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There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

Purpose: The reproducibility of neurite orientation dispersion and density imaging (NODDI) metrics in the human brain has not been explored across different magnetic resonance (MR) scanners from different vendors. This study aimed to evaluate the scan-rescan and inter-vendor reproducibility of NODDI metrics in white and gray matter of healthy subjects using two 3-T MR scanners from two vendors., Methods: Ten healthy subjects (7 males; mean age 30 ± 7 years, range 23-37 years) were included in the study. Whole-brain diffusion-weighted imaging was performed with b-values of 1000 and 2000 s/mm 2 using two 3-T MR scanners from two different vendors. Automatic extraction of the region of interest was performed to obtain NODDI metrics for whole and localized areas of white and gray matter. The coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated to assess the scan-rescan and inter-vendor reproducibilities of NODDI metrics., Results: The scan-rescan and inter-vendor reproducibility of NODDI metrics (intracellular volume fraction and orientation dispersion index) were comparable with those of diffusion tensor imaging (DTI) metrics. However, the inter-vendor reproducibilities of NODDI (CoV = 2.3-14%) were lower than the scan-rescan reproducibility (CoV: scanner A = 0.8-3.8%; scanner B = 0.8-2.6%). Compared with the finding of DTI metrics, the reproducibility of NODDI metrics was lower in white matter and higher in gray matter., Conclusion: The lower inter-vendor reproducibility of NODDI in some brain regions indicates that data acquired from different MRI scanners should be carefully interpreted.

Background: Although pathological studies usually indicate pure dopaminergic neuronal degeneration in patients with parkin (PRKN) mutations, there is no evidence to date regarding white matter (WM) pathology. A previous diffusion MRI study has revealed WM microstructural alterations caused by systemic oxidative stress in idiopathic Parkinson's disease (PD), and we found that PRKN patients have systemic oxidative stress in serum biomarker studies. Thus, we hypothesized that PRKN mutations might lead to WM abnormalities. Objective: To investigate whether there are WM microstructural abnormalities in early-onset PD patients with PRKN mutations using diffusion tensor imaging (DTI). Methods: Nine PRKN patients and 15 age- and sex-matched healthy controls were recruited. DTI measures were acquired on a 3T MR scanner using a b value of 1,000 s/mm2 along 32 isotropic diffusion gradients. The DTI measures were compared between groups using tract-based spatial statistics (TBSS) analysis. Correlation analysis was also performed between the DTI parameters and several serum oxidative stress markers obtained in a previously conducted metabolomic analysis. Results: Although the WM volumes were not significantly different, the TBSS analysis revealed a corresponding decrease in fractional anisotropy and an increase in mean diffusivity and radial diffusivity in WM areas, such as the anterior and superior corona radiata and uncinate fasciculus, in PRKN patients compared with controls. Furthermore, 9-hydroxystearate, an oxidative stress marker, and disease duration were positively correlated with several parameters in PRKN patients. Conclusion: This pilot study suggests that WM microstructural impairments occur in PRKN patients and are associated with disease duration and oxidative stress. [ABSTRACT FROM AUTHOR]

The incidence of neurodegenerative diseases has shown an increasing trend. These conditions typically cause progressive functional disability. Identification of robust biomarkers of neurodegenerative diseases is a key imperative to facilitate early identification of the pathological features and to foster a better understanding of the pathogenetic mechanisms of individual diseases. Diffusion tensor imaging (DTI) is the most widely used diffusion MRI technique for assessment of neurodegenerative diseases. The DTI parameters are promising biomarkers for evaluation of microstructural changes; however, some limitations of DTI restrict its wider clinical use. New diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), bi‐tensor DTI, and neurite orientation density and dispersion imaging (NODDI) have been demonstrated to provide value addition to DTI for evaluation of neurodegenerative diseases. In this review article, we summarize the key technical aspects and provide an overview of the current state of knowledge regarding the role of DKI, bi‐tensor DTI, and NODDI as biomarkers of microstructural changes in representative neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. Level of Evidence: 5 Technical Efficacy Stage: 2 J. MAGN. RESON. IMAGING 2020;52:1620–1636. [ABSTRACT FROM AUTHOR]

Introduction: Levodopa-induced dyskinesia is a complication of levodopa therapy and negatively impacts the quality of life of patients. We aimed to elucidate white matter alterations in Parkinson's disease with levodopa-induced dyskinesia using advanced diffusion magnetic resonance imaging techniques.Methods: The enrolled subjects included 26 clinically confirmed Parkinson's disease patients without levodopa-induced dyskinesia, 25 Parkinson's disease patients with levodopa-induced dyskinesia, and 23 healthy controls. Subjects were imaged using a 3-T magnetic resonance scanner. Diffusion tensor imaging, diffusion kurtosis imaging, and neurite orientation dispersion and density imaging findings were compared between groups with a group-wise whole brain approach and a region-of-interest analysis for each white matter tract. Additionally, logistic regression analysis was used to calculate odds ratios for levodopa-induced dyskinesia.Results: Group-wise tract-based spatial statistical analysis revealed significant white matter differences in isotropic diffusion, complexity, or heterogeneity, and neurite density between healthy controls and Parkinson's disease patients without levodopa-induced dyskinesia and between patients with and without levodopa-induced dyskinesia. Region-of-interest analysis revealed similar alterations using a group-wise whole-brain approach in the external capsule, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and uncinate fasciculus. These tracts had an odds ratio of approximately 2.3 for the presence of levodopa-induced dyskinesia.Conclusions: Our findings suggest that Parkinson's disease with levodopa-induced dyskinesia produces less white matter microstructural disruption, especially in temporal lobe fibers, than Parkinson's disease without levodopa-induced dyskinesia. These fibers has a more than 2-fold odds ratio for the presence of levodopa-induced dyskinesia and might be associated with the pathogenesis of the sequela. [ABSTRACT FROM AUTHOR]