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. 2024 Dec 7;14(12):e084448.
doi: 10.1136/bmjopen-2024-084448.

Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol

Susan C Shelmerdine  1   2   3 , Cato Pauling  2 , Emma Allan  4 , Dean Langan  2   5 , Emily Ashworth  4 , Ka-Wai Yung  6 , Joy Barber  7 , Saira Haque  8 , David Rosewarne  9 , Nick Woznitza  10   11 , Sarim Ather  12 , Alex Novak  13 , Kanthan Theivendran  14 , Owen J Arthurs  4   2   3
Affiliations

Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol

Susan C Shelmerdine et al. BMJ Open. .

Abstract

Introduction: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial intelligence (AI) tools to assist fracture detection in adult patients exist, although their efficacy in children is less well known. This study aims to evaluate whether a commercially available AI tool (certified for paediatric use) improves healthcare professionals (HCPs) detection of fractures, and how this may impact patient care in a retrospective simulated study design.

Methods and analysis: Using a multicentric dataset of 500 paediatric radiographs across four body parts, the diagnostic performance of HCPs will be evaluated across two stages-first without, followed by with the assistance of an AI tool (BoneView, Gleamer) after an interval 4-week washout period. The dataset will contain a mixture of normal and abnormal cases. HCPs will be recruited across radiology, orthopaedics and emergency medicine. We will aim for 40 readers, with ~14 in each subspecialty, half being experienced consultants. For each radiograph HCPs will evaluate presence of a fracture, their confidence level and a suitable simulated management plan. Diagnostic accuracy will be judged against a consensus interpretation by an expert panel of two paediatric radiologists (ground truth). Multilevel logistic modelling techniques will analyse and report diagnostic accuracy outcome measures for fracture detection. Descriptive statistics will evaluate changes in simulated patient management.

Ethics and dissemination: This study was granted approval by National Health Service Health Research Authority and Health and Care Research Wales (REC Reference: 22/PR/0334). IRAS Project ID is 274 278. Funding has been provided by the National Institute for Heath and Care Research (NIHR) (Grant ID: NIHR-301322). Findings from this study will be disseminated through peer-reviewed publications, conferences and non-peer-reviewed media and social media outlets.

Trial registration number: ISRCTN12921105.

Keywords: ACCIDENT & EMERGENCY MEDICINE; Diagnostic Imaging; Paediatric orthopaedics.

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Conflict of interest statement

Competing interests: NW reports the following competing interests: consultancy fees from InHealth Reporting, SM Radiology; speaker honoraria fees from AstraZeneca and travel grant award from Qure.ai Technologies. All other authors (SS, CP, EAllan, DL, EAshworth, K-WY, JB, SH, DR, SA, AN, KT and OJA) deny any competing interest statements.

Figures

Figure 1
Figure 1. A diagrammatic flow chart of the multireader multicase (MRMC) study outline. AI, artificial intelligence.
Figure 2
Figure 2. Simulated patient management options provided to different subspecialty readers recruited in this study. For every case reviewed, the reader will be asked to select the single best treatment plan. They will be presented with slightly different options depending on their area of medical expertise. ED, emergency department.
See this image and copyright information in PMC

References

    1. Jones IE, Williams SM, Dow N, et al. How many children remain fracture-free during growth? a longitudinal study of children and adolescents participating in the Dunedin Multidisciplinary Health and Development Study. Osteoporos Int. 2002;13:990–5. doi: 10.1007/s001980200137. - DOI - PubMed
    1. Cooper C, Dennison EM, Leufkens HG, et al. Epidemiology of Childhood Fractures in Britain: A Study Using the General Practice Research Database. J Bone Miner Res. 2004;19:1976–81. doi: 10.1359/jbmr.040902. - DOI - PubMed
    1. Eakins C, Ellis WD, Pruthi S, et al. Second opinion interpretations by specialty radiologists at a pediatric hospital: rate of disagreement and clinical implications. AJR Am J Roentgenol. 2012;199:916–20. doi: 10.2214/AJR.11.7662. - DOI - PubMed
    1. Taves J, Skitch S, Valani R. Determining the clinical significance of errors in pediatric radiograph interpretation between emergency physicians and radiologists. CJEM. 2018;20:420–4. doi: 10.1017/cem.2017.34. - DOI - PubMed
    1. Klein EJ, Koenig M, Diekema DS, et al. Discordant radiograph interpretation between emergency physicians and radiologists in a pediatric emergency department. Pediatr Emerg Care. 1999;15:245–8. - PubMed