Evidence map›Paper›PMID 35083464›Full record

ArticleATS scholar2021

Teaching Radial Endobronchial Ultrasound with a Three-Dimensional-printed Radial Ultrasound Model.

Anna Ridgers, Jasun Li, Jasamine Coles-Black, Michael Jiang, Gordon Chen, Jason Chuen, Christine F McDonald, Graham Hepworth, Daniel P Steinfort, Louis B Irving and 4 more

Open access · goldAbstract read
In one paragraph

Article in ATS scholar, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 32% of its field
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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Endobronchial Ultrasound Image Simulation for Image-Guided Bronchoscopy.IEEE transactions on bio-medical engineering · 2023
    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 at 6 institutions in 2 countries.

Anna RidgersDepartment of Respiratory and Sleep Medicine.
Jasun Li3dMedLab.
Jasamine Coles-Black3dMedLab.
Michael Jiang3dMedLab.
Gordon Chen3dMedLab.
Jason Chuen3dMedLab.
Christine F McDonaldDepartment of Respiratory and Sleep Medicine.
Graham HepworthInstitute for Breathing and Sleep.
Daniel P SteinfortUniversity of Melbourne, Melbourne, Australia.
Louis B IrvingUniversity of Melbourne, Melbourne, Australia.
Peter WallbridgeUniversity of Melbourne, Melbourne, Australia.
Barton R JenningsDepartment of Respiratory and Sleep Medicine, Monash Health, Melbourne, Australia; and.
Phan NguyenDepartment of Thoracic Medicine, Royal Adelaide Hospital, Adelaide, Australia.
Tracy L LeongDepartment of Respiratory and Sleep Medicine.
The University of Melbourne · AUInstitute for Breathing and Sleep · AUThe Royal Melbourne Hospital · AUMonash Health · AURoyal Adelaide Hospital · AUXLAB (Slovenia) · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPeripheral pulmonary lesion (PPL) incidence is rising because of increased chest imaging sensitivity and frequency. For PPLs suspicious for lung cancer, current clinical guidelines recommend tissue diagnosis. Radial endobronchial ultrasound (R-EBUS) is a bronchoscopic technique used for this purpose. It has been observed that diagnostic yield is impacted by the ability to accurately manipulate the radial probe. However, such skills can be acquired, in part, from simulation training. Three-dimensional (3D) printing has been used to produce training simulators for standard bronchoscopy but has not been specifically used to develop similar tools for R-EBUS.

objectiveWe report the development of a novel ultrasound-compatible, anatomically accurate 3D-printed R-EBUS simulator and evaluation of its utility as a training tool.

methodsComputed tomography images were used to develop 3D-printed airway models with ultrasound-compatible PPLs of "low" and "high" technical difficulty. Twenty-one participants were allocated to two groups matched for prior R-EBUS experience. The intervention group received 15 minutes to pretrain R-EBUS using a 3D-printed model, whereas the nonintervention group did not. Both groups then performed R-EBUS on 3D-printed models and were evaluated using a specifically developed assessment tool.

resultsFor the "low-difficulty" model, the intervention group achieved a higher score (21.5 ± 2.02) than the nonintervention group (17.1 ± 5.7), reflecting 26% improvement in performance (

conclusion3D-printing can be used to develop simulators for R-EBUS education. Training using these models significantly improves procedural performance and is effective in both novice and experienced trainees.

Indexed as

3Dradial endobronchial ultrasoundsimulationtraining

Identifiers

PMID35083464
PMCPMC8787737
OpenAlexW3215024309

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.