Share Email Print
cover

Proceedings Paper

Planning and visualization methods for effective bronchoscopic target localization
Author(s): Jason D. Gibbs; Pinyo Taeprasarsit; William E. Higgins
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Bronchoscopic biopsy of lymph nodes is an important step in staging lung cancer. Lymph nodes, however, lie behind the airway walls and are near large vascular structures - all of these structures are hidden from the bronchoscope's field of view. Previously, we had presented a computer-based virtual bronchoscopic navigation system that provides reliable guidance for bronchoscopic sampling. While this system offers a major improvement over standard practice, bronchoscopists told us that target localization- lining up the bronchoscope before deploying a needle into the target - can still be challenging. We therefore address target localization in two distinct ways: (1) automatic computation of an optimal diagnostic sampling pose for safe, effective biopsies, and (2) a novel visualization of the target and surrounding major vasculature. The planning determines the final pose for the bronchoscope such that the needle, when extended from the tip, maximizes the tissue extracted. This automatically calculated local pose orientation is conveyed in endoluminal renderings by a 3D arrow. Additional visual cues convey obstacle locations and target depths-of-sample from arbitrary instantaneous viewing orientations. With the system, a physician can freely navigate in the virtual bronchoscopic world perceiving the depth-of-sample and possible obstacle locations at any endoluminal pose, not just one pre-determined optimal pose. We validated the system using mediastinal lymph nodes in eleven patients. The system successfully planned for 20 separate targets in human MDCT scans. In particular, given the patient and bronchoscope constraints, our method found that safe, effective biopsies were feasible in 16 of the 20 targets; the four remaining targets required more aggressive safety margins than a "typical" target. In all cases, planning computation took only a few seconds, while the visualizations updated in real time during bronchoscopic navigation.

Paper Details

Date Published: 17 February 2012
PDF: 13 pages
Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83161H (17 February 2012); doi: 10.1117/12.910913
Show Author Affiliations
Jason D. Gibbs, Broncus Technologies, Inc. (United States)
The Pennsylvania State Univ. (United States)
Pinyo Taeprasarsit, Silpakorn Univ. (Thailand)
The Pennsylvania State Univ. (United States)
William E. Higgins, The Pennsylvania State Univ. (United States)


Published in SPIE Proceedings Vol. 8316:
Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Kenneth H. Wong, Editor(s)

© SPIE. Terms of Use
Back to Top