Real-Time 3-D Video Reconstruction for Guidance of Transventricular Neurosurgery

Abstract

Neuroendoscopic approach to deep-brain targets imparts deformation of the ventricles and adjacent parenchyma, limiting the accuracy of conventional neuronavigation. We report a method for 3D endoscopic reconstruction and registration via simultaneous localization and mapping (SLAM) for real-time guidance with or without robotic assistance. The aim is to permit augmented video overlay of structures registered from preoperative or intraoperative 3D images within and beyond the endoscopic field of view for more accurate targeting in the presence of deep-brain deformation. Phantom studies were performed to evaluate geometric accuracy and uncertainty in distinct scenarios of limited data (feature sparsity and scene occlusion), demonstrating performance over a broad range of challenges to endoscopic data. Reconstruction and registration accuracy were maintained even with up to 40% loss in feature density or 120° of the visual scene occluded. Overall, the method achieved a high degree of geometric accuracy, with target registration error of 1.02 mm and runtime supporting real-time guidance (3.45 Hz, representing a >16× speedup with SLAM approach compared to previous work). The studies establish essential quantitative performance characteristics and validation that are essential to future translation to clinical studies.