川畑 和也

Abstract Objectives To investigate trajectories of regional brain volume changes in multiple system atrophy (MSA) and their potential utility as surrogate markers of disease progression in the cerebellar subtype (MSA‐C). Background Reliable biomarkers for tracking disease progression in MSA are urgently needed. Although several studies have explored neuroimaging markers, imaging measures that are reliable and reproducible at the individual‐level are lacking. Methods Longitudinal three‐dimensional (3D)‐T1 images from multiple cohorts of 21 subjects with probable MSA‐C, 19 with probable MSA‐parkinsonian subtype (MSA‐P), 113 with Parkinson's disease, and 227 healthy controls were processed using the FreeSurfer longitudinal pipeline. Extracted volumes were assessed for individual longitudinal trajectories, intra‐individual variability, and pontine regional volume decline. Results Pontine volumes showed lower intra‐individual variability in measurements compared with other infratentorial brain regions. All probable MSA‐C patients exhibited a decline in pontine volume, ranging from −3.6% to −16.8% per year (mean: −9.1%), falling more than two standard deviations below the mean of healthy controls. In MSA‐C, the temporal dynamics of pontine volumes exhibited nonlinear changes, characterized by progressive atrophy in the earlier period of the disease, followed by a pre‐plateau phase associated with advanced disability in the later period. Predictive modeling suggests that pontine atrophy may begin before symptom onset of MSA‐C. Conclusions Pontine volume is a sensitive marker of disease progression, exhibiting a nonlinear decline with low intra‐individual variability in measurements and greater volume loss in the earlier stages, reaching a pre‐plateau phase in the later stages with advanced disability. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

INTRODUCTION: Progressive supranuclear palsy (PSP) involves midbrain structures, including the red nucleus (RN), an iron-rich region that appears as a high-contrast area on quantitative susceptibility mapping (QSM). RN may serve as a promising biomarker for differentiating parkinsonism. However, RN deformation in PSP remains elusive. This study aimed to evaluate RN deformation in PSP using coronal QSM images and compare them with those of Parkinson's disease (PD) and healthy controls (HC). METHODS: We evaluated the QSM images of 22 patients with PSP, 37 patients with PD, and 43 HC. We developed a grading system to assess RN deformation on coronal QSM images and classified them into three grades. The midbrain and RN volumes were extracted using distinct approaches, and their relationship with grading was investigated. For validation, coronal QSM images of 16 PSP patients from a different institution were assessed. RESULTS: In PSP, 59 % of the patients displayed a flattened RN of grade 3, which we termed a Rice-Grain Appearance. The volume reductions in midbrain and RN were associated with deformation. Differentiation based on the presence of this appearance yielded a specificity of 1.000 (CI: 1.000-1.000) and sensitivity of 0.591 (0.385-0.796) for distinguishing PSP from others. Secondary dataset also showed that 56 % of patients with PSP were classified as grade 3. CONCLUSION: In coronal QSM images, the flattened RN shape appears to be specific to PSP compared to PD and HC and may serve as a marker to help differentiate PSP in future clinical settings.

INTRODUCTION: Olfactory dysfunction and REM sleep behavior disorder (RBD) are associated with distinct cognitive trajectories in the course of Parkinson's disease (PD). The underlying neurobiology for this relationship remains unclear but may involve distinct patterns of neurodegeneration. This study aimed to examine longitudinal cortical atrophy and thinning in early-stage PD with severe olfactory deficit (anosmia) without and with concurrent probable RBD. METHODS: Longitudinal MRI data over four years of 134 de novo PD and 49 healthy controls (HC) from the Parkinson Progression Marker Initiative (PPMI) cohort were analyzed using a linear mixed-effects model. Patients were categorized into those with anosmia by the University of Pennsylvania Smell Identification Test (UPSIT) score ≤ 18 (AO+) and those without (UPSIT score > 18, AO-). The AO+ group was further subdivided into AO+ with probable RBD (AO+RBD+) and without (AO+RBD-) for subanalysis. RESULTS: Compared to subjects without baseline anosmia, the AO+ group exhibited greater longitudinal declines in both volume and thickness in the bilateral parahippocampal gyri and right transverse temporal gyrus. Patients with concurrent anosmia and RBD showed more extensive longitudinal declines in cortical volume and thickness, involving additional brain regions including the bilateral precuneus, left inferior temporal gyrus, right paracentral gyrus, and right precentral gyrus. CONCLUSIONS: The atrophy/thinning patterns in early-stage PD with severe olfactory dysfunction include regions that are critical for cognitive function and could provide a structural basis for previously reported associations between severe olfactory deficit and cognitive decline in PD. Concurrent RBD might enhance the dynamics of cortical changes.

