Evidence map›Paper›PMID 41816472›Full record

ReviewJournal of thoracic disease2026

Best practices in shape-sensing robotic bronchoscopy with mobile cone beam computed tomography guidance: how I do it.

Benjamin Casal, Roberto F Casal

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2026. 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
–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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

Benjamin CasalThe University of Texas Long School of Medicine, San Antonio, TX, USA.
Roberto F CasalDepartment of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.ORCID https://orcid.org/0000-0002-6167-475X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have demonstrated that shape-sensing robotic bronchoscopy with mobile cone-beam computed tomography (CBCT) guidance results in superb diagnostic outcomes for the diagnosis of peripheral lung lesions. Given the more favorable safety profile and the ability to also stage the mediastinum with endobronchial ultrasound when indicated, the combination of these technologies is likely to replace percutaneous computed tomography (CT)-guided biopsies of peripheral lung nodules in the years to come. Hands-on training in simulators, mannequins or cadaveric models is paramount before adopting this technique, but certain procedural and pre-procedural steps can only be practiced during true cases. Just like with any other new technology, there is an expected learning curve that physicians will go through before obtaining the desired procedural outcomes. Through the current manuscript we share some guidance based on years of research and clinical experience, which we hope will shorten the learning curve for newly adopters of these technologies. We have incorporated into our practice a systematic approach that maximizes the efficiency of patient positioning, integration of mobile CBCT and shape-sensing robotic bronchoscopy, as well as prevention of atelectasis and target motion. We believe this approach is key to maximizing efficiency and procedural outcomes, and we are honored to share it with the readers.

Indexed as

atelectasiscone-beam computed tomography (CBCT)Robotic bronchoscopy

Identifiers

PMID41816472
PMCPMC12972905

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.