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Abstract #2599

Accelerating Diffusion Kurtosis Acquisition using SIR and Model-Based Reconstruction

Christopher Lee Welsh 1 , Edward W Hsu 1 , and Edward VR DiBella 2

1 Department of Bioengineering, University of Utah, Salt Lake City, UT, United States, 2 Radiology, UCAIR, University of Utah, Salt Lake City, UT, United States

Diffusion kurtosis imaging (DKI) is a way to model tissue microstructure that is more realistic than DTI since it measures the degree of non-Gaussian diffusion. However, DKI requires a long scan time. A model-based strategy is presented to estimate diffusion and kurtosis tensors directly from accelerated k-space data. The accuracy of the model-based method with an acceleration factor of 3 was compared to using all acquired data. The findings suggest the proposed strategy can be used to reduce DKI scan time if used in conjunction with SIR, while still characterizing non-Gaussian diffusion and neural fiber crossings without loss of accuracy.

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