Faster cardiac MRI using deep-learning image reconstruction to measure left ventricular ejection fraction
Official title: Evaluation of Left Ventricular Ejection Fraction Using an Accelerated Cardiac Cine-MRI Sequence With Deep Learning-based Image Reconstructions Compared to the Reference Cine-MRI Sequence in the Assessment or Follow-up of Left Ventricular Hypertrophy
Run by Centre Hospitalier Universitaire, Amiens · NCT07061821 · Data updated 2026-11-12
This will test whether a faster cardiac MRI scan using deep-learning reconstruction can accurately measure ejection fraction in adults referred for left ventricular hypertrophy.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 61 (estimated) |
| Sponsor | Centre Hospitalier Universitaire, Amiens Academic / other |
| Locations | 1 site (Amiens) |
| Status | Recruiting |
| Started | August 5, 2025 |
| Main results expected | September 2026 |
| Study ends | September 2026 |
| Registry record updated | January 16, 2026 |
| Trial ID | NCT07061821 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal participants are adults (18+) referred for cardiac MRI to evaluate or follow left ventricular hypertrophy who can give informed consent and meet MRI safety requirements.
✕Probably not a fit
Patients with arrhythmias, severe obesity preventing scanner entry, inability to hold breath for at least 10 seconds, claustrophobia, pregnancy, gadolinium allergy, or other MRI contraindications are unlikely to benefit or may be excluded.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Cardiac MRI is the reference standard for measuring left ventricular ejection fraction, but conventional cine sequences require multiple breath-holds that can be difficult for elderly or dyspneic patients. This project uses an accelerated cine-CMR sequence combined with deep learning-based image reconstruction to shorten acquisition time and reduce breath-hold requirements. Adults referred for CMR for left ventricular hypertrophy will undergo the accelerated imaging and results will be compared with standard cine techniques for LVEF, ventricular volumes, and image quality. The aim is to determine whether accelerated, DL-reconstructed images maintain diagnostic accuracy while improving patient comfort and scan efficiency.
Why it matters
Potential benefit: If successful, patients could have shorter, more comfortable MRI exams that still provide accurate ejection fraction measurements, which would particularly help elderly or breathless patients.
How similar studies have gone: Prior studies of accelerated cine MRI with deep-learning reconstructions have shown promising results for preserving image quality and LVEF accuracy, though broader clinical validation is still ongoing.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patient referred for cardiac MRI as part of the assessment or follow-up of left ventricular hypertrophy * Age ≥ 18 years old * Ability of the subject to understand and express his consent * Affiliation to the social security scheme Exclusion Criteria: * Severe obesity (\>140 kg) preventing the patient from entering the scanner bore, which has a diameter of less than 70 cm * Age ≥ 18 years old * Person under guardianship or curators, or deprived of liberty * Pregnant or breastfeeding woman * Known allergy to gadolinium chelates * Claustrophobia * Any contraindication to MRI * Arrhythmia * Inability to hold breath for more than 10 seconds
Where it's running
-
CHRU Amiens
Amiens, France Recruiting
Study contacts
- Study coordinator: Cédric Renard, MD
- Email: renard.cedric@chu-amiens.fr
- Phone: 33+3 22 08 75 37
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.