient's head, which are utilized for patient-to-image registration. Finally, VAR is produced by merging the real-time video of the patient and the preoperative three-dimensional (3D) operational planning model. In addition, SAR is implemented by projecting the planning electrode trajectories and local anatomical structure onto the patient's scalp. RESULTS: The error of registration, the electrode EPs and the target points are evaluated on a phantom. The fiducial registration error is [Formula: see text] mm (max 1.22 mm), and the target registration error is [Formula: see text] mm (max 1.18 mm). The projection overlay error is [Formula: see text] mm, and the TP error after the pre-warped projection is [Formula: see text] mm. The TP error caused by a surgeon's viewpoint deviation is also evaluated. CONCLUSION: The presented system can help surgeons quickly verify registration accuracy during SEEG procedures and can provide accurate EP locations and internal structural information to the surgeon. With more intuitive surgical information, the surgeon may have more confidence and be able to perform surgeries with better outcomes.
Authors: Vejay N Vakharia; Rachel Sparks; Aidan G O'Keeffe; Roman Rodionov; Anna Miserocchi; Andrew McEvoy; Sebastien Ourselin; John Duncan Journal: Epilepsia Date: 2017-03-06 Impact factor: 5.864
Authors: Francesco Cardinale; Massimo Cossu; Laura Castana; Giuseppe Casaceli; Marco Paolo Schiariti; Anna Miserocchi; Dalila Fuschillo; Alessio Moscato; Chiara Caborni; Gabriele Arnulfo; Giorgio Lo Russo Journal: Neurosurgery Date: 2013-03 Impact factor: 4.654
Authors: Marta Kersten-Oertel; Ian Gerard; Simon Drouin; Kelvin Mok; Denis Sirhan; David S Sinclair; D Louis Collins Journal: Int J Comput Assist Radiol Surg Date: 2015-02-26 Impact factor: 2.924
Authors: Robert Krempien; Harald Hoppe; Lüder Kahrs; Sascha Daeuber; Oliver Schorr; Georg Eggers; Marc Bischof; Marc W Munter; Juergen Debus; Wolfgang Harms Journal: Int J Radiat Oncol Biol Phys Date: 2007-12-31 Impact factor: 7.038
Authors: Zoltán Bárdosi; Christian Plattner; Yusuf Özbek; Thomas Hofmann; Srdjan Milosavljevic; Volker Schartinger; Wolfgang Freysinger Journal: Int J Comput Assist Radiol Surg Date: 2019-09-11 Impact factor: 2.924
Authors: Marko Švaco; Ivan Stiperski; Domagoj Dlaka; Filip Šuligoj; Bojan Jerbić; Darko Chudy; Marina Raguž Journal: Front Neurorobot Date: 2020-10-23 Impact factor: 2.650