Evidence map›Paper›PMID 37734952›Full record

ArticleThorax2023

Automatic analysis of bronchus-artery dimensions to diagnose and monitor airways disease in cystic fibrosis.

Qianting Lv, Leticia Gallardo-Estrella, Eleni-Rosalina Andrinopoulou, Yuxin Chen, Jean-Paul Charbonnier, Rikke Mulvad Sandvik, Daan Caudri, Kim Gjerum Nielsen, Marleen de Bruijne, Pierluigi Ciet and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Thorax, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

20 citing papers in PubMed, 32 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Qianting LvDepartment of Paediatric Pulmonology and Allergology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands.ORCID 0000-0003-1113-9481
Leticia Gallardo-EstrellaThirona, Nijmegen, The Netherlands.
Eleni-Rosalina AndrinopoulouDepartment of Biostatistics and Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
Yuxin ChenDepartment of Paediatric Pulmonology and Allergology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands.
Jean-Paul CharbonnierThirona, Nijmegen, The Netherlands.
Rikke Mulvad SandvikCF Center Copenhagen, Paediatric Pulmonary Service, Department of Paediatric and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.ORCID 0000-0002-0374-7279
Daan CaudriDepartment of Paediatric Pulmonology and Allergology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands.
Kim Gjerum NielsenCF Center Copenhagen, Paediatric Pulmonary Service, Department of Paediatric and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.ORCID 0000-0001-5906-9449
Marleen de BruijneBiomedical Imaging Group Rotterdam, Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.ORCID 0000-0002-6328-902X
Pierluigi CietDepartment of Paediatric Pulmonology and Allergology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands.ORCID 0000-0003-4017-8957
Harm TiddensDepartment of Paediatric Pulmonology and Allergology, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands h.tiddens@erasmusmc.nl.ORCID 0000-0001-5628-6667
Erasmus MC · NLUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCystic fibrosis (CF) lung disease is characterised by progressive airway wall thickening and widening. We aimed to validate an artificial intelligence-based algorithm to assess dimensions of all visible bronchus-artery (BA) pairs on chest CT scans from patients with CF.

methodsThe algorithm fully automatically segments the bronchial tree; identifies bronchial generations; matches bronchi with the adjacent arteries; measures for each BA-pair bronchial outer diameter (B

resultsThe automatic and manual BA analysis showed no significant differences in quantifying bronchi. For the longitudinal datasets the automatic BA analysis detected 247 and 347 BA pairs/CT in the Copenhagen and ataluren dataset, respectively. A significant increase of 0.02 of B

conclusionThe BA analysis can fully automatically analyse a large number of BA pairs on chest CTs to detect and monitor progression of bronchial wall thickening and bronchial widening in patients with CF.

Indexed as

Cystic FibrosisRespiration DisordersArtificial IntelligenceBronchiBronchial ArteriesHumansLungBronchiectasisCystic FibrosisImaging/CT MRI etcPaediatric Lung Disaese

Identifiers

PMID37734952
PMCPMC10803964
OpenAlexW4386922426

What OpenQuestion holds

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LicenceCC BY-NC
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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.