Learning Curve of Real-Time Imaging with C-Arm Based Tomography for Peripheral Lung Nodule Biopsy.

Grant Senyei, Matthew Nobari, Russell Miller, Brody Harrell, George Z Cheng

Open access · goldAbstract read

In one paragraph

Article in Life (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

0.5field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

Human and Deep Learning Predictions of Peripheral Lung Cancer Using a 1.3 mm Video Endoscopic Probe.Respirology (Carlton, Vic.) · 2025
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

5 authors at 3 institutions in 1 country.

Grant SenyeiDivision of Pulmonary, Critical Care, and Sleep Medicine, University of California San Diego, La Jolla, CA 92037, USA.

Matthew NobariDivision of Pulmonary, Critical Care, and Sleep Medicine, University of California San Diego, La Jolla, CA 92037, USA.

Russell MillerDivision of Pulmonary, Critical Care, and Sleep Medicine, University of California San Diego, La Jolla, CA 92037, USA.

Brody HarrellCalifornia State University, San Bernadino, CA 92407, USA.

George Z ChengDivision of Pulmonary, Critical Care, and Sleep Medicine, University of California San Diego, La Jolla, CA 92037, USA.ORCID 0000-0001-6859-8705

University of California System · USCalifornia State University, San Bernardino · USNaval Medical Center San Diego · US

Funding

Body Vision Ltd. N/A

6 · The paper itself

Abstract

The number of procedures required to attain proficiency with new bronchoscopic biopsy technologies for peripheral pulmonary lesions (PPLs) is uncertain. A prospective, single-center study evaluated learning curves of two operators performing PPL biopsies using a novel, real-time, intraoperative tomographic imaging system in consecutive procedures in adults with CT-detected PPLs. Operators were considered "proficient" when they asked three or fewer questions of the manufacturer's clinical representative with no subsequent navigations in which they asked more than three questions. A total of 31 procedures were performed on 31 patients (Operator 1: 18, Operator 2: 13). Proficiency was achieved after an average of 10 procedures (Operator 1: 12, Operator 2: 8). From the learning curve to the post-learning curve period, the number of questions (median [IQR]: 23 [9.5-41.5] versus 0 [0-1],

Indexed as

interventional pulmonologylearning curvenavigational bronchoscopy

Identifiers

PMID37109465

DOI10.3390/life13040936

PMCPMC10141185

OpenAlexW4362585780

What OpenQuestion holds

Textmetadata

LicenceCC BY

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.