BACKGROUND: Advanced imaging techniques have been studied for differential diagnosis between PD, MSA, and PSP. OBJECTIVES: This study aims to validate the utility of individual voxel-based morphometry techniques for atypical parkinsonism in a blinded fashion. METHODS: Forty-eight healthy controls (HC) T1-WI were used to develop a referential dataset and fit a general linear model after segmentation into gray matter (GM) and white matter (WM) compartments. Segmented GM and WM with PD (n = 96), MSA (n = 18), and PSP (n = 20) were transformed into z-scores using the statistics of referential HC and individual voxel-based z-score maps were generated. An imaging diagnosis was assigned by two independent raters (trained and untrained) blinded to clinical information and final diagnosis. Furthermore, we developed an observer-independent index for ROI-based automated differentiation. RESULTS: The diagnostic performance using voxel-based z-score maps by rater 1 and rater 2 for MSA yielded sensitivities: 0.89, 0.94 (95% CI: 0.74-1.00, 0.84-1.00), specificities: 0.94, 0.80 (0.90-0.98, 0.73-0.87); for PSP, sensitivities: 0.85, 0.90 (0.69-1.00, 0.77-1.00), specificities: 0.98, 0.94 (0.96-1.00, 0.90-0.98). Interrater agreement was good for MSA (Cohen's kappa: 0.61), and excellent for PSP (0.84). Receiver operating characteristic analysis using the ROI-based new index showed an area under the curve (AUC): 0.89 (0.77-1.00) for MSA, and 0.99 (0.98-1.00) for PSP. CONCLUSIONS: These evaluations provide support for the utility of this imaging technique in the differential diagnosis of atypical parkinsonism demonstrating a remarkably high differentiation accuracy for PSP, suggesting potential use in clinical settings in the future.

INTRODUCTION: Parkinson's disease (PD) exhibits divergent cognitive trajectories; however, the factors contributing to these variations remain elusive. This study aimed to examine the clinical features of patients with different long-term cognitive trajectories in de novo PD over a five-year follow-up. METHODS: We analyzed 258 patients who completed every annual evaluation for five years. According to the Montreal Cognitive Assessment (MoCA) scores, we classified patients into three groups: cognitively normal (n = 118, CN), remitting MoCA decline (n = 74, RMD), and progressive MoCA decline (n = 66, PMD). RESULTS: The RMD group was associated with lower olfactory scores (Odds Ratio (OR) = 0.958, p = 0.040), whereas PMD was associated with higher depression scores (OR = 1.158, p = 0.045), probable RBD (OR = 3.169, p = 0.002), older age (OR = 1.132, p < 0.001) and lower educational attainment (OR = 0.828, p = 0.004). PMD had higher neurofilament light chain protein values than CN and RMD (p = 0.006, 0.015, respectively). Longitudinally, PMD showed a greater decline in all cognitive scores and hippocampus volumes (p = 0.004). Meanwhile, RMD exhibited intermediate cognitive and volumetric trajectories between CN and PMD and displayed worse score changes in memory tasks than CN. CONCLUSIONS: While PMD exhibited known risk factors for cognitive impairment, along with worse cognitive performance and hippocampal volume decline, RMD displayed baseline lower olfactory scores and intermediate cognitive and hippocampal volume decline between the two groups. These findings suggest individuals in RMD may still be at risk for cognitive deficits. However, further long-term follow-up data are needed to unravel the determinants and dynamics of cognitive functions.

