Image-based global registration system for bronchoscopy guidance

摘要

Previous studies have shown that bronchoscopy guidance systems improve accuracy and reduce skill variation among physicians during bronchoscopy. In the past, we presented an image-based bronchoscopy guidance system that has been extensively validated in live bronchoscopic procedures. However, this system cannot actively recover from adverse events, such as patient coughing or dynamic airway collapses. After such events, the bronchoscope position is recovered only by moving back to a previously seen and easily identifiable bifurcation such as the main carina. Furthermore, the system requires an attending technician to closely follow the physician's movement of the bronchoscope to avoid misguidance. Also, when the physician is forced to advance the bronchoscope across multiple bifurcations, the system is not able to detect faulty maneuvers. We propose two system-level solutions. The first solution is a system-level guidance strategy that incorporates a global-registration algorithm to provide the physician with updated navigational and guidance information during bronchoscopy. The system can handle general navigation to a region of interest (ROI), as well as adverse events, and it requires minimal commands so that it can be directly controlled by the physician. The second solution visualizes the global picture of all the bifurcations and their relative orientations in advance and suggests the maneuvers needed by the bronchoscope to approach the ROI. Guided bronchoscopy results using human airway-tree phantoms demonstrate the potential of the two solutions.