Evidence map›Paper›PMID 40061857›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2025

Two-phase radial endobronchial ultrasound bronchoscopy registration.

Wennan Zhao, Trevor Kuhlengel, Qi Chang, Vahid Daneshpajooh, Yuxuan He, Austin Kao, Rebecca Bascom, Danish Ahmad, Yu Maw Htwe, Jennifer Toth and 4 more

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Wennan ZhaoPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-3153-5134
Trevor KuhlengelPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-0669-4627
Qi ChangPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.ORCID https://orcid.org/0009-0004-7400-9849
Vahid DaneshpajoohPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.
Yuxuan HePenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.
Austin KaoPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.
Rebecca BascomPenn State University, College of Medicine, Hershey, Pennsylvania, United States.ORCID https://orcid.org/0000-0001-5875-3476
Danish AhmadPenn State University, College of Medicine, Hershey, Pennsylvania, United States.
Yu Maw HtwePenn State University, College of Medicine, Hershey, Pennsylvania, United States.
Jennifer TothPenn State University, College of Medicine, Hershey, Pennsylvania, United States.
Thomas SchaerUniversity of Pennsylvania, Department of Clinical Studies New Bolton Center, Philadelphia, Pennsylvania, United States.
Leslie BrewerUniversity of Pennsylvania, Department of Clinical Studies New Bolton Center, Philadelphia, Pennsylvania, United States.
Rachel HilliardUniversity of Pennsylvania, Department of Clinical Studies New Bolton Center, Philadelphia, Pennsylvania, United States.ORCID https://orcid.org/0000-0002-6836-0024
William E HigginsPenn State University, School of Electrical Engineering and Computer Science, University Park, Pennsylvania, United States.ORCID https://orcid.org/0000-0003-4781-9374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Lung cancer remains the leading cause of cancer death. This has brought about a critical need for managing peripheral regions of interest (ROIs) in the lungs, be it for cancer diagnosis, staging, or treatment. The state-of-the-art approach for assessing peripheral ROIs involves bronchoscopy. To perform the procedure, the physician first navigates the bronchoscope to a preplanned airway, aided by an assisted bronchoscopy system. They then confirm an ROI's specific location and perform the requisite clinical task. Many ROIs, however, are extraluminal and invisible to the bronchoscope's field of view. For such ROIs, current practice dictates using a supplemental imaging method, such as fluoroscopy, cone-beam computed tomography (CT), or radial endobronchial ultrasound (R-EBUS), to gather additional ROI location information. Unfortunately, fluoroscopy and cone-beam CT require substantial radiation and lengthen procedure time. As an alternative, R-EBUS is a safer real-time option involving no radiation. Regrettably, existing assisted bronchoscopy systems offer no guidance for R-EBUS confirmation, forcing the physician to resort to an unguided guess-and-check approach for R-EBUS probe placement-an approach that can produce R-EBUS placement errors exceeding 30 deg, an error that can result in missing many ROIs. Thus, because of physician skill variations, biopsy success rates using R-EBUS for ROI confirmation have varied greatly from 31% to 80%. This situation obliges the physician to turn to a radiation-based modality to gather sufficient information for ROI confirmation. We propose a two-phase registration method that provides guidance for R-EBUS probe placement. Approach: After the physician navigates the bronchoscope to the airway near a target ROI, the two-phase registration method begins by registering a virtual bronchoscope to the real bronchoscope. A virtual 3D R-EBUS probe model is then registered to the real R-EBUS probe shape depicted in the bronchoscopic video using an iterative region-based alignment method drawing on a level-set-based optimization. This synchronizes the guidance system to the target ROI site. The physician can now perform the R-EBUS scan to confirm the ROI. Results: We validated the method's efficacy for localizing extraluminal ROIs with a series of three studies. First, for a controlled phantom study, we observed that the mean accumulated position and direction errors (accounting for both registration phases) were 1.94 mm and 3.74 deg (equivalent to 1.30 mm position error for a 20 mm biopsy needle), respectively. Next, for a live animal study, these errors were 2.81 mm and 4.79 deg (2.41 mm biopsy needle error), respectively. For 100% of the ROIs considered in these two studies, the method enabled visualization of an ROI via R-EBUS in under 3 min per ROI. Finally, initial operating-room tests on lung cancer patients indicated the method's efficacy, functionality, efficiency, and safety under standard clinical conditions. Conclusions: The method offers a quick, low-cost, radiation-free approach for examining peripheral extraluminal ROIs using R-EBUS. Although our studies focused on R-EBUS as the supplemental working channel instrument, the proposed method has general applicability to any clinical bronchoscopic task requiring a working channel instrument. Thus, the method has the potential to improve the efficiency and efficacy of bronchoscopic procedures for lung cancer patients.

Indexed as

bronchoscopyendobronchial ultrasoundimage-guided bronchoscopyimage-guided surgery systemsimage registrationlung cancermultimodal imagingrobotics-assisted bronchoscopyworking channel instruments

Identifiers

PMID40061857
PMCPMC11889395

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.