Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation

Not Applicable

Not yet recruiting

• Conditions: Cardiovascular Diseases; Healthy Volunteers
• Interventions: Diagnostic Test: AI-assisted cardiac magnetic resonance imaging

• Registration Number: NCT06061822
• Lead Sponsor: Imperial College London

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2023-09-18
• Study First Submitted QC: 2023-09-25
• Study First Posted: 2023-09-29
• Status Verified: 2025-01
• Last Update Submitted: 2025-01-06
• Last Update Posted: 2025-01-08
• Study Start: 2025-03-01
• Primary Completion: 2027-12-01
• Study Completion: 2027-12-01

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 150

Inclusion Criteria

• Adult (aged at least 18 years)

Exclusion Criteria

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

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: CROSSOVER

Arm && Interventions

Group	Intervention	Description
AI-planned images acquired	AI-assisted cardiac magnetic resonance imaging	-
Radiographer-planned images acquired	AI-assisted cardiac magnetic resonance imaging	-

Primary Outcome Measures

Name	Time	Method
Time taken to acquire images	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.
Image quality	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.