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Introduction: Monoamine oxidase type B inhibitors, including selegiline, are established as anti-Parkinsonian Drugs. Inhibition of monoamine oxidase type B enzymes might suppress the inflammation because of inhibition to generate reactive oxygen species. However, its effect on brain microstructure remains unclear. The aim of this study is to elucidate white matter and substantia nigra (SN) microstructural differences between Patients with Parkinson's disease with and without selegiline treatment by two independently recruited cohorts., Methods: Diffusion tensor imaging and free water imaging indices of WM and SN were compared among 22/15 Patients with Parkinson's disease with selegiline (PDselegiline(+)), 33/23 Patients with Parkinson's disease without selegiline (PDselegiline(-)), and 25/20 controls, in the first/second cohorts. Two cohorts were analyzed with different MRI protocols., Results: Diffusion tensor imaging and free-water indices of major white matter tracts were significantly differed between the PDselegiline(-) and controls in both cohorts, although not between the PDselegiline(+) and controls except for restricted areas. Compared with the PDselegiline(+), free-water was significantly higher in the PDselegiline(-) in the inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and superior and posterior corona radiata (first cohort) and the forceps major and splenium of the corpus callosum (second cohort). There were no significant differences in free-water of anterior or posterior substantia nigra between PDselegiline(+) and PDselegiline(-)., Conclusions: Selegiline treatment might reduce the white matter microstructural abnormalities detected by free-water imaging in Parkinson's disease., Competing Interests: Declaration of competing interest None., (Copyright © 2023. Published by Elsevier B.V.)

Background: Patients with Parkinson's disease (PD) carrying GBA gene mutations (GBA-PD) have a more aggressive disease course than those with idiopathic PD (iPD)., Objective: The objective of this study was to investigate fiber-specific white matter (WM) differences in nonmedicated patients with early-stage GBA-PD and iPD using fixel-based analysis, a novel technique to assess tract-specific WM microstructural and macrostructural features comprehensively., Methods: Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross section (FC), and a combination of FD and FC (FDC), were compared among 30 healthy control subjects, 16 patients with GBA-PD, and 35 patients with iPD. Associations between FDC and clinical evaluations were also explored using multiple linear regression analyses., Results: Patients with GBA-PD showed significantly lower FD in the fornix and superior longitudinal fasciculus than healthy control subjects, and lower FC in the corticospinal tract (CST) and lower FDC in the CST, middle cerebellar peduncle, and striatal-thalamo-cortical pathways than patients with iPD. Contrarily, patients with iPD showed significantly higher FC and FDC in the CST and striatal-thalamo-cortical pathways than healthy control subjects. In addition, lower FDC in patients with GBA-PD was associated with reduced glucocerebrosidase enzyme activity, lower cerebrospinal fluid total α-synuclein levels, lower Montreal Cognitive Assessment scores, lower striatal binding ratio, and higher Unified Parkinson's Disease Rating Scale Part III scores., Conclusions: We report reduced fiber-specific WM density and bundle cross-sectional size in patients with GBA-PD, suggesting neurodegeneration linked to glucocerebrosidase deficiency, α-synuclein accumulation, and poorer cognition and motor functions. Conversely, patients with iPD showed increased fiber bundle size, likely because of WM reorganization. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Background: Impulse control behaviors (ICBs) in Parkinson's disease (PD) are thought to be caused by an overdose of dopaminergic therapy in the relatively spared ventral striatum, or by hypersensitivity of this region to dopamine. Alterations in brain networks are now also thought to contribute to the development of ICBs., Objective: To comprehensively assess white matter microstructures in PD patients with ICBs using advanced diffusion MRI and magnetization transfer saturation (MT-sat) imaging., Methods: This study included 19 PD patients with ICBs (PD-ICBs), 18 PD patients without ICBs (PD-nICBs), and 20 healthy controls (HCs). Indices of diffusion tensor imaging (DTI), diffusion kurtosis imaging, neurite orientation dispersion and density imaging, and MT-sat imaging were evaluated using tract-based spatial statistics (TBSS), regions of interest (ROIs), and tract-specific analysis (TSA)., Results: Compared with HCs, PD-nICBs had significant alterations in many major white matter tracts in most parameters. In contrast, PD-ICBs had only partial changes in several parameters. Compared with PD-ICBs, TBSS, ROI, and TSA analyses revealed that PD-nICBs had lower axial kurtosis, myelin volume fraction, and orientation dispersion index in the uncinate fasciculus and external capsule, as well as in the retrolenticular part of the internal capsule. These are components of the reward system and the visual and emotional perception areas, respectively., Interpretation: Myelin and axonal changes in fibers related to the reward system and visual emotional recognition might be more prominent in PD-nICBs than in PD-ICBs., (© 2022 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

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., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: To investigate whether Parkinson's disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)-based structural connectome matrices calculated from diffusion-weighted MRI., Methods: In this prospective study, 115 PD patients and 115 healthy controls were enrolled. NOS-based and parameter-weighted connectome matrices were calculated from MRI images obtained with a 3-T MRI unit. With 5-fold cross-validation, diagnostic performance of convolutional neural network (CNN) models using those connectome matrices in differentiating patients with PD from healthy controls was evaluated. To identify the important brain connections for diagnosing PD, gradient-weighted class activation mapping (Grad-CAM) was applied to the trained CNN models., Results: CNN models based on some parameter-weighted structural matrices (diffusion kurtosis imaging (DKI)-weighted, neurite orientation dispersion and density imaging (NODDI)-weighted, and g-ratio-weighted connectome matrices) showed moderate performance (areas under the receiver operating characteristic curve (AUCs) = 0.895, 0.801, and 0.836, respectively) in discriminating PD patients from healthy controls. The DKI-weighted connectome matrix performed significantly better than the conventional NOS-based matrix (AUC = 0.761) (DeLong's test, p < 0.0001). Alterations of neural connections between the basal ganglia and cerebellum were indicated by applying Grad-CAM to the NODDI- and g-ratio-weighted matrices., Conclusion: Patients with PD can be differentiated from healthy controls by applying the deep learning technique to the parameter-weighted connectome matrices, and neural circuit disorders including those between the basal ganglia on one side and the cerebellum on the contralateral side were visualized., (© 2021. The Author(s).)

