Peer-Reviewed Journal Details
Mandatory Fields
Nardelli, Pietro; Jaeger, Alexander; O’Shea, Conor; Khan, Kashif A.; Kennedy, Marcus P.; Cantillon-Murphy, Pádraig
International Journal Of Computer Assisted Radiology And Surgery
Pre-clinical validation of virtual bronchoscopy using 3D Slicer
WOS: 5 ()
Optional Fields
Virtual bronchoscopy Computed tomography Airway segmentation 3D Slicer
Lung cancer still represents the leading cause of cancer-related death, and the long-term survival rate remains low. Computed tomography (CT) is currently the most common imaging modality for lung diseases recognition. The purpose of this work was to develop a simple and easily accessible virtual bronchoscopy system to be coupled with a customized electromagnetic (EM) tracking system for navigation in the lung and which requires as little user interaction as possible, while maintaining high usability. The proposed method has been implemented as an extension to the open-source platform, 3D Slicer. It creates a virtual reconstruction of the airways starting from CT images for virtual navigation. It provides tools for pre-procedural planning and virtual navigation, and it has been optimized for use in combination with a of freedom EM tracking sensor. Performance of the algorithm has been evaluated in ex vivo and in vivo testing. During ex vivo testing, nine volunteer physicians tested the implemented algorithm to navigate three separate targets placed inside a breathing pig lung model. In general, the system proved easy to use and accurate in replicating the clinical setting and seemed to help choose the correct path without any previous experience or image analysis. Two separate animal studies confirmed technical feasibility and usability of the system. This work describes an easily accessible virtual bronchoscopy system for navigation in the lung. The system provides the user with a complete set of tools that facilitate navigation towards user-selected regions of interest. Results from ex vivo and in vivo studies showed that the system opens the way for potential future work with virtual navigation for safe and reliable airway disease diagnosis.
Grant Details