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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 hinderthe movement of water in CSF and lead to non-Gaussian diffusion. Diffusionkurtosis imaging (DKI) is a commonly used technique for quantifyingnon-Gaussian diffusivity. In this study, we used DKI to evaluate thenon-Gaussian diffusion of CSF in AD patients and HC. Between-group differencewas explored. In addition, we have built a prediction model usingcross-validation Support Vector Machines (SVM), and achieved excellentperformance. The validated area under the receiver operating characteristiccurve(AUC) is in the range of 0.96-1.00, and the correct prediction is in therange of 87.1% - 90.0%.

Characterize the non-Gaussian diffusion property of cerebrospinal fluid  using Diffusion Kurtosis Imaging and explore its diagnostic efficacy for  Alzheimer's disease