Evidence map›Paper›PMID 40711551›Full record

ArticleEuropean radiology2026

Image quality in ultra-low-dose chest CT versus chest x-rays guiding paediatric cystic fibrosis care.

Niamh Moore, Patrick O'Regan, Rena Young, Grainne Curran, Michael Waldron, Alex O'Mahony, Mo'ayyad E Suleiman, Mary Jane Murphy, Michael Maher, Andrew England and 1 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology, 2026. 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
–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

1 citing paper in PubMed.

  1. 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

11 authors.

Niamh MooreDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland. niamh.moore@ucc.ie.ORCID http://orcid.org/0000-0003-2099-2222
Patrick O'ReganDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Rena YoungDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Grainne CurranDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Michael WaldronDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Alex O'MahonyDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Mo'ayyad E SuleimanSydney School of Health Sciences, University of Sydney, Sydney, NSW, Australia.
Mary Jane MurphyDepartment of Radiology, Cork University Hospital, Cork, Ireland.
Michael MaherDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Andrew EnglandDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.
Mark F McEnteeDiscipline of Medical Imaging and Radiation Therapy, School of Medicine, University College Cork, Cork, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesCystic fibrosis (CF) is a prevalent autosomal recessive disorder, with lung complications being the primary cause of morbidity and mortality. In paediatric patients, structural lung changes begin early, necessitating prompt detection to guide treatment and delay disease progression. This study evaluates ultra-low-dose CT (ULDCT) versus chest x-rays  (CXR) for children with CF (CwCF) lung disease assessment. ULDCT uses AI-enhanced deep-learning iterative reconstruction to achieve radiation doses comparable to a CXR. MATERIALS AND

methodsThis prospective study recruited radiographers and radiologists to assess the image quality (IQ) of ten paired ULDCT and CXR images of CwCF from a single centre. Statistical analyses, including the Wilcoxon Signed Rank test and visual grading characteristic (VGC) analysis, compared diagnostic confidence and anatomical detail.

resultsSeventy-five participants were enrolled, 25 radiologists and 50 radiographers. The majority (88%) preferred ULDCT over CXR for monitoring CF lung disease due to higher perceived confidence (p ≤ 0.001) and better IQ ratings (p ≤ 0.05), especially among radiologists (area under the VGC curve and its 95% CI was 0.63 (asymmetric 95% CI: 0.51-0.73; p ≤ 0.05). While ULDCT showed no significant differences in anatomical visualisation compared to CXR, the overall IQ for lung pathology assessment was rated superior.

conclusionULDCT offers superior IQ over CXR in CwCF, with similar radiation doses. It also enhances diagnostic confidence, supporting its use as a viable CXR alternative. Standardising CT protocols to optimise IQ and minimise radiation is essential to improve disease monitoring in this vulnerable group. KEY POINTS: Question How does chest X-ray (CXR) IQ in children compare to ULDCT at similar radiation doses for assessing CF-related lung disease? Findings ULDCT offers superior IQ over CXR in CwCF. Participants preferred ULDCT due to higher perceived confidence levels and superior IQ. Clinical relevance ULDCT can enhance diagnosis in CwCF while maintaining comparable radiation doses. ULDCT also enhances diagnostic confidence, supporting its use as a viable CXR alternative.

Indexed as

Cystic FibrosisRadiation DosageRadiography, ThoracicTomography, X-Ray ComputedAdolescentChildChild, PreschoolFemaleHumansLungMaleProspective StudiesRadiographic Image Interpretation, Computer-AssistedChildrenDiagnostic imagingfollow-upLung disease

Identifiers

PMID40711551
PMCPMC12712111

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Registered trials

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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.