Paediatric fractures, Artificial intelligence in diagnosis Study

• Research type

  Research Study

• Full title

  The PEAS Study: PaEdiatric fractures, Artificial intelligence in diagnosis Study

• IRAS ID

  282169

• Contact name

  Caroline Hing

• Contact email

  Caroline.Hing@stgeorges.nhs.uk

• Sponsor organisation

  St George’s University Hospitals NHS Foundation Trust

• Duration of Study in the UK

  1 years, 0 months, 1 days

• Research summary

  In the UK 1 in 50 children will sustain a fractured bone yearly. Studies have reported that 34% of children sustaining an injury do not have a fracture on initial X-ray.

  The limitations of radiological diagnosis in detecting paediatric fractures include missed fractures affecting growth, resulting in deformity or over treatment of suspected fractures. More advanced imaging such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are resource intensive and may expose the patient to increased radiation.

  This study aims to develop Artificial Intelligence (AI) techniques to improve the accuracy of detecting fractures on radiographs. The outcome of the project will provide a tool for frontline practitioners to improve accuracy and confidence in diagnosing paediatric fractures.

• REC name

  London - Surrey Research Ethics Committee

• REC reference

  20/PR/0211

• Date of REC Opinion

  28 Jul 2020

• REC opinion

  Further Information Favourable Opinion