ADOPT: Improving diagnosis of pulmonary hypertension with AI and echo

  • Research type

    Research Study

  • Full title

    Artificial intelligence: Improving diagnosis of pulmonary hypertension by transthoracic echocardiography: ADOPT

  • IRAS ID

    328912

  • Contact name

    Daniel X Augustine

  • Contact email

    Daniel.augustine@nhs.net

  • Sponsor organisation

    Royal United Hospitals Bath NHS Foundation Trust

  • Duration of Study in the UK

    2 years, 0 months, 1 days

  • Research summary

    Pulmonary Hypertension (PH) is a condition caused by high blood pressure in the blood vessels that carry blood to the lungs. It can cause severe breathlessness and failure of the right side of the heart. Sadly it is often fatal, and life expectancy ranges from months to years. For some subtypes of PH, effective treatments exist which can improve life expectancy and quality-of-life. Accurate tools for the assessment of PH are therefore essential so that life-saving medications can be started earlier.

    In existing diagnostic pathways, evidence for the suspicion of PH is frequently overlooked, significantly delaying the time to diagnosis. Echocardiography (echo) is a quick, safe and well-tolerated test requested to investigate breathless patients, and which can provide useful information about the suspicion of PH. However, outside of specialist PH centres, doctors may not routinely look for and comment on the presence of clues to possible PH.

    We think that using Artificial Intelligence (AI) techniques to read echo’s could make their interpretation faster and more reliable. There may also be subtle clues to the presence or severity of PH on echo, less recognisable to the human eye, which AI can identify.

    In this study we will gather echo images from 5 specialist PH hospitals across the UK which have all been anonymised (patient’s name and personal details removed). These will all be historic scans (i.e. have already taken place) and will be grouped into those with PH present (including PH sub-type) or absent. These anonymised echo images will be used to develop and train an AI tool to identify scans where PH is present, including which specific type of PH may be present. The developed AI tool will then be tested on a separate group of scans (not used in the training stage) to validate its performance.

  • REC name

    North of Scotland Research Ethics Committee 1

  • REC reference

    23/NS/0088

  • Date of REC Opinion

    11 Aug 2023

  • REC opinion

    Favourable Opinion