5D whole-heart sparse MRI.
Magn Reson Med
; 79(2): 826-838, 2018 02.
Article
en En
| MEDLINE
| ID: mdl-28497486
PURPOSE: A 5D whole-heart sparse imaging framework is proposed for simultaneous assessment of myocardial function and high-resolution cardiac and respiratory motion-resolved whole-heart anatomy in a single continuous noncontrast MR scan. METHODS: A non-electrocardiograph (ECG)-triggered 3D golden-angle radial balanced steady-state free precession sequence was used for data acquisition. The acquired 3D k-space data were sorted into a 5D dataset containing separated cardiac and respiratory dimensions using a self-extracted respiratory motion signal and a recorded ECG signal. Images were then reconstructed using XD-GRASP, a multidimensional compressed sensing technique exploiting correlations/sparsity along cardiac and respiratory dimensions. 5D whole-heart imaging was compared with respiratory motion-corrected 3D and 4D whole-heart imaging in nine volunteers for evaluation of the myocardium, great vessels, and coronary arteries. It was also compared with breath-held, ECG-gated 2D cardiac cine imaging for validation of cardiac function quantification. RESULTS: 5D whole-heart images received systematic higher quality scores in the myocardium, great vessels and coronary arteries. Quantitative coronary sharpness and length were always better for the 5D images. Good agreement was obtained for quantification of cardiac function compared with 2D cine imaging. CONCLUSION: 5D whole-heart sparse imaging represents a robust and promising framework for simplified comprehensive cardiac MRI without the need for breath-hold and motion correction. Magn Reson Med 79:826-838, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Imagen por Resonancia Magnética
/
Imagenología Tridimensional
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Técnicas de Imagen Cardíaca
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Corazón
Límite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Magn Reson Med
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Estados Unidos