AI-enhanced LF-MRI in Epilepsy - version 1.0

  • Research type

    Research Study

  • Full title

    Evaluation of Artificial Intelligence-enhanced Low Field Magnetic Resonance Imaging in Epilepsy

  • IRAS ID

    352304

  • Contact name

    John Duncan

  • Contact email

    j.duncan@ucl.ac.uk

  • Sponsor organisation

    University College London

  • Clinicaltrials.gov Identifier

    Z6364106/2025/06/258, Data Protection number

  • Duration of Study in the UK

    1 years, 0 months, 4 days

  • Research summary

    The global burden of epilepsy is high affecting over 50 million people worldwide. Majority live in low- and middle-income countries (LMICs) where access to diagnosis and treatment is limited. Accurate diagnosis of epilepsy and identification of the underlying cause through brain imaging is key to providing appropriate treatment. Magnetic resonance imaging (MRI) is the recommended modality of choice for brain imaging. However, in many LMICs it is scarce, and the cost of maintenance is unattainable. This study aims to explore the usefulness of a lower cost, more portable MRI machine for epilepsy diagnosis. It will be a proof-of-concept study evaluating the utility of low magnetic field MRI (LF-MRI) in epilepsy diagnosis. It will include 30 adults with epilepsy who have undergone a high field MRI (HF-MRI) brain scan as part of their routine clinical care under the University College London (UCL) Hospitals (UCLH), within twelve months of recruitment. Participants will be consecutively recruited and offered a LF-MRI brain scan on the Swoop MR Imaging System (Hyperfine) at the Birbeck-UCL Centre for Neuroimaging (BUCNI). Image post-processing will be performed using the open access machine learning program, LF-SynthSR, to enhance the image quality and allow for quantitative image analysis. Anonymised HF- and LF-MRI scans will be independently reported using a structured reporting template by two neuroradiologists. A perception survey will be administered to all participants to assess their tolerability of the LF-MRI. This study will serve as a foundation for future studies in this field and in areas where such innovations are most needed.

  • REC name

    North East - Newcastle & North Tyneside 1 Research Ethics Committee

  • REC reference

    25/NE/0149

  • Date of REC Opinion

    1 Aug 2025

  • REC opinion

    Further Information Favourable Opinion