Affiliations: Institute of Medical Imaging and Engineering, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, USST, Yangpu District, Shanghai, China
Correspondence:
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Corresponding author: Sheng Dong Nie, Institute of Medical Imaging and Engineering, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, USST, No 516, Jungong Road, Yangpu District, Shanghai 200093, China. Tel.: +8621 55271172; Fax: +8621 55270695; E-mail: [email protected].
Abstract: In order to diagnose Parkinson disease (PD) at an early stage, it is important to develop a sensitive method for detecting structural changes in the substantia nigra (SN). Diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) have become important tools in supporting diagnosis of PD, with findings based on increased apparent diffusion coefficients (ADCs) in basal ganglia and decreased fractional anisotropy (FA) in SN. Based on the hypothesis that a diffusion kurtosis imaging (DKI) theory is a valuable method for PD diagnosis based on the non-Gaussian diffusion of water in biologic systems, the purpose of this study is to develop an image processing scheme (software) based on Image-J for the facilitating the application of DKI to assist PD diagnosis. Using the new DKI software enables to estimate the diffusional kurtosis and diffusion coefficients, which reflect the structural differences between regions of interest. The experimental results of applying the new software showed that diffusional kurtosis was highly sensitive to microstructural tissue changes, which were not noticeable in the diffusion coefficient values. Thus, the study results may suggest that applying the new image processing software can be useful for assessing tissue structural abnormalities, monitoring and following disease progression.
Keywords: Parkinson’s disease, diffusional kurtosis imaging, substantia nigra
