Evidence map›Paper›PMID 35344969›Full record

ArticleRespiration; international review of thoracic diseases2022

Accuracy of Pulmonary Nodule Sampling Using Robotic Assisted Bronchoscopy with Shape Sensing, Fluoroscopy, and Radial Endobronchial Ultrasound (The ACCURACY Study).

Jeffrey Thiboutot, A Christine Argento, Jason Akulian, Hans J Lee, Andrew DeMaio, Christopher M Kapp, Momen M Wahidi, Lonny Yarmus

Abstract read
PubMed Publisher
In one paragraph

Article in Respiration; international review of thoracic diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Robotic Bronchoscopy: Review of Three Systems.Life (Basel, Switzerland) · 2023
    Review
  7. Robotic Assisted Bronchoscopy: The Ultimate Solution for Peripheral Pulmonary Nodules?Respiration; international review of thoracic diseases · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Jeffrey ThiboutotDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
A Christine ArgentoDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Jason AkulianDivision of Pulmonary and Critical Care Medicine, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Hans J LeeDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Andrew DeMaioDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA, ademaio3@jhmi.edu.
Christopher M KappDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Momen M WahidiDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, Duke University, Durham, North Carolina, USA.
Lonny YarmusDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Johns Hopkins University · USDuke University · USUniversity of North Carolina at Chapel Hill · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite recent advances in guided bronchoscopy, the yield of bronchoscopic biopsy of a peripheral pulmonary nodule (PPN) remains highly variable.

objectiveThe aim of the study was to evaluate which features of robotic assisted bronchoscopy (RAB) contribute to a successful biopsy in a cadaver model.

methodsA preclinical, prospective, single-blinded trial using a ventilated human cadaveric model assessed the successful puncture of implanted pulmonary nodules using various localization techniques with RAB. The different approaches included positioning the robotic catheter at predefined distances from the target nodule (<10 mm, 10-20 mm, 20-30 mm), bronchoscopist correction of divergence between the software virtual map and bronchoscopic view if observed, and impact of fluoroscopy and radial endobronchial ultrasound (rEBUS). The primary endpoint was a central target hit (defined as an inner 2/3 target puncture) verified by cone-beam computed tomography.

resultsThirty-eight RAB procedures were performed to target 16 PPNs. Median nodule size was 16.2 mm. All targets were located in the outer 1/3 of the lung with a bronchus sign in 31.3%. Central target hit rates were improved when the robotic catheter tip was closer to the nodule (<10 mm 68%, 10-20 mm 66%, 20-30 mm 11%, p < 0.001). Multivariable analysis confirmed the strongest predictor of a central target hit was robotic catheter distance to nodule (OR 0.89 per increase in 1 mm, p < 0.001), independent of the presence of a bronchus sign, divergence or concentric rEBUS view.

conclusionsUtilizing a RAB platform, closer proximity of the robotic catheter to the target nodule results in an increase in peripheral nodule biopsy success.

Indexed as

Lung NeoplasmsRobotic Surgical ProceduresBronchoscopyEndosonographyFluoroscopyHumansProspective StudiesFluoroscopyPulmonary noduleRadial endobronchial ultrasoundRobotic assisted bronchoscopy

Identifiers

PMID35344969
OpenAlexW4220767467

What OpenQuestion holds

Textmetadata
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.