Fusion of MDCT-based endoluminal renderings and endoscopic video

Abstract

Early lung cancer can cause structural and color changes to the airway mucosa. A three-dimensional (3D) multidetector CT (MDCT) chest scan provides 3D structural data for airway walls, but no detailed mucosal information. Conversely, bronchoscopy gives color mucosal information, due to airway-wall inflammation and early cancer formation. Unfortunately, each bronchoscopic video image provides only a limited local view of the airway mucosal surface and no 3D structural/location information. The physician has to mentally correlate the video images with each other and the airway surface data to analyze the airway mucosal structure and color. A fusion of the topographical information from the 3D MDCT data and the color information from the bronchoscopic video enables 3D visualization, navigation, localization, and combined color-topographic analysis of the airways. This paper presents a fast method for topographic airway-mucosal surface fusion of bronchoscopic video with 3D MDCT endoluminal views. Tests were performed on phantom sequences, real bronchoscopy patient video, and associated 3D MDCT scans. Results show that we can effectively accomplish mapping over a continuous sequence of airway images spanning several generations of airways in a few seconds. Real-time navigation and visualization of the combined data was performed. The average surface-point mapping error for a phantom case was estimated to be only on the order of 2 mm for 20 mm diameter airway.