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Abstract #0699

Experimentally and Computationally Fast Method for Estimation of the Mean Kurtosis

Brian Hansen1, Torben E. Lund1, Ryan Sangill1, Sune N. Jespersen1, 2

1CFIN, Aarhus University, Aarhus C, Denmark; 2Department of Physics, Aarhus University, Aarhus C, Denmark

Diffusion kurtosis imaging is a popular extension of diffusion tensor imaging accounting for nongaussian aspects of diffusion in biological tissue. Recently, several studies have indicated enhanced sensitivity of mean kurtosis (MK) to pathology, including stroke. However, lengthy acquisition time and postprocessing remains an obstacle for the exploration of further clinical applications. Here we propose a very fast acquisition and postprocessing scheme based on a linear combination of 13 diffusion weighted images for estimation of a new mean kurtosis metric, the trace of the kurtosis tensor, which is then shown to have very similar contrast to MK in the human brain.