ADVENT A pilot study to evaluate Automatic-DVT diagnostic software v1

  • Research type

    Research Study

  • Full title

    A multi-centre, prospective, double-blinded, pilot study evaluating artificial intelligence driven automatic detection of proximal deep vein thrombosis (DVT)



  • Contact name

    Nicola Curry

  • Contact email

  • Sponsor organisation

    Oxford University Hospitals NHS Foundation Trust

  • ISRCTN Number


  • Identifier

    CTU 18/111, NHSBT CTU Reference

  • Duration of Study in the UK

    1 years, 3 months, days

  • Research summary

    Deep vein thrombosis (DVT) is a term which describes the blood clots (thrombi) that can form in the deep veins. The deep leg veins are commonly affected (such as the proximal veins: femoral vein or popliteal vein) or the deep veins of the pelvis. The standard approach to making a diagnosis involves an algorithm combining pre-test probability, a blood test called the D-dimer test, and the patient undergoing an ultrasound of the leg veins. Ultrasound is currently completed by trained radiographers.
    However, handheld ultrasound probes have recently become available and they have enabled ‘app-based’ ultrasonography to be performed. ThinkSono has developed software which it is hoped has the same accuracy for diagnosing DVT as the standard ultrasound. If this trial has a positive outcome, it would mean that DVT could be diagnosed at point of care by non-radiographers such as nurses, junior doctors, general practitioners and other healthcare staff. By diagnosing DVT early in the clinical pathway (for example, at GP practices), the technology could reduce emergency department admissions and free up specialists to focus on other clinical tasks. These improvements could also potentially reduce the financial burden of the DVT diagnostic service on the NHS.

  • REC name

    East of Scotland Research Ethics Service REC 2

  • REC reference


  • Date of REC Opinion

    2 Aug 2021

  • REC opinion

    Further Information Favourable Opinion