Ultrasound in inflammatory muscle disease

  • Research type

    Research Study

  • Full title

    Development of a novel machine learning ultrasound imaging technique to identify and quantify skeletal muscle disease in real time

  • IRAS ID

    200219

  • Contact name

    Ian Loram

  • Contact email

    I.Loram@mmu.ac.uk

  • Sponsor organisation

    Manchester Metropolitan University

  • Duration of Study in the UK

    0 years, 6 months, 1 days

  • Research summary

    Inflammatory myopathies are disorders where inflammation occurs in muscle tissue, causing disabling weakness. Taking a sample of muscle (muscle biopsy) is the best way to diagnose these conditions, but this cannot be repeated to see how people respond to treatments. \n\nUltrasound is a technique which can show pictures of muscle and is quick and non-invasive. Current ways of using ultrasound in muscle disorders depend on the person doing the scan for results so may not be very accurate. We have developed a new way of using ultrasound where a computer can learn to recognize patterns of the images by itself. This means that we can pick up differences in ultrasound information without a person having to look at the images. We want to test whether the computer can pick out differences on the ultrasound between people with and without inflammatory muscle diseases.\n\nWe will recruit 25 people with inflammatory muscle disease and 25 healthy control participants. People with muscle disease will have had a sample of muscle taken in the clinic (biopsy) to prove they have the condition. We will examine them for signs of muscle disease and the level of weakness. We will then measure leg movements using a special device while continuing to scan the leg muscles using ultrasound. The assessments will be done at Salford Royal NHS Foundation Trust and Manchester Metropolitan University, and would usually involve attending on two occasions.\n

  • REC name

    North West - Liverpool Central Research Ethics Committee

  • REC reference

    16/NW/0760

  • Date of REC Opinion

    18 Oct 2016

  • REC opinion

    Favourable Opinion