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Recruiting NCT06061822

NCT06061822 Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation

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Clinical Trial Summary
NCT ID NCT06061822
Status Recruiting
Phase
Sponsor Imperial College London
Condition Cardiovascular Diseases
Study Type INTERVENTIONAL
Enrollment 150 participants
Start Date 2026-05-01
Primary Completion 2027-12-01

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age N/A
Study Type INTERVENTIONAL
Interventions
AI-assisted cardiac magnetic resonance imaging

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

You will actively receive the study intervention — which may be a drug, biologic, device, or procedure.

This trial targets 150 participants in total. It began in 2026-05-01 with a primary completion date of 2027-12-01.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief 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 Criteria

Inclusion Criteria: * Adult (aged at least 18 years) Exclusion Criteria: * Children (patients below age 18). * Pregnant patients.

Contact & Investigator

Central Contact

James P Howard, MB BChir PhD

✉ james.howard1@imperial.ac.uk

📞 +44 207 594 5735

Principal Investigator

James P Howard, MB BChir PhD

PRINCIPAL INVESTIGATOR

Imperial College London

Frequently Asked Questions

Who can join the NCT06061822 clinical trial?

This trial is open to participants of all sexes, aged 18 Years or older, studying Cardiovascular Diseases. Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT06061822 currently recruiting?

Yes, NCT06061822 is actively recruiting participants. Contact the research team at james.howard1@imperial.ac.uk for enrollment information.

Where is the NCT06061822 trial being conducted?

This trial is being conducted at London, United Kingdom.

Who is sponsoring the NCT06061822 clinical trial?

NCT06061822 is sponsored by Imperial College London. The principal investigator is James P Howard, MB BChir PhD at Imperial College London. The trial plans to enroll 150 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: July 2026  ·  Data Methodology