Evidence map›Paper›PMID 41229865›Full record

ArticleJournal of thoracic disease2025

Virtual

An Thi Nhat Ho, Xiaoyue Ma, Paul J Christos, Alessia Pedoto, Robert P Lee, Catherine L Oberg, Rastko Rakočević, Matthew J Bott, Mohit Chawla, Bryan C Husta and 1 more

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2025. 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. Article
  2. Review
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

11 authors.

An Thi Nhat HoSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Xiaoyue MaDivision of Biostatistics, Weill Cornell Medicine, New York, NY, USA.
Paul J ChristosDivision of Biostatistics, Weill Cornell Medicine, New York, NY, USA.
Alessia PedotoDepartment of Anesthesiology and Critical Care Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Robert P LeeSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Catherine L ObergSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Rastko RakočevićSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Matthew J BottThoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Mohit ChawlaSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Bryan C HustaSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Or Kalchiem-DekelSection of Interventional Pulmonology, Pulmonary Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Background: The diagnostic accuracy of shape-sensing robotic bronchoscopy (ssRAB) is impacted by computed tomography-to-body divergence (CTBD) due to a discrepancy between virtual and actual lesion locations. The prevalence, types, implication, and determinants of CTBD during ssRAB remain understudied. This study aimed to qualify and quantify CTBD during cone-beam computed tomography (CBCT)-guided ssRAB and identify contributing factors. Methods: This was an analysis of a prospectively curated database of patients who underwent mobile CBCT-guided ssRAB for the sampling of parenchymal lung lesions between October 2021 and June 2022. The primary outcome was the distance and vector of target displacement between the virtual preoperative CT-based and the actual intraoperative CBCT-based relationship between the tip of the ssRAB catheter and the target lesion. Results: A total of 81 lesions in 70 participants were included in the final analysis. Displacement was identified in 67% of targeted lesions. In 78% the ssRAB catheter was closer than expected (forward displacement) and an overshoot beyond the lesion occurred in 46% of displacement instances. In a multivariable logistic regression analysis, ≥7 traversed airway generations were independently associated with target lesion displacement. Despite a high level of displacement, there was no statistically significant difference in diagnostic yield rates between cases with and without displacement. Conclusions: CTBD, i.e., displacement of the actual target lesion from the virtual location, is common during navigational bronchoscopy. When targeting peripheral lesions, the catheter is more likely to be closer to the lesion or beyond it than expected based on the virtual planning. Bronchoscopists should anticipate CTBD and integrate data from various intraoperative imaging tools to attenuate its impact on sampling and avoid potential complications.

Indexed as

cone-beam computed tomography (CBCT)lung noduleRobotic-assisted bronchoscopy (RAB)

Identifiers

PMID41229865
PMCPMC12603554

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.