  Differentiating Alzheimer's disease (AD) patients from healthy controls (HCs)
remains a challenge. The changes of protein level in cerebrospinal fluid (CSF)
of AD patients have been reported in the literature. Macromolecules will hinder
the movement of water in CSF and lead to non-Gaussian diffusion. Diffusion
kurtosis imaging (DKI) is a commonly used technique for quantifying
non-Gaussian diffusivity. In this study, we used DKI to evaluate the
non-Gaussian diffusion of CSF in AD patients and HC. Between-group difference
was explored. In addition, we have built a prediction model using
cross-validation Support Vector Machines (SVM), and achieved excellent
performance. The validated area under the receiver operating characteristic
curve(AUC) is in the range of 0.96-1.00, and the correct prediction is in the
range of 87.1% - 90.0%.
