TRACE TBI

  • Research type

    Research Study

  • Full title

    Non invasive assessment of cerebral perfusion in traumatic brain injury using machine learning analysis of continuous trans cranial Doppler waveforms

  • IRAS ID

    362356

  • Contact name

    Sam Hutchings

  • Contact email

    sam.hutchings@nhs.net

  • Sponsor organisation

    King's College Hospital NHS Foundation Trust

  • Duration of Study in the UK

    2 years, 0 months, 1 days

  • Research summary

    Patients with severe brain injury following trauma are at high risk of death and long term disability. One specific area where management is challenging relates to the detection and treatment of brain swelling that typically follows injury. Failure to act on increased brain swelling can lead to a devastating reduction in brain blood flow and a worse outcome for the patient. In an established neurosurgical intensive care unit, such swelling will be monitored by the presence of a dedicated probe that is placed in the brain tissue by a neurosurgeon. Where this procedure cannot be performed, usually because the patient is not in a specialist centre, doctors need to find alternative ways of detecting brain swelling.

    One approach is to use ultrasound, a safe and non-invasive technique, to measure blood flow in one of the large arteries supplying the brain. A headset like device, the Dolphin TCD, can be placed on patients and can automatically detect changes in blood flow without requiring an operator. Furthermore this device is entirely non- invasive and does not require specialist expertise to set up.

    The data produced by this device is a waveform that provides an indication of blood flow to the brain. However, just looking at the waveform does not in itself provide enough information about the degree of brain swelling as the changes produced may be quite subtle. In this study we will apply the Dolphin device to patients with differing degrees of brain injury in intensive care who are also being monitored using invasive brain probes. We will analyse the resultant waveforms using a machine learning technique. This will hopefully allow us to see early signals of brain swelling in the waveform. We will build on this work in future studies with the ultimate aim of developing a monitor that can be used to provide early warning of severe brain swelling.

  • REC name

    London - South East Research Ethics Committee

  • REC reference

    26/LO/0404

  • Date of REC Opinion

    12 Jun 2026

  • REC opinion

    Favourable Opinion