Magnetic Resonance ImagingCINEDLNCT05105984
Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions by Deep-Learning in Ischemic Heart Disease
An observational study of Magnetic Resonance Imaging and Cardiac Magnetic Resonance Imaging, run by Centre Hospitalier Universitaire, Amiens at 1 site in France.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Magnetic Resonance Imaging, Cardiac Magnetic Resonance Imaging, Deep-Learning
- How many people
- 54 participants
- Where
- 1 siteFrance
- Study dates
- 14 Apr 2022to 29 Jan 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Cardiac MRI is one of the examinations prescribed as part of routine care for this pathology. When the patient come for a cardiac MRI in the workup for ischemic heart disease, the patient will be asked on the day of the exam if he agrees to participate in the study. An information letter will have been sent to the patient before the appointment is made. In the event that he agrees to participate, a free-breathing cardiac cine-MRI sequence with Deep Learning based image reconstruction will be appended to the usual protocol.
Who may be able to join
- Age > or = 18 years old
- Ischemic heart disease
- Ability of the subject to understand and express his consent
- Affiliation to the social security scheme
Who cannot join
- Major obesity (> 140kg) not allowing the patient to enter the tunnel of the machine whose diameter is less than 70cm
- Under 18 years old
- Pregnant woman
- Known allergy to gadolinium chelates
- Claustrophobia
- Any contraindication to MRI
- Arrhythmia
- Difficulty in holding apneas of more than 10 seconds
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions Developed by Deep-Learning Compared to the Classic Apnea Cine-MRI Sequence in the Assessment of Ischemic Heart Disease.
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.
Read more
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.
- Conditions
- Magnetic Resonance Imaging, Cardiac Magnetic Resonance Imaging, Deep-Learning, Left Ventricular Ejection Fraction
- Keywords
- Magnetic resonance imaging, Cardiac magnetic resonance imaging, Deep-Learning, Left ventricular ejection fraction, Left ventricular end systolic volume, left ventricular end diastolic volume
What is being measured
The primary outcome is the main question the study is designed to answer.
difference of LVEF measurements between Deep Learning reconstruction and the classic cine-MRI sequence
difference of LVEF measurements between Deep Learning reconstruction and the classic cine-MRI sequence
Measured: 5 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Nov 2021
- Study start14 Apr 2022
- Primary completion24 Apr 2023
- Study completion29 Jan 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Magnetic Resonance ImagingStudies of the same condition, open and under way.
- More trials run by Centre Hospitalier Universitaire, AmiensThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 54 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire, Amiens
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05105984
- Sponsor's protocol ID
- PI2021_843_0157
- Acronym
- CINEDL
- Status last verified
- Nov 2025
- First submitted
- 2 Nov 2021
- Last updated
- 19 Nov 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Monteuuis D, Bouzerar R, Dantoing C, Poujol J, Bohbot Y, Renard C. Prospective Comparison of Free-Breathing Accelerated Cine Deep Learning Reconstruction Versus Standard Breath-Hold Cardiac MRI Sequences in Patients With Ischemic Heart Disease. AJR Am J Roentgenol. 2024 May;222(5):e2330272. doi: 10.2214/AJR.23.30272. Epub 2024 Feb 7.
PubMed 38323784
Study at a glance
From the registry record, last updated by the sponsor on 19 Nov 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions Developed by Deep-Learning Compared to the Classic Apnea Cine-MRI Sequence in the Assessment of Ischemic Heart Disease.
- ClinicalTrials.gov ID
- NCT05105984
- Acronym / sponsor ID
- CINEDL / PI2021_843_0157
- Conditions
- Magnetic Resonance Imaging, Cardiac Magnetic Resonance Imaging, Deep-Learning, Left Ventricular Ejection Fraction
- Keywords
- Magnetic resonance imaging, Cardiac magnetic resonance imaging, Deep-Learning, Left ventricular ejection fraction, Left ventricular end systolic volume, left ventricular end diastolic volume
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 54 participants (actual)
- Lead sponsor
- Centre Hospitalier Universitaire, AmiensUniversity, hospital or other
- Study start
- 14 Apr 2022 (actual)
- Primary completion
- 24 Apr 2023 (actual)
- Study completion
- 29 Jan 2024 (actual)
- First posted
- 3 Nov 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Cardiac MRI is one of the examinations prescribed as part of routine care for this pathology. When the patient come for a cardiac MRI in the workup for ischemic heart disease, the patient will be asked on the day of the exam if he agrees to participate in the study. An information letter will have been sent to the patient before the appointment is made. In the event that he agrees to participate, a free-breathing cardiac cine-MRI sequence with Deep Learning based image reconstruction will be appended to the usual protocol.
Key inclusion criteria (4 listed)
- Age > or = 18 years old
- Ischemic heart disease
- Ability of the subject to understand and express his consent
- Affiliation to the social security scheme
Key exclusion criteria (8 listed)
- Major obesity (> 140kg) not allowing the patient to enter the tunnel of the machine whose diameter is less than 70cm
- Under 18 years old
- Pregnant woman
- Known allergy to gadolinium chelates
- Claustrophobia
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
difference of LVEF measurements between Deep Learning reconstruction and the classic cine-MRI sequence
Time frame: 5 minutes
difference of LVEF measurements between Deep Learning reconstruction and the classic cine-MRI sequence
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Nov 2025.
- Results publication: PubMed 38323784Monteuuis D, Bouzerar R, Dantoing C, Poujol J, Bohbot Y, Renard C. Prospective Comparison of Free-Breathing Accelerated Cine Deep Learning Reconstruction Versus Standard Breath-Hold Cardiac MRI Sequences in Patients With Ischemic Heart Disease. AJR Am J Roentgenol. 2024 May;222(5):e2330272. doi: 10.2214/AJR.23.30272. Epub 2024 Feb 7.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Magnetic Resonance Imaging and Cardiac Magnetic Resonance Imaging, run by Centre Hospitalier Universitaire, Amiens at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Nov 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
difference of LVEF measurements between Deep Learning reconstruction and the classic cine-MRI sequence (time frame: 5 minutes). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05105984, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Nov 2025.