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.

Neurocognitive and psychiatric disorders have significant consequences for quality of life in patients with Parkinson's disease (PD). In the current study, we evaluated microstructural white matter (WM) alterations associated with neurocognitive and psychiatric disorders in PD using neurite orientation dispersion and density imaging (NODDI) and linked independent component analysis (LICA). The indices of NODDI were compared between 20 and 19 patients with PD with and without neurocognitive and psychiatric disorders, respectively, and 25 healthy controls using tract-based spatial statistics and tract-of-interest analyses. LICA was applied to model inter-subject variability across measures. A widespread reduction in axonal density (indexed by intracellular volume fraction [ICVF]) was demonstrated in PD patients with and without neurocognitive and psychiatric disorders, as compared with healthy controls. Compared with patients without neurocognitive and psychiatric disorders, patients with neurocognitive and psychiatric disorders exhibited more extensive (posterior predominant) decreases in axonal density. Using LICA, ICVF demonstrated the highest contribution (59% weight) to the main effects of diagnosis that reflected widespread decreases in axonal density. These findings suggest that axonal loss is a major factor underlying WM pathology related to neurocognitive and psychiatric disorders in PD, whereas patients with neurocognitive and psychiatric disorders had broader axonal pathology, as compared with those without. LICA suggested that the ICVF can be used as a useful biomarker of microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD., (© 2020 The Authors. Journal of Neuroscience Research published by Wiley Periodicals, Inc.)

Purpose: Micro fractional anisotropy (μFA) is more accurate than conventional fractional anisotropy (FA) for assessing microscopic tissue properties and can overcome limitations related to crossing white matter fibres. We compared μFA and FA for evaluating white matter changes in patients with Parkinson's disease (PD)., Methods: We compared FA and μFA measures between 25 patients with PD and 25 age- and gender-matched healthy controls using tract-based spatial statistics (TBSS) analysis. We also examined potential correlations between changes, revealed by conventional FA or μFA, and disease duration or Unified Parkinson's Disease Rating Scale (UPDRS)-III scores., Results: Compared with healthy controls, patients with PD had significantly reduced μFA values, mainly in the anterior corona radiata (ACR). In the PD group, μFA values (primarily those from the ACR) were significantly negatively correlated with UPDRS-III motor scores. No significant changes or correlations with disease duration or UPDRS-III scores with tissue properties were detected using conventional FA., Conclusion: μFA can evaluate microstructural changes that occur during white matter degeneration in patients with PD and may overcome a key limitation of FA.

Purpose: This study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson's disease (PD) diagnosis., Methods: NM-MRI datasets from two different 3T-scanners were used: a "principal dataset" with 122 participants and an "external validation dataset" with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined., Results: For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets., Conclusion: U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method.

This study aimed to discriminate between neuroinflammation and neuronal degeneration in the white matter (WM) and gray matter (GM) of patients with Parkinson's disease (PD) using free-water (FW) imaging. Analysis using tract-based spatial statistics (TBSS) of 20 patients with PD and 20 healthy individuals revealed changes in FW imaging indices (i.e., reduced FW-corrected fractional anisotropy (FA T ), increased FW-corrected mean, axial, and radial diffusivities (MD T , AD T , and RD T , respectively) and fractional volume of FW (FW) in somewhat more specific WM areas compared with the changes of DTI indices. The region-of-interest (ROI) analysis further supported these findings, whereby those with PD showed significantly lower FA T and higher MD T , AD T , and RD T (indices of neuronal degeneration) in anterior WM areas as well as higher FW (index of neuroinflammation) in posterior WM areas compared with the controls. Results of GM-based spatial statistics (GBSS) analysis revealed that patients with PD had significantly higher MD T , AD T , and FW than the controls, whereas ROI analysis showed significantly increased MD T and FW and a trend toward increased AD T in GM areas, corresponding to Braak stage IV. These findings support the hypothesis that neuroinflammation precedes neuronal degeneration in PD, whereas WM microstructural alterations precede changes in GM., Competing Interests: The authors declare no conflicts of interest.

Introduction: Parkinson's disease (PD) is marked by the degeneration of dopaminergic neurons in the nigrostriatal pathway (NSP). We aimed to identify the microstructural changes in the NSP of PD patients using neurite orientation dispersion and density imaging (NODDI)., Methods: NSPs of 29 PD patients, who were retrospectively selected from patients previously admitted to our institution, and 29 age- and gender-matched healthy controls were isolated via deterministic tractography. The NODDI indices, intracellular volume fraction (Vic), orientation dispersion index (OD), and isotropic volume fraction (Viso) were compared between the two groups. The significant results were assessed with a tract-profile analysis. The correlation between indices and disease duration or motor symptom severity was evaluated with the Pearson's correlation test., Results: The contralateral distal Vic (p = 0.00028) of the nigrostriatal pathway was significantly lower in PD patients than in healthy controls. No correlations were detected between any of the indices and disease duration or motor symptom severity., Conclusions: NODDI can be used to identify retrograde degeneration of the NSP in PD patients and might be useful for monitoring the disease progression of PD., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)