Evidence map›Paper›PMID 42861162›Full record

ArticleBJR open2026

Automated triage to a virtual lung nodule clinic using veye lung nodule volumetry provides a cost saving compared to standard care.

Giles Dixon, Vruti Dattani, Vidan Masani, Pia Charters, Mary Jordan, Jonathan C L Rodrigues

Abstract read
In one paragraph

Article in BJR open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Giles DixonDepartment of Respiratory Medicine, Royal United Hospitals Bath NHS Foundation Trust, Bath, BA13NG, United Kingdom.ORCID https://orcid.org/0000-0001-9787-0739
Vruti DattaniDepartment of Radiology, Royal United Hospitals Bath NHS Foundation Trust, Bath, BA13NG, United Kingdom.
Vidan MasaniDepartment of Respiratory Medicine, Royal United Hospitals Bath NHS Foundation Trust, Bath, BA13NG, United Kingdom.
Pia ChartersDepartment of Radiology, Royal United Hospitals Bath NHS Foundation Trust, Bath, BA13NG, United Kingdom.
Mary JordanYork Health Economics Consortium, University of York, York, YO10 5DD, United Kingdom.
Jonathan C L RodriguesDepartment of Radiology, Royal United Hospitals Bath NHS Foundation Trust, Bath, BA13NG, United Kingdom.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Objectives: Pulmonary nodules are frequently identified on thoracic CT imaging, with management guided by established clinical pathways. Thoracic CT scans are reported by both specialist and general radiologists. This study evaluated discordance in pulmonary nodule identification and management between general and specialist radiologists and modeled automated triage to a virtual nodule clinic (VNC). Methods: All CT scans, including the thorax, performed over a 1-week period at a single UK center in March 2022 were identified and original reports reviewed. Oncology follow-up scans were excluded. Reports were categorized and compared with an independent second expert radiologist review. VNC triage pathways were modeled to select patients for second review by an expert radiologist. The pathways used combinations of original radiologist reports and automated nodule assessment (DeepHealth Ltd) to trigger VNC review. The cost implications of each pathway were calculated. Results: Among 243 CT scans, 98 (40%) original reports identified a pulmonary nodule. Expert review identified incorrect recommendations in 24/243 (10%) cases. Errors were significantly more frequent in reports issued by general radiologists compared with specialist thoracic radiologists (χ² ∼ 11.0, df = 2, Conclusion: Approximately 10% of thoracic CT scans contained errors in pulmonary nodule reporting. Cost-saving triage pathways combining non-specialist reporting with automated nodule assessment appear feasible and warrant prospective real-world validation. Advances in knowledge: This study demonstrates theoretical clinical implementation of semi-automated triage to a virtual nodule clinic and provides an evidence base for prospective study.

Indexed as

artificial intelligencecomputed tomographypulmonary nodules

Identifiers

PMID42861162
PMCPMC13654201

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.