AI-powered Portable MRI Abnormality Detection

NCT ID: NCT06803420

Last Updated: 2025-01-31

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

400 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-02-01

Study Completion Date

2027-10-31

Brief Summary

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This study aims to test a new AI-powered portable MRI scanner that can quickly identify whether a brain scan is normal or abnormal. Currently, standard MRI scans are expensive and have long waiting times. Our goal is to see if a smaller, cheaper, and more accessible MRI scanner-combined with artificial intelligence (AI)-can help doctors identify abnormalities faster and improve patient care.

We will invite patients from King's College Hospital (KCH) who are already having a standard MRI scan. They will be asked to have an extra scan using the portable MRI, which takes about 60 minutes. The AI tool will then analyse these scans and compare its results to those of expert radiologists.

By the end of the study, we hope to prove whether portable MRI with AI can be used in hospitals and GP clinics, making brain scans more accessible, reducing wait times, and helping doctors prioritise urgent cases.

This study is funded by the Medical Research Council (MRC) and has been approved by UK research ethics committees.

Detailed Description

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Conditions

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Head Injury

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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Portable, ultra-low-field MRI scanner

Patients undergoing a standard brain MRI scan will be invited to have an additional portable MRI scan within 30 days of their clinical scan.

Group Type EXPERIMENTAL

Portable, ultra-low-field MRI scanner

Intervention Type DEVICE

This study evaluates a portable, ultra-low-field MRI scanner (the Hyperfine Swoop) combined with artificial intelligence (AI) to detect brain abnormalities.

Patients undergoing a standard brain MRI scan will be invited to have an additional portable MRI scan within 30 days of their clinical scan. The portable MRI scan will take approximately 60 minutes, using multiple imaging sequences, including T2-weighted scans.

The AI system will then analyse the portable MRI images and categorise them as "normal" or "abnormal". The results will be compared with expert neuroradiologist reports from standard MRI scans to validate accuracy.

This intervention aims to assess whether portable MRI with AI can provide a low-cost, accessible alternative to standard MRI, potentially improving triage and reducing waiting times for patients requiring urgent brain imaging.

Interventions

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Portable, ultra-low-field MRI scanner

This study evaluates a portable, ultra-low-field MRI scanner (the Hyperfine Swoop) combined with artificial intelligence (AI) to detect brain abnormalities.

Patients undergoing a standard brain MRI scan will be invited to have an additional portable MRI scan within 30 days of their clinical scan. The portable MRI scan will take approximately 60 minutes, using multiple imaging sequences, including T2-weighted scans.

The AI system will then analyse the portable MRI images and categorise them as "normal" or "abnormal". The results will be compared with expert neuroradiologist reports from standard MRI scans to validate accuracy.

This intervention aims to assess whether portable MRI with AI can provide a low-cost, accessible alternative to standard MRI, potentially improving triage and reducing waiting times for patients requiring urgent brain imaging.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

Adults ≥18 years old. Undergoing standard brain MRI including T2-weighted sequences.

Exclusion Criteria

Contraindications to MRI (e.g. pacemaker, pregnancy). Poor quality MRI scans without a neuroradiology report.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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King's College London

OTHER

Sponsor Role collaborator

King's College Hospital NHS Trust

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Thomas Booth, Dr

Role: PRINCIPAL_INVESTIGATOR

King's College London & King's College Hospital

Central Contacts

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Frantisek Vasa, PhD

Role: CONTACT

Phone: 020 7848 9670

Email: [email protected]

Giusi Manfredi, PhD

Role: CONTACT

Phone: 020 7848 9670

Email: [email protected]

Other Identifiers

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IRAS 347453

Identifier Type: -

Identifier Source: org_study_id