Evaluation of a Free-breathing Cardiac Cine-MRI Sequence With Image Reconstructions by Deep-Learning in Ischemic Heart Disease

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

54 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-04-14

Study Completion Date

2024-01-29

Brief Summary

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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.

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Detailed Description

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Conditions

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Magnetic Resonance Imaging Cardiac Magnetic Resonance Imaging Deep-Learning Left Ventricular Ejection Fraction

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Age \> or = 18 years old
* Ischemic heart disease
* Ability of the subject to understand and express his consent
* Affiliation to the social security scheme

Exclusion Criteria

* 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

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No