Abstract #3095

A physically-constrained model for diffusion kurtosis imaging

Darryl McClymont¹, Irvin Teh¹, Hannah Whittington¹, Vicente Grau², and Jurgen Schneider¹

¹Division of Cardiovascular Medicine, University of Oxford, Oxford, United Kingdom, ²Department of Engineering Science, University of Oxford, Oxford, United Kingdom

Diffusion kurtosis imaging provides higher-order information about diffusion. However, the quadratic term in the diffusion kurtosis model produces undesirable behaviour at high b-values as a result of the negative tails of the diffusivity distribution. A truncated normal distribution has been proposed to address this in one dimension. This work extends this concept to a multivariate truncated normal distribution, and extends the range of b-values over which kurtosis can be estimated. The proposed model is fit to diffusion data from rat hearts, and yields kurtosis values that are consistent with the DKI model.

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