Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation

NCT ID: NCT06061822

Last Updated: 2025-08-22

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

RECRUITING

Clinical Phase

NA

Total Enrollment

150 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-09-09

Study Completion Date

2027-12-01

Brief Summary

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Cardiac MRI (CMR) scanning allows doctors to create detailed images of the heart. However, the need for experienced cardiac radiographers to perform each scan can make CMR's delivery difficult, and some patients in the UK wait more than half a year for a scan. These radiographers must take pictures of different part of the heart, termed "views", each of which must be precisely positioned.

The investigators believe they can revolutionise CMR, by using artificial intelligence to automatically position the views so radiographers can focus on more difficult tasks.

The investigators have used a retrospective database of pseudonymised (anonymised and linked) CMR scans at our hospital to create these artificial intelligence (AI) algorithms, and they have validated them retrospectively on previous studies. The investigators now wish to test the algorithms prospectively.

In this study, the investigators will recruit patients undergoing clinical CMR scans. In addition to the routine images acquired by expert radiographers, the investigators will require a duplicate set of images, positioned and planned by the AI algorithms.

The investigators will then compare, within each patient, the AI-planned and expert-radiographer-planned scanning in terms of both speed and image quality.

Detailed Description

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Conditions

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Cardiovascular Diseases Healthy Volunteers

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Study Groups

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AI-planned images acquired

Group Type EXPERIMENTAL

AI-assisted cardiac magnetic resonance imaging

Intervention Type DIAGNOSTIC_TEST

An AI algorithm will be used to automatically position (plan) the scan planes used in a cardiac MRI scan. The resultant images will be compared with standard radiographer-positioned images.

Radiographer-planned images acquired

Group Type ACTIVE_COMPARATOR

AI-assisted cardiac magnetic resonance imaging

Intervention Type DIAGNOSTIC_TEST

An AI algorithm will be used to automatically position (plan) the scan planes used in a cardiac MRI scan. The resultant images will be compared with standard radiographer-positioned images.

Interventions

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AI-assisted cardiac magnetic resonance imaging

An AI algorithm will be used to automatically position (plan) the scan planes used in a cardiac MRI scan. The resultant images will be compared with standard radiographer-positioned images.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Adult (aged at least 18 years)

Exclusion Criteria

* Children (patients below age 18).
* Pregnant patients.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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British Heart Foundation

OTHER

Sponsor Role collaborator

Medical Research Council

OTHER_GOV

Sponsor Role collaborator

Rosetrees Trust

OTHER

Sponsor Role collaborator

Imperial College London

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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James P Howard, MB BChir PhD

Role: PRINCIPAL_INVESTIGATOR

Imperial College London

Locations

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Imperial College Healthcare NHS Trust

London, , United Kingdom

Site Status RECRUITING

Countries

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United Kingdom

Central Contacts

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James P Howard, MB BChir PhD

Role: CONTACT

+44 207 594 5735

Facility Contacts

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James P Howard, MB BChir PhD

Role: primary

+447841124459

Other Identifiers

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23HH8238

Identifier Type: -

Identifier Source: org_study_id

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