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NCT Number: NCT06061822

Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation

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.

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Key information

Conditions

Cardiovascular Diseases Healthy Volunteers

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Imperial College Healthcare NHS Trust

London, United Kingdom

Location status: Recruiting

Location contact

James P Howard, MB BChir PhD

CONTACT

[email protected]

+447841124459

James P Howard, MB BChir PhD

PRINCIPAL_INVESTIGATOR

Who can participate

Healthy volunteers accepted: Yes

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

Inclusion criteria

  • Adult (aged at least 18 years)

Exclusion criteria

  • Children (patients below age 18).
  • Pregnant patients.

Treatment and study plan

AI-assisted cardiac magnetic resonance imaging

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.

Primary outcomes

  1. Time taken to acquire images

    Time frame: During the MRI scan

    The time taken in seconds from the beginning of the planning process, until the last planned images has been fully acquired.

  2. Image quality

    Time frame: During the MRI scan

    Quality of acquired images (AI-planning versus radiographer planning) assessed by level 3 cardiac MRI accredited doctors, by asking them to choose whether (a) the AI-acquired image is of higher diagnostic quality, (b) the radiographer-acquired image is of higher diagnostic quality, or (c) the AI- and radiographer-acquired images are of identical diagnostic quality.

Study contacts

Contact information is provided by the study sponsor or research team.

James P Howard, MB BChir PhD

CONTACT

[email protected]

+44 207 594 5735

Sponsors and collaborators

Lead sponsor

Imperial College London

Other

Collaborators

  • British Heart Foundation
  • Medical Research Council
  • Rosetrees Trust

Registry information

Acronym: AID-MR

Important dates

Study start
2026
Primary completion
2027
Study completion
2027
First posted
Sep 29, 2023
Registry last updated
May 11, 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.

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