Abstract

We used neurite orientation dispersion and density imaging (NODDI) to quantify changes in the substantia nigra pars compacta (SNpc) and striatum in Parkinson disease (PD). Diffusion-weighted magnetic resonance images were acquired from 58 PD patients and 36 age- and sex-matched controls. The intracellular volume fraction (Vic), orientation dispersion index (OD), and isotropic volume fraction (Viso) of the basal ganglia were compared between groups. Multivariate logistic regression analysis determined which diffusion parameters were independent predictors of PD. Receiver operating characteristic (ROC) analysis compared the diagnostic accuracies of the evaluated indices. Pearson coefficient analysis correlated each diffusional parameter with disease severity. Vic in the contralateral SNpc and putamen were significantly lower in PD patients than in healthy controls (P < 0.00058). Vic and OD in the SNpc and putamen showed significant negative correlations (P < 0.05) with disease severity. Multivariate logistic analysis revealed that Vic (P = 0.0000046) and mean diffusivity (P = 0.019) in the contralateral SNpc were the independent predictors of PD. In the ROC analysis, Vic in the contralateral SNpc showed the best diagnostic performance (mean cutoff, 0.62; sensitivity, 0.88; specificity, 0.83). NODDI is likely to be useful for diagnosing PD and assessing its progression. • Neurite orientation dispersion and density imaging (NODDI) is a new diffusion MRI technique • NODDI estimates neurite microstructure more specifically than diffusion tensor imaging • By using NODDI, nigrostriatal alterations in PD can be evaluated in vivo • NOODI is useful for diagnosing PD and assessing its disease progression.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.