Cognitive and movement processes involved integration of several large-scale brain networks. Central to these integrative processes are connector hubs, brain regions characterized by strong connections with multiple networks. Growing evidence suggests that many neurodegenerative and psychiatric disorders are associated with connector hub dysfunctions. Using a network metric called functional connectivity overlap ratio, we investigated connector hub alterations in Parkinson's disease. Resting-state functional MRI data from 99 patients (male/female = 44/55) and 99 age- and sex-matched healthy controls (male/female = 39/60) participating in our cross-sectional study were used in the analysis. We have identified two sets of connector hubs, mainly located in the sensorimotor cortex and cerebellum, with significant connectivity alterations with multiple resting-state networks. Sensorimotor connector hubs have impaired connections primarily with primary processing (sensorimotor, visual), visuospatial, and basal ganglia networks, whereas cerebellar connector hubs have impaired connections with basal ganglia and executive control networks. These connectivity alterations correlated with patients' motor symptoms. Specifically, values of the functional connectivity overlap ratio of the cerebellar connector hubs were associated with tremor score, whereas that of the sensorimotor connector hubs with postural instability and gait disturbance score, suggesting potential association of each set of connector hubs with the disorder's two predominant forms, the akinesia/rigidity and resting tremor subtypes. In addition, values of the functional connectivity overlap ratio of the sensorimotor connector hubs were highly predictive in classifying patients from controls with an accuracy of 75.76%. These findings suggest that, together with the basal ganglia, cerebellar and sensorimotor connector hubs are significantly involved in Parkinson's disease with their connectivity dysfunction potentially driving the clinical manifestations typically observed in this disorder.

Accumulating evidence from anatomical and neuroimaging studies suggests that the cerebellum is engaged in a variety of motor and cognitive tasks. Given its various functions, a key question is whether the cerebellum also plays an important role in the brain's integrative functions. Here, we hypothesize the existence of connector regions, also known as connector hubs, where multiple resting state networks converged in the cerebellum. To verify this, we employed a recently developed voxel-level network measure called functional connectivity overlap ratio (FCOR), which could be used to quantify the spatial extent of a region's connection to several large-scale cortical networks. Using resting state functional MRI data from 101 healthy participants, cerebellar FCOR maps were constructed and used to identify the locations of connector hubs in the cerebellum. Results showed that a number of cerebellar regions exhibited strong connectivity with multiple functional networks, verifying our hypothesis. These highly connected regions were located in the posterior cerebellum, especially in lobules VI, VII, and IX, and mainly connected to the core neurocognitive networks such as default mode and executive control networks. Regions associated with the sensorimotor network were also localized in lobule V, VI, and VIII, albeit in small clusters. These cerebellar connector hubs may play an essential role in the processing of information across the core neurocognitive networks.

BACKGROUND AND PURPOSE: To clarify the relationship between fiber-specific white matter changes in amyotrophic lateral sclerosis (ALS) and clinical signs of upper motor neuron (UMN) involvement, we performed a fixel-based analysis (FBA), a novel framework for diffusion-weighted imaging analysis. METHODS: We enrolled 96 participants, including 48 nonfamilial ALS patients and 48 age- and sex-matched healthy controls (HCs), in this study and conducted whole-brain FBA and voxel-based morphometry analysis. We compared the fiber density (FD), fiber morphology (fiber cross-section [FC]), and a combined index of FD and FC (FDC) between the ALS and HC groups. We performed a tract-of-interest analysis to extract FD values across the significant regions in the whole-brain analysis. Then, we evaluated the associations between FD values and clinical variables. RESULTS: The bilateral corticospinal tracts (CSTs) and the corpus callosum (CC) showed reduced FD and FDC in ALS patients compared with HCs (p < 0.05, familywise error-corrected), and the comparison of FCs revealed no region that was significantly different from another. Voxel-based morphometry showed cortical volume reduction in the regions, including the primary motor area. Clinical scores showed correlations with FD values in the CSTs (UMN score: rho = -0.530, p < 0.001; central motor conduction time [CMCT] in the upper limb: rho = -0.474, p = 0.008; disease duration: rho = -0.383, p = 0.007; ALS Functional Rating Scale-Revised: rho = 0.340, p = 0.018). In addition, patients whose CMCT was not calculated due to unevoked waves also showed FD reduction in the CSTs. CONCLUSIONS: Our findings suggest that FD values in the CST estimated via FBA can be potentially used in evaluating UMN impairments.

