Optimal route planning for image-guided EBUS bronchoscopy.


Journal

Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250

Informations de publication

Date de publication:
09 2019
Historique:
received: 08 04 2019
revised: 16 07 2019
accepted: 16 07 2019
pubmed: 31 7 2019
medline: 10 9 2020
entrez: 31 7 2019
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 31362107
pii: S0010-4825(19)30238-0
doi: 10.1016/j.compbiomed.2019.103361
pmc: PMC6820695
mid: NIHMS1536359
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

103361

Subventions

Organisme : NCI NIH HHS
ID : R01 CA151433
Pays : United States

Informations de copyright

Copyright © 2019 Elsevier Ltd. All rights reserved.

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Auteurs

Xiaonan Zang (X)

School of Electrical Engineering and Computer Science, USA; EDDA Technologies, Princeton, NJ, 08540, USA.

Jason D Gibbs (JD)

School of Electrical Engineering and Computer Science, USA; X-Nav Technologies, Lansdale, PA, 19446, USA.

Ronnarit Cheirsilp (R)

School of Electrical Engineering and Computer Science, USA; Broncus Medical, San Jose, CA, USA.

Patrick D Byrnes (PD)

School of Electrical Engineering and Computer Science, USA.

Jennifer Toth (J)

Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Penn State University, University Park and Hershey, PA, USA.

Rebecca Bascom (R)

Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Penn State University, University Park and Hershey, PA, USA.

William E Higgins (WE)

School of Electrical Engineering and Computer Science, USA. Electronic address: weh2@psu.edu.

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Classifications MeSH