Multi-echo MR thermometry using iterative separation of baseline water and fat images.
Magn Reson Med
; 81(4): 2385-2398, 2019 04.
Article
em En
| MEDLINE
| ID: mdl-30394582
ABSTRACT
PURPOSE:
To perform multi-echo water/fat separated proton resonance frequency (PRF)-shift temperature mapping.METHODS:
State-of-the-art, iterative multi-echo water/fat separation algorithms produce high-quality water and fat images in the absence of heating but are not suitable for real-time imaging due to their long compute times and potential errors in heated regions. Existing fat-referenced PRF-shift temperature reconstruction methods partially address these limitations but do not address motion or large time-varying and spatially inhomogeneous B0 shifts. We describe a model-based temperature reconstruction method that overcomes these limitations by fitting a library of separated water and fat images measured before heating directly to multi-echo data measured during heating, while accounting for the PRF shift with temperature.RESULTS:
Simulations in a mixed water/fat phantom with focal heating showed that the proposed algorithm reconstructed more accurate temperature maps in mixed tissues compared to a fat-referenced thermometry method. In a porcine phantom experiment with focused ultrasound heating at 1.5 Tesla, temperature maps were accurate to within 1∘ C of fiber optic probe temperature measurements and were calculated in 0.47 s per time point. Free-breathing breast and liver imaging experiments demonstrated motion and off-resonance compensation. The algorithm can also accurately reconstruct water/fat separated temperature maps from a single echo during heating.CONCLUSIONS:
The proposed model-based water/fat separated algorithm produces accurate PRF-shift temperature maps in mixed water and fat tissues in the presence of spatiotemporally varying off-resonance and motion.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Imageamento por Ressonância Magnética
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Água
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Termografia
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Tecido Adiposo
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Fígado
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Animals
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Female
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Humans
Idioma:
En
Revista:
Magn Reson Med
Assunto da revista:
DIAGNOSTICO POR IMAGEM
Ano de publicação:
2019
Tipo de documento:
Article