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Bias and precision analysis of diffusional kurtosis imaging for different acquisition schemes

Diffusional kurtosis imaging (DKI) is an approach to characterizing the non‐Gaussian fraction of water diffusion in biological tissue. However, DKI is highly susceptible to the low signal‐to‐noise ratio of diffusion‐weighted images, causing low precision and a significant bias due to Rician noise distribution. Here, we evaluate precision and bias using weighted linear least squares fitting of different acquisition schemes including several multishell schemes, a diffusion spectrum imaging (DSI) scheme, as well as a compressed sensing reconstruction of undersampled DSI scheme.