Computer-based system for the virtual-endoscopic guidance of bronchoscopy

Abstract

The standard procedure for diagnosing lung cancer involves two stages: three-dimensional (3D) computed-tomography (CT) image assessment, followed by interventional bronchoscopy. In general, the physician has no link between the 3D CT image assessment results and the follow-on bronchoscopy. Thus, the physician essentially performs bronchoscopic biopsy of suspect cancer sites blindly. We have devised a computer-based system that greatly augments the physician's vision during bronchoscopy. The system uses techniques from computer graphics and computer vision to enable detailed 3D CT procedure planning and follow-on image-guided bronchoscopy. The procedure plan is directly linked to the bronchoscope procedure, through a live registration and fusion of the 3D CT data and bronchoscopic video. During a procedure, the system provides many visual tools, fused CT-video data, and quantitative distance measures; this gives the physician considerable visual feedback on how to maneuver the bronchoscope and where to insert the biopsy needle. Central to the system is a CT-video registration technique, based on normalized mutual information. Several sets of results verify the efficacy of the registration technique. In addition, we present a series of test results for the complete system for phantoms, animals, and human lung-cancer patients. The results indicate that not only is the variation in skill level between different physicians greatly reduced by the system over the standard procedure, but that biopsy effectiveness increases.

3D CT-Video Fusion for Image-Guided Bronchoscopy

“…To facilitate one-to-one pixel-based (x, y) registration between these two cameras, we first measure off-line (before a procedure) the focal length and field-of-view dimensions of the bronchoscope. These quantities are easily measured, per [46,47]. The measured quantities are then used to compute endoluminal renderings I CT (x, y) for the virtual-world camera.…”

“…where L is the intensity of the bronchoscope's light source, θ s is the angle between the light source and p's surface normal, R is the distance from the light source to p, and σ is a proportionality factor that takes into account airway-surface albedo and the bronchoscope's device characteristics [46]. The final 2D point I V (x, y) then results from a standard 3D-to-2D transformation of I(p).…”

“…Finally, Section 3.3 describes how fusion is accomplished between the CT and video data. For this paper, we follow the notational conventions of [46].…”

“…Note that (2) is a model for a video frame I V (x, y) (we do not have control over this), while (3) is our controllable implementation of the CT-based camera producing frames I CT (x, y). Extensive results for controlled and real tests, given in [46], have validated the efficacy of these models.…”

“…Reference [46] gives further discussion on the quantities above. Figure 6 gives an example of the quantities used in the optimization.…”