Artificial Intelligence Delivered Cardiac Magnetic Resonance - Prospective Validation
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-assisted cardiac magnetic resonance imaging.
- Who it may be relevant to
- Registry conditions: Cardiovascular Diseases, Healthy Volunteers. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United Kingdom
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Interventions
- Diagnostic test 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.
Primary outcome measures
- Time taken to acquire images [Time frame: During the MRI scan]
- Image quality [Time frame: During the MRI scan]
Eligibility criteria
Inclusion criteria
- Adult (aged at least 18 years)
Exclusion criteria
- Children (patients below age 18).
- Pregnant patients.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Crossover
- Masking
- Double blind
- Primary purpose
- Diagnostic
Study locations
United Kingdom · 1 center
- Imperial College Healthcare NHS Trust — London
Identifiers
NCT: NCT06061822 · 23HH8238