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Modeling an equivalent b-value in diffusion-weighted steady-state free precession. | LitMetric

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

Magn Reson Med

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.

Published: August 2020


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Article Abstract

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  mm /s and  mm /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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216928PMC
http://dx.doi.org/10.1002/mrm.28169DOI Listing

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