Ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) for simultaneous quantification of long and ultrashort T2 tissues.
Magn Reson Med
; 82(4): 1359-1372, 2019 10.
Article
en En
| MEDLINE
| ID: mdl-31131911
PURPOSE: To demonstrate an ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) method that allows quantifying relaxation times for muscle and bone in the musculoskeletal system and generating bone enhanced images that mimic CT scans. METHODS: A fast imaging steady-state free precession MRF sequence with half pulse excitation and half projection readout was designed to sample fast T2 decay signals. Varying echo time (TE) of a sinusoidal pattern was applied to enhance sensitivity for tissues with short and ultrashort T2 values. The performance of UTE-MRF was evaluated via simulations, phantom, and in vivo experiments. RESULTS: A minimal TE of 0.05 ms was achieved. Simulations indicated the sinusoidal TE sampling increased T2 quantification accuracy in the cortical bone and tendon but had little impact on long T2 muscle quantifications. For the rubber phantom, the averaged relaxometries from UTE-MRF (T1 = 162 ms and T2 = 1.07 ms) compared well with the gold standard (T1 = 190 ms and T2∗ = 1.03 ms). For the long T2 agarose phantom, the linear regression slope between UTE-MRF and gold standard was 1.07 (R2 = 0.991) for T1 and 1.04 (R2 = 0.994) for T2 . In vivo experiments showed the detection of the cortical bone (averaged T2 = 1.0 ms) and Achilles tendon (averaged T2 = 15 ms). Scalp structures from the bone enhanced image show high similarity with CT. CONCLUSION: The UTE-MRF with sinusoidal TEs can simultaneously quantify T1 , T2 , proton density, and B0 in long, short, even ultrashort T2 musculoskeletal structures. Bone enhanced images can be achieved in the brain with UTE-MRF.
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Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Procesamiento de Imagen Asistido por Computador
/
Imagen por Resonancia Magnética
Límite:
Humans
Idioma:
En
Revista:
Magn Reson Med
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2019
Tipo del documento:
Article
País de afiliación:
China