Brain structure comparison among Parkinson disease, essential tremor, and healthy controls using 7T MRI.

Both Parkinson disease (PD) and Essential tremor (ET) are movement disorders causing tremors in elderly individuals. Although PD and ET are different disease, they often present with similar initial symptoms, making their differentiation challenging with magnetic resonance imaging (MRI) techniques. This study aimed to identify structural brain differences among PD, ET, and health controls (HCs) using 7-Tesla (T) MRI. We assessed the whole-brain parcellation in gray matter volume, thickness, subcortical volume, and small regions of basal ganglia in PD (n = 18), ET (n = 15), and HCs (n = 18), who were matched for age and sex. Brain structure analysis was performed automatic segmentation through Freesurfer software. Small regions of basal ganglia were manually segmented by ITK-SNAP. Additionally, we examined the associations between clinical indicators (symptom duration, unified Parkinson diseases rating scale (UPDRS), and clinical rating scale for tremor (CRST)) and brain structure. PD showed a significant reduction in gray matter volume in the postcentral region compared to ET. ET showed a significant reduction in cerebellum volume compared to HCs. There was a negative correlation between CRST scores (B and C) and gray matter thickness in right superior frontal in ET. This study demonstrated potential of 7T MRI in differentiating brain structure differences among PD, ET, and HCs. Specific findings, such as parietal lobe atrophy in PD compared to ET and cerebellum atrophy in ET compared to HCs, the importance of advanced imaging techniques in accurately diagnosing and distinguishing between movement disorders that present with similar initial symptoms.

Study protocol of the GRoningen early-PD Ambroxol treatment (GREAT) trial: a randomized, double-blind, placebo-controlled, single center trial with ambroxol in Parkinson patients with a GBA mutation.

BACKGROUND: To date, no disease modifying therapies are available for Parkinson's disease (PD). Since PD is the second most prevalent neurodegenerative disorder, there is a high demand for such therapies. Both environmental and genetic risk factors play an important role in the etiology and progression of PD. The most common genetic risk factor for PD is a mutation in the GBA1(GBA)-gene, encoding the lysosomal enzyme glucocerebrosidase (GCase). The mucolytic ambroxol is a repurposed drug, which has shown the property to upregulate GCase activity in-vitro and in-vivo. Ambroxol therefore has the potency to become a disease modifying therapy in PD, which was the reason to design this randomized controlled trial with ambroxol in PD patients. METHODS: This trial is a single-center, double-blind, randomized, placebo-controlled study, including 80 PD patients with a GBA mutation, receiving either ambroxol 1800 mg/day or placebo for 48 weeks. The primary outcome measure is the Unified Parkinson's Disease Rating Scale motor subscore (part III) of the Movement Disorder Society (MDS-UPDRSIII) in the practically defined off-state at 60 weeks (after a 12-week washout period). Secondary outcomes include a 3,4-dihydroxy-6-18F-fluoro-I-phenylalanine ([18F]FDOPA) PET-scan of the brain, Magnetic Resonance Imaging (with resting state f-MRI and Diffusion Tensor Imaging), GCase activity, both intra- and extracellularly, sphingolipid profiles in plasma, Montreal Cognitive Assessment (MoCA), quality of life (QoL) measured by the Parkinson's Disease Questionnaire (PDQ-39) and the Non-Motor Symptom Scale (NMSS) questionnaire. DISCUSSION: Ambroxol up to 1200 mg/day has shown effects on human cerebrospinal fluid endpoints, which supports at least passage of the blood-brain-barrier. The dose titration in this trial up to 1800 mg/day will reveal if this dose level is safe and also effective in modifying the course of the disease. TRIAL REGISTRATION: NCT05830396. Registration date: March 20, 2023.

Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor.

Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.

The influence of accelerated brain aging on coactivation pattern dynamics in Parkinson's disease.

Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.

Parkinson's Disease Recognition Using Decorrelated Convolutional Neural Networks: Addressing Imbalance and Scanner Bias in rs-fMRI Data.

Parkinson's disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells in the brain and varies from person to person. The exact cause of PD is still unknown, and the diagnosis of PD does not include a specific objective test with certainty. Although deep learning has made great progress in medical neuroimaging analysis, these methods are very susceptible to biases present in neuroimaging datasets. An innovative decorrelated deep learning technique is introduced to mitigate class bias and scanner bias while simultaneously focusing on finding distinguishing characteristics in resting-state functional MRI (rs-fMRI) data, which assists in recognizing PD with good accuracy. The decorrelation function reduces the nonlinear correlation between features and bias in order to learn bias-invariant features. The publicly available Parkinson's Progression Markers Initiative (PPMI) dataset, referred to as a single-scanner imbalanced dataset in this study, was used to validate our method. The imbalanced dataset problem affects the performance of the deep learning framework by overfitting to the majority class. To resolve this problem, we propose a new decorrelated convolutional neural network (DcCNN) framework by applying decorrelation-based optimization to convolutional neural networks (CNNs). An analysis of evaluation metrics comparisons shows that integrating the decorrelation function boosts the performance of PD recognition by removing class bias. Specifically, our DcCNN models perform significantly better than existing traditional approaches to tackle the imbalance problem. Finally, the same framework can be extended to create scanner-invariant features without significantly impacting the performance of a model. The obtained dataset is a multiscanner dataset, which leads to scanner bias due to the differences in acquisition protocols and scanners. The multiscanner dataset is a combination of two publicly available datasets, namely, PPMI and FTLDNI-the frontotemporal lobar degeneration neuroimaging initiative (NIFD) dataset. The results of t-distributed stochastic neighbor embedding (t-SNE) and scanner classification accuracy of our proposed feature extraction-DcCNN (FE-DcCNN) model validated the effective removal of scanner bias. Our method achieves an average accuracy of 77.80% on a multiscanner dataset for differentiating PD from a healthy control, which is superior to the DcCNN model trained on a single-scanner imbalanced dataset.

Neuropathologic Validation and Diagnostic Accuracy of Presynaptic Dopaminergic Imaging in the Diagnosis of Parkinsonism.

BACKGROUND AND OBJECTIVES: Degeneration of the presynaptic nigrostriatal dopaminergic system is one of the main biological features of Parkinson disease (PD), multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD), which can be measured using single-photon emission CT imaging for diagnostic purposes. Despite its widespread use in clinical practice and research, the diagnostic properties