Evidence map›Paper›PMID 42287359›Full record

ArticleSkeletal radiology2026

Mechanical axis image quality of the EOS imaging system compared to digital radiographs.

Ahmed Alghamdi, Natalie Lee, Farag Shuweihdi, Amaka C Offiah

Abstract readComparative Study
In one paragraph

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

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ahmed AlghamdiDivision of Clinical Medicine, University of Sheffield, Western Bank, Sheffield, UK. amalghamdy@kku.edu.sa.ORCID http://orcid.org/0000-0003-1734-6510
Natalie LeeRadiology Department, Sheffield Children's NHS Foundation Trust, Western Bank, Sheffield, UK.
Farag ShuweihdiLeeds Institute of Health Sciences, University of Leeds, Leeds, UK.ORCID http://orcid.org/0000-0003-1199-2992
Amaka C OffiahDivision of Clinical Medicine, University of Sheffield, Western Bank, Sheffield, UK.ORCID http://orcid.org/0000-0001-8991-5036

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare mechanical axis image quality between the EOS imaging system and digital radiograph (DR). MATERIALS AND

methodsThis retrospective study included 100 patients who underwent both EOS and DR mechanical axis imaging. It was conducted according to the Quality and Standards Department at the University of Sheffield. Three observers independently scored the DR and EOS images according to the modified European guidelines on quality criteria for diagnostic radiographic images in paediatrics: resolution, coverage of the area of interest, positioning, contrast, and motion. The range of scores was (Yes) for the fulfilled criterion and (No) for the not fulfilled criterion. For the motion criterion, the scores were (No) if the image quality criterion was not fulfilled (motion) and (Yes) if the image quality criterion was fulfilled (no motion). Inter-rater agreement was measured using the Gwet's agreement coefficient (AC1) with a 95% confidence interval. The accuracy of the EOS was assessed using sensitivity, specificity, and the area under curve (AUC). Variables between the EOS and DR were compared using McNemar's test. Both Gwet's AC1 and corresponding 95%CI were computed using irrCAC library in R4.41 software.

resultsThe mean (range) age of patients when they underwent DR and EOS imaging was 11.2 (4-18) and 11.8 (5-17) years, respectively. EOS demonstrated almost perfect inter-rater reliability in the resolution criterion (AC1 = 0.99, 95% CI = 0.98,1.00, p < 0.001), while DR showed similar reliability in the motion artefacts (AC1 = 0.96, 95% CI = 0.92.00, p < 0.001). Intra-rater reliability was high for most criteria. EOS images demonstrated high sensitivity for all criteria and variable specificity, which equalled or exceeded that of DR images. Significant differences were found in some criteria, such as the coverage of the area of interest (chi-squared = 37.39, p < 0.001) and hip level (chi-squared statistic = 31.44, p < 0.001).

conclusionThe high AC1, sensitivity, and AUCs highlight the diagnostic image quality of the EOS imaging system for mechanical axis images, making it a valuable modality in clinical settings. Therefore, the EOS imaging system can be used instead of DR in this context, offering advantages such as lower irradiation, shorter scanning time, and the capability for 3D reconstruction.

Indexed as

Radiographic Image EnhancementAdolescentChildChild, PreschoolFemaleHumansMaleReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityDigital radiographsEOS imaging systemMechanical axis imaging

Identifiers

PMID42287359
PMCPMC13522051

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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.