Evidence map›Paper›PMID 35928581›Full record

ArticleAME case reports2022

Combined portable cone beam computed tomography and robotic-assisted bronchoscopy impacting diagnosis of a solitary pulmonary nodule: a case report.

Jennifer D Duke, Sebastian Fernandez-Bussy, Janani Reisenauer

Open access · diamondAbstract readCase Reports
In one paragraph

Article in AME case reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Jennifer D DukeDivision of Pulmonary Medicine, Mayo Clinic, Rochester, MN, USA.
Sebastian Fernandez-BussyDivision of Pulmonary Medicine, Mayo Clinic, Jacksonville, FL, USA.
Janani ReisenauerDivision of Pulmonary Medicine, Mayo Clinic, Rochester, MN, USA.
Mayo Clinic · USMayo Clinic in Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung cancer is the leading cause of cancer-related mortality in men and women throughout the world. Historically, bronchoscopy played a limited role in pulmonary nodule management due to a limited diagnostic accuracy. With the emergence of robotic bronchoscopy, proceduralists can now navigate to more peripheral lesions completely extrinsic to the airways with increased diagnostic yield. Despite the increased diagnostic yield from robotic-assisted bronchoscopy, challenges in exact localization of the lesion during a procedure can occur. This case highlights a novel use of robotic bronchoscopy combined with mobile three-dimensional (3D) imaging to optimize lesion location for biopsy previously not reported in the literature. Case Description: We describe a case where the combination of robotic bronchoscopy with new mobile 3D imaging was essential for the accurate biopsy of an incidentally found pulmonary nodule in a 72-year-old woman. Initial navigation to the nodule using robotic bronchoscopy resulted in the catheter being inferior to the area of interest. After renavigation using the information provided by mobile 3D imaging, we were able to confirmed tool-in-lesion prior to biopsy. The patient was diagnosed with adenocarcinoma with papillary features and underwent a lobectomy with a favorable prognosis. Conclusions: A diagnosis of adenocarcinoma was made for this patient utilizing the novel combined technique of robotic peripheral pulmonary nodule biopsy with portable 3D imaging, which may improve overall diagnostic accuracy of bronchoscopic biopsy.

Indexed as

biopsycase reportLung cancermobile three-dimensional imaging (mobile 3D imaging)robotic bronchoscopy

Identifiers

PMID35928581
PMCPMC9343982
OpenAlexW4285547432

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.