Validation of Diffusion Kurtosis Imaging as an Early-Stage Biomarker of Parkinson's Disease in Animal Models

Diffusion kurtosis imaging (DKI), which is a mathematical extension of diffusion tensor imaging (DTI), assesses non-Gaussian water diffusion in the brain. DKI proved to be effective in supporting the diagnosis of different neurodegenerative disorders. Its sensitively detects microstructural changes in the brain induced by either protein accumulation, glial cell activation or neurodegeneration as observed in mouse models of Parkinson's disease. We applied two experimental models of Parkinson's disease to validate the diagnostic utility of DKI in early and late stage of disease pathology. We present two DKI analysis methods: (1) tract based spatial statistics (TBSS), which is a hypothesis independent data driven approach intended to evaluate white matter changes; and (2) region of interest (ROI) based analysis based on hypothesis of ROIs relevant for Parkinson's disease, which is specifically used for gray matter changes. The main aim of this chapter is to provide detailed information of how to perform the DKI imaging acquisition and analysis in the mouse brain, which can be, to some extent translated to humans.