Dual-Pathway sequences for MR thermometry: When and where to use them.
Magn Reson Med
; 77(3): 1193-1200, 2017 03.
Article
em En
| MEDLINE
| ID: mdl-26968318
PURPOSE: Dual-pathway sequences have been proposed to help improve the temperature-to-noise ratio (TNR) in MR thermometry. The present work establishes how much of an improvement these so-called "PSIF-FISP" sequences may bring in various organs and tissues. METHODS: Simulations and TNR calculations were validated against analytical equations, phantom, abdomen, and brain scans. Relative TNRs for PSIF-FISP, as compared to a dual-FISP reference standard, were calculated for flip angle (FA) = 1 to 85 º and repetition time (TR) = 6 to 60 ms, for gray matter, white matter, cervix, endometrium, myometrium, prostate, kidney medulla and cortex, bone marrow, pancreas, spleen, muscle, and liver tissues. RESULTS: PSIF-FISP was TNR superior in the kidney, pelvis, spleen, or gray matter at most tested TR and FA settings, and benefits increased at shorter TRs. PSIF-FISP was TNR superior in other tissues, e.g., liver, muscle, pancreas, for only short TR settings (20 ms or less). The TNR benefits of PSIF-FISP increased slightly with FA, and strongly with decreasing TR. Up to two- to three-fold reductions in TR with 20% TNR gains were achievable. In any given tissue, TNR performance is expected to further improve with heating, due to changes in relaxation rates. CONCLUSION: Dual-pathway PSIF-FISP can improve TNR and acquisition speed over standard gradient-recalled echo sequences, but optimal acquisition parameters are tissue dependent. Magn Reson Med 77:1193-1200, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Temperatura Corporal
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Algoritmos
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Processamento de Sinais Assistido por Computador
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
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Termografia
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Revista:
Magn Reson Med
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Turquia
País de publicação:
Estados Unidos