Evidence map›Paper›PMID 35819999›Full record

ArticleIEEE transactions on bio-medical engineering2023

Endobronchial Ultrasound Image Simulation for Image-Guided Bronchoscopy.

Wennan Zhao, Danish Ahmad, Jennifer Toth, Rebecca Bascom, William E Higgins

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Two-phase radial endobronchial ultrasound bronchoscopy registration.Journal of medical imaging (Bellingham, Wash.) · 2025
    Article
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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

5 authors.

Wennan Zhao
Danish Ahmad
Jennifer Toth
Rebecca Bascom
William E Higgins

Funding

Multimodal Image-Guided Intervention System for Lung-Cancer Diagnosis and StagingR01CA151433 · NCI · PENNSYLVANIA STATE UNIVERSITY, THE · PI HIGGINS, WILLIAM EVAN · 2010 to 2022
$3.7M
NCI NIH HHS R01 CA151433
6 · The paper itself

Abstract

BACKGROUND/

objectiveAccurate disease diagnosis and staging are essential for patients suspected of having lung cancer. The state-of-the-art minimally invasive tools used by physicians to perform these operations are bronchoscopy, for navigating the lung airways, and endobronchial ultrasound (EBUS), for localizing suspect extraluminal cancer lesions. While new image-guided systems enable accurate bronchoscope navigation close to a lesion, no means exists for guiding the final EBUS localization of an extraluminal lesion. We propose an EBUS simulation method to assist with EBUS localization.

methodsThe method draws on a patient's chest computed-tomography (CT) scan to model the ultrasound signal propagation through the tissue media. The method, which is suitable for simulating EBUS images for both radial-probe and convex-probe EBUS devices, entails three steps: 1) image preprocessing, which generates a 2D CT equivalent of the EBUS scan plane; 2) EBUS scan-line computation, which models ultrasound transmission to map the CT plane into a preliminary simulated EBUS image; and 3) image post-processing, which increases realism by introducing simulated EBUS imaging effects and artifacts.

resultsResults show that the method produces simulated EBUS images that strongly resemble images generated live by a real device and compares favorably to an existing ultrasound simulation method. It also produces images at a rate greater than real time (i.e., 53 frames/sec). We also demonstrate a successful integration of the method into an image-guided EBUS bronchoscopy system. CONCLUSION/SIGNIFICANCE: The method is effective and practical for procedure planning/preview and follow-on live guidance of EBUS bronchoscopy.

Indexed as

BronchoscopyLung NeoplasmsEndosonographyHumansLungUltrasonography

Identifiers

PMID35819999
PMCPMC9927880

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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.