RecruitingNot ApplicableNCT06061822

Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation


Sponsor

Imperial College London

Enrollment

150 participants

Start Date

Sep 9, 2025

Study Type

INTERVENTIONAL

Conditions

Summary

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.


Eligibility

Min Age: 18 Years

Inclusion Criteria1

  • Adult (aged at least 18 years)

Exclusion Criteria2

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

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Interventions

DIAGNOSTIC_TESTAI-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.


Locations(1)

Imperial College Healthcare NHS Trust

London, United Kingdom

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NCT06061822


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