The thalamus is critical for the brain's integrative hub functions; however, the localization and characterization of the different thalamic hubs remain unclear. Using a voxel-level network measure called functional connectivity overlap ratio (FCOR), we examined the thalamus' association with large-scale resting-state networks (RSNs) to elucidate its connector hub roles. Connections to the core-neurocognitive networks were localized in the anterior and medial parts, such as the anteroventral and mediodorsal nuclei areas. Regions functionally connected to the sensorimotor network were distinctively located around the lateral pulvinar nucleus but to a limited extent. Prominent connector hubs include the anteroventral, ventral lateral, and mediodorsal nuclei with functional connections to multiple RSNs. These findings suggest that the thalamus, with extensive connections to most of the RSNs, is well placed as a critical integrative functional hub and could play an important role for functional integration facilitating brain functions associated with primary processing and higher cognition.

Introduction: Parkinson's disease (PD) shows a variety of visual deficits including visuoperceptual disturbances, however, the neural basis remains unclear. We aimed to clarify clinical and neural features of visuoperceptual disturbances in PD. Methods: The visuospatial/perceptual abilities of ninety-six participants (48 patients with PD and 48 healthy controls) were evaluated using the subtest part 1 and 5-8 of the Visual Object and Space Perception battery (VOSP), cube/pentagon copying and clock drawing tasks. Resting-state fMRI images were acquired and analyzed the differences between PD with incomplete letters below the cut-off and above for intranetwork (primary/medial/higher visual networks) and interregional functional connectivity changes, and spectral dynamic causal modeling was performed to examine the causality. Results: In the PD group, position discrimination and incomplete letter scores were significantly decreased among VOSP subtests, the latter having the largest effect size. The incomplete letter scores correlated with the position discrimination while not with the dot counting, number location and cube analysis, cube/pentagon copying or clock drawing. The group with the incomplete letter scores below the cut-off had regions with decreased functional connectivity surrounding the calcarine sulcus in the primary visual network. These regions had decreased interregional functional connectivity with bilateral lingual gyri and cunei but increased with the thalamus. In this group, effective connectivity from the lingual gyrus to the calcarine sulcus was significantly decreased. Conclusion: The incomplete letters may be sensitive to detect visuoperceptual disturbances in PD. Decreased connectivity in the ventral visual feedback pathway may contribute to these deficits.

Cognitive deficits in Parkinson's disease (PD) are heterogeneous entities, but a relationship between the heterogeneity of cognitive deficits and resting-state network (RSN) changes remains elusive. In this study, we examined five sub-domain scores according to Addenbrooke's Cognitive Examination-Revised (ACE-R) for the cognitive evaluation and classification of 72 non-demented patients with PD. Twenty-eight patients were classified as PD with normal cognition (PD-NC). The remaining 44 were subdivided into the following 2 groups using a hierarchical cluster analysis: 20 with a predominant decrease in memory (PD with amnestic cognitive deficits: PD-A) and 24 with good memory who exhibited a decrease in other sub-domains (PD with non-amnestic cognitive deficits: PD-NA). We used an independent component analysis of RS-fMRI data to investigate the inter-group differences of RSN. Compared to the controls, the PD-A showed lower FC within the ventral default mode network (vDMN) and the visuospatial network. On the other hand, the PD-NA showed lower FC within the visual networks and the cerebellum-brainstem network. Significant differences in the FC within the vDMN and cerebellum-brainstem network were observed between the PD-A and PD-NA, which provided a good discrimination between PD-A and PD-NA using a support vector machine. Distinct patterns of cognitive deficits correspond to different RSN changes.