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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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| Measure | Description | Time Frame |
|---|---|---|
| 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 | 5 minutes |
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Inclusion Criteria:
Exclusion Criteria:
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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.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| CHU Amiens-Picardie | Amiens | France | 80000 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38323784 | Result | 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. |
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