ArticleComputers in biology and medicine2019
Optimal route planning for image-guided EBUS bronchoscopy.
Article in Computers in biology and medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Balancing Accuracy, Safety, and Cost in Mediastinal Diagnostics: A Systematic Review of EBUS and Mediastinoscopy in NSCLC.Healthcare (Basel, Switzerland) · 2025Review
- Two-phase radial endobronchial ultrasound bronchoscopy registration.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using Deep Learning.Journal of imaging · 2024Article
- Endobronchial Ultrasound Image Simulation for Image-Guided Bronchoscopy.IEEE transactions on bio-medical engineering · 2023Article
- Efficient procedure planning for comprehensive lymph node staging bronchoscopy.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Multimodal Registration for Image-Guided EBUS Bronchoscopy.Journal of imaging · 2022Article
- Three-dimensional catheter navigation of airways using continuous-sweep limited angle fluoroscopy on a C-arm.Journal of medical imaging (Bellingham, Wash.) · 2021Article
- Image-guided EBUS bronchoscopy system for lung-cancer staging.Informatics in medicine unlocked · 2021Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The staging of the central-chest lymph nodes is a major lung-cancer management procedure. To perform a staging procedure, the physician first uses a patient's 3D X-ray computed-tomography (CT) chest scan to interactively plan airway routes leading to selected target lymph nodes. Next, using an integrated EBUS bronchoscope (EBUS = endobronchial ultrasound), the physician uses videobronchoscopy to navigate through the airways toward a target node's general vicinity and then invokes EBUS to localize the node for biopsy. Unfortunately, during the procedure, the physician has difficulty in translating the preplanned airway routes into safe, effective biopsy sites. We propose an automatic route-planning method for EBUS bronchoscopy that gives optimal localization of safe, effective nodal biopsy sites. To run the method, a 3D chest model is first computed from a patient's chest CT scan. Next, an optimization method derives feasible airway routes that enables maximal tissue sampling of target lymph nodes while safely avoiding major blood vessels. In a lung-cancer patient study entailing 31 nodes (long axis range: [9.0 mm, 44.5 mm]), 25/31 nodes yielded safe airway routes having an optimal tissue sample size = 8.4 mm (range: [1.0 mm, 18.6 mm]) and sample adequacy = 0.42 (range: [0.05, 0.93]). Quantitative results indicate that the method potentially enables successful biopsies in essentially 100% of selected lymph nodes versus the 70-94% success rate of other approaches. The method also potentially facilitates adequate tissue biopsies for nearly 100% of selected nodes, as opposed to the 55-77% tissue adequacy rates of standard methods. The remaining nodes did not yield a safe route within the preset safety-margin constraints, with 3 nodes never yielding a route even under the most lenient safety-margin conditions. Thus, the method not only helps determine effective airway routes and expected sample quality for nodal biopsy, but it also helps point out situations where biopsy may not be advisable. We also demonstrate the methodology in an image-guided EBUS bronchoscopy system, used successfully in live lung-cancer patient studies. During a live procedure, the method provides dynamic real-time sample size visualization in an enhanced virtual bronchoscopy viewer. In this way, the physician vividly sees the most promising biopsy sites along the airway walls as the bronchoscope moves through the airways.
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