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Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession

PURPOSE: Diffusion‐weighted steady‐state free precession (DW‐SSFP) is shown to provide a means to probe non‐Gaussian diffusion through manipulation of the flip angle. A framework is presented to define an effective b‐value in DW‐SSFP. THEORY: The DW‐SSFP signal is a summation of coherence pathways w...

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Autores principales: Tendler, Benjamin C., Foxley, Sean, Cottaar, Michiel, Jbabdi, Saad, Miller, Karla L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216928/
https://www.ncbi.nlm.nih.gov/pubmed/31922283
http://dx.doi.org/10.1002/mrm.28169
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author Tendler, Benjamin C.
Foxley, Sean
Cottaar, Michiel
Jbabdi, Saad
Miller, Karla L.
author_facet Tendler, Benjamin C.
Foxley, Sean
Cottaar, Michiel
Jbabdi, Saad
Miller, Karla L.
author_sort Tendler, Benjamin C.
collection PubMed
description PURPOSE: Diffusion‐weighted steady‐state free precession (DW‐SSFP) is shown to provide a means to probe non‐Gaussian diffusion through manipulation of the flip angle. A framework is presented to define an effective b‐value in DW‐SSFP. THEORY: The DW‐SSFP signal is a summation of coherence pathways with different b‐values. The relative contribution of each pathway is dictated by the flip angle. This leads to an apparent diffusion coefficient (ADC) estimate that depends on the flip angle in non‐Gaussian diffusion regimes. By acquiring DW‐SSFP data at multiple flip angles and modeling the variation in ADC for a given form of non‐Gaussianity, the ADC can be estimated at a well‐defined effective b‐value. METHODS: A gamma distribution is used to model non‐Gaussian diffusion, embedded in the Buxton signal model for DW‐SSFP. Monte‐Carlo simulations of non‐Gaussian diffusion in DW‐SSFP and diffusion‐weighted spin‐echo sequences are used to verify the proposed framework. Dependence of ADC on flip angle in DW‐SSFP is verified with experimental measurements in a whole, human postmortem brain. RESULTS: Monte‐Carlo simulations reveal excellent agreement between ADCs estimated with diffusion‐weighted spin‐echo and the proposed framework. Experimental ADC estimates vary as a function of flip angle over the corpus callosum of the postmortem brain, estimating the mean and standard deviation of the gamma distribution as [Formula: see text]  mm(2)/s and [Formula: see text]  mm(2)/s. CONCLUSION: DW‐SSFP can be used to investigate non‐Gaussian diffusion by varying the flip angle. By fitting a model of non‐Gaussian diffusion, the ADC in DW‐SSFP can be estimated at an effective b‐value, comparable to more conventional diffusion sequences.
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spelling pubmed-72169282020-05-13 Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession Tendler, Benjamin C. Foxley, Sean Cottaar, Michiel Jbabdi, Saad Miller, Karla L. Magn Reson Med Notes—Imaging Methodology PURPOSE: Diffusion‐weighted steady‐state free precession (DW‐SSFP) is shown to provide a means to probe non‐Gaussian diffusion through manipulation of the flip angle. A framework is presented to define an effective b‐value in DW‐SSFP. THEORY: The DW‐SSFP signal is a summation of coherence pathways with different b‐values. The relative contribution of each pathway is dictated by the flip angle. This leads to an apparent diffusion coefficient (ADC) estimate that depends on the flip angle in non‐Gaussian diffusion regimes. By acquiring DW‐SSFP data at multiple flip angles and modeling the variation in ADC for a given form of non‐Gaussianity, the ADC can be estimated at a well‐defined effective b‐value. METHODS: A gamma distribution is used to model non‐Gaussian diffusion, embedded in the Buxton signal model for DW‐SSFP. Monte‐Carlo simulations of non‐Gaussian diffusion in DW‐SSFP and diffusion‐weighted spin‐echo sequences are used to verify the proposed framework. Dependence of ADC on flip angle in DW‐SSFP is verified with experimental measurements in a whole, human postmortem brain. RESULTS: Monte‐Carlo simulations reveal excellent agreement between ADCs estimated with diffusion‐weighted spin‐echo and the proposed framework. Experimental ADC estimates vary as a function of flip angle over the corpus callosum of the postmortem brain, estimating the mean and standard deviation of the gamma distribution as [Formula: see text]  mm(2)/s and [Formula: see text]  mm(2)/s. CONCLUSION: DW‐SSFP can be used to investigate non‐Gaussian diffusion by varying the flip angle. By fitting a model of non‐Gaussian diffusion, the ADC in DW‐SSFP can be estimated at an effective b‐value, comparable to more conventional diffusion sequences. John Wiley and Sons Inc. 2020-01-10 2020-08 /pmc/articles/PMC7216928/ /pubmed/31922283 http://dx.doi.org/10.1002/mrm.28169 Text en © 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Notes—Imaging Methodology
Tendler, Benjamin C.
Foxley, Sean
Cottaar, Michiel
Jbabdi, Saad
Miller, Karla L.
Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title_full Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title_fullStr Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title_full_unstemmed Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title_short Modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
title_sort modeling an equivalent b‐value in diffusion‐weighted steady‐state free precession
topic Notes—Imaging Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216928/
https://www.ncbi.nlm.nih.gov/pubmed/31922283
http://dx.doi.org/10.1002/mrm.28169
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