Skip to main content
OpenTrials
Active, Not Recruiting

NCT Number: NCT07717632

AI-enhanced LF-MRI in Epilepsy

The global burden of epilepsy is high affecting over 50 million people worldwide. Majority live in low- and middleincome 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.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Age range

18 year–70 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

UCL Queen Square Institute of Neurology

London, United Kingdom

About this study

The aim of this study is to determine the utility of AI-enhanced Low Field (AI-LF) MRI in the identification of focal brain lesions in adults with epilepsy. This is a proof-of-concept study evaluating the utility of AI-LF-MRI in aiding identification of potentially epileptogenic brain lesions, by comparing neuroradiologists' lesion detection on this modality versus standard HF-MRI. It will include ~30 adults with epilepsy who have undergone a high field (1.5T or 3T) MRI (HF-MRI) brain scan as part of their routine clinical care at University College London (UCL) Hospitals (UCLH), within the previous twelve months. Participants will be consecutively recruited and offered a LF-MRI brain scan on the 0.064T Swoop MR Imaging System (Hyperfine®) at the Birkbeck-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. Each participant will only have a single encounter with the study on the day they get their LF-MRI scan. There is no follow-up required with this study.

Inclusion criteria

  • Adults aged between >18 years and <70 years
  • Diagnosis of epilepsy and attending a UCLH-affiliated outpatient epilepsy clinic
  • Undergone a 1.5T or 3T MRI Brain scan within 12 months of recruitment as part of standard clinical care.
  • Can tolerate MRI scanning without sedation. Exclusion criteria
  • Cognitive impairment that precludes ability to consent or assent to the study 2. Inability to lie flat for the duration of the scan 3. Body habitus incompatible with LF-MRI device 4. Presence of MRI contraindications as stipulated by standard MRI operating procedures

We will recruit at least 30 patients, of these, 20 patients will have a visible lesion on the HF-MRI scan (reference standard). A sample size of 20 patients will be sufficient to demonstrate that the proportion of lesions similarly identified is at least 0.8, against a null hypothesis of 0.5, using a one-sample, one-sided exact binomial test with a 5% significance level and a power of 80%. The rest will not have a visible potentially epileptogenic lesion on the HF-MRI scan.

Two consultant neuroradiologists will separately and independently report AI-LF- then HF-MRI scans according to set criteria, including, MRI scanner field strength, presence of lesion, lesion location and artefacts. They will be provided with basic participant clinical details such as age, seizure type and. EEG findings, but blinded to diagnosis. Rates of lesion detection and false positives in the AI-LF-MRI scans will be compared with the reference standard of a recent clinical HF-MRI and reported as proportions. Sensitivity and specificity analyses will be performed for the qualitative analysis of AI-LF-MRI. Intraclass coefficients and Bland Altman analyses will be used to compare quantitative inter-rater and inter-method agreement, respectively. Descriptive statistics such as medians (IQR) and proportions will be used to describe participants' demographic information and survey responses.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adults aged between >17 years and <70 years
  • Diagnosis of epilepsy and attending at UCLH-affiliated outpatient epilepsy clinic
  • Undergone a 1.5T or 3T MRI Brain scan within 12 months of recruitment as part of standard clinical care
  • Can tolerate MRI scanning without sedation.

Exclusion criteria

  • Cognitive impairment that precludes ability to consent or assent to the study
  • Inability to lie flat
  • Body habitus incompatible with LF-MRI device
  • Presence of MRI contraindications as stipulated by standard MRI operating procedures

Treatment and study plan

MRI

Diagnostic Test

Low magnetic field MRI of the brain

Other names: Low-field

Primary outcomes

  1. Sensitivity of AI-LF-MRI for lesion detection, measured as the proportion of lesions identified on HF-MRI that are also detected on AI-LF-MRI by blinded neuroradiologist review.

    Time frame: Baseline assessment (within the study imaging visit). Participant will only undergo a low-field MRI scan which will be compared to a reference high-field MRI scan done within 12 months of enrolment.

    The rate of correctly identified abnormalities on the AI-enhanced low-field MRI when compared to standard of care high-field MRI. There is no pre-specified "good" rate assigned for this pilot study.

Secondary outcomes

  1. Proportion of scans with clinically significant artefacts, determined by blinded neuroradiologist assessment, on AI-LF-MRI compared with HF-MRI

    Time frame: Baseline assessment (within the study imaging visit)

    Rate of reported artefacts, including movement, blurring and signal inhomogeneity, on AI-LF-MRI compared to HF-MRI

  2. Inter-rater agreement among blinded neuroradiologists for qualitative lesion detection and classification on AI-LF-MRI and HF-MRI, measured using Cohen's kappa for pairwise agreement between raters and Fleiss' kappa for agreement across all raters

    Time frame: Baseline assessment (within the study imaging visit)

    Compare agreement of lesions identified among radiologists reading the scans

  3. Inter-method agreement between AI-LF-MRI and HF-MRI for quantitative imaging measures, assessed using Bland-Altman analysis.

    Time frame: Baseline assessment (within the study imaging visit)

    Comparative analysis of hippocampal volume segmentation of the SuperSynth (AI tool) of low-field vs high-field MRI

  4. Acceptability of the LF-MRI scanning process, assessed using participant responses to a custom acceptability questionnaire

    Time frame: Baseline assessment (within the study imaging visit)

    Participants answer a custom-made questionnaire immediately after their low-field MRI scan on the Hyperfine. The questionnaire has closed-ended questions about their experience, with a few opportunities for open comment.

Sponsors and collaborators

Lead sponsor

University College, London

Other

Collaborators

  • The Leverhulme Trust
  • University College London Hospitals

Registry information

Official study title

Evaluation of Artificial Intelligence-enhanced Low Field

Acronym: ALF-ME

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Jul 21, 2026
Registry last updated
Jul 23, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.