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NCT05105984: CINEDL
Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions by Deep-Learning in Ischemic Heart Disease
trial in Magnetic Resonance Imaging in 54 participants. Completed in 29 January 2024.
24 April 2023
Quick facts
| Lead sponsor | Centre Hospitalier Universitaire, Amiens |
|---|---|
| Status | Completed |
| Study type | OBSERVATIONAL |
| Enrollment | 54 |
| Start date | 14 April 2022 |
| Primary completion | 24 April 2023 |
| Estimated completion | 29 January 2024 |
| Sites | 1 location across France |
Conditions studied
- Magnetic Resonance Imaging — all drugs for Magnetic Resonance Imaging →
- Cardiac Magnetic Resonance Imaging — all drugs for Cardiac Magnetic Resonance Imaging →
- Deep-Learning — all drugs for Deep-Learning →
- Left Ventricular Ejection Fraction — all drugs for Left Ventricular Ejection Fraction →
Sponsor
Centre Hospitalier Universitaire, Amiens
Who can join
18 and older, any sex, with Magnetic Resonance Imaging or Cardiac Magnetic Resonance Imaging. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Today, MRI is the gold standard for the precise assessment of left ventricular volume and function, but presents the drawback of having a long acquisition time and of generating motion artifacts, in particular respiratory artifacts, requiring repeated sequences in apnea to cover the whole cardiac volume. These apneas are difficult to achieve in patients with ischemic heart disease and may lead to degradation of the images, an increase in the duration of the examination by repeated acquisitions and therefore to diagnostic inaccuracies. Artificial intelligence, already used in practice in cardiac MRI for automatic segmentation of the heart chambers, improves radiological interpretation with rapid and precise measurements. Deep-learning, which is part of artificial intelligence, would allow the reconstruction of cine-MRI sequences in free breathing, in order to overcome the artifacts from respiratory motions, and the improvement of diagnostic performance while improving examination conditions for patients. Patients coming for a cardiac MRI for the assessment of ischemic heart disease will be eligible to the protocol. If the patient agrees to participate, a free-breathing cardiac cine-MRI sequence with Deep Learning based image reconstruction will be added to the usual protocol. No follow-up will be required in this study.
Publications & conference data
1 peer-reviewed publication reference this trial (live from Europe PMC):
-
Prospective Comparison of Free-Breathing Accelerated Cine Deep Learning Reconstruction Versus Standard Breath-Hold Cardiac MRI Sequences in Patients With Ischemic Heart Disease.
Monteuuis D, Bouzerar R, Dantoing C, Poujol J, et al · · 2024 · cited 8× · PMID 38323784 · DOI 10.2214/ajr.23.30272
Verify or expand the search:
- PubMed search for NCT05105984
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT05105984 (US National Library of Medicine, public domain)
- Publications: Europe PMC API search by NCT ID, retrieved 10 June 2026
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Centre Hospitalier Universitaire, Amiens
- Last refreshed: 19 November 2025
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05105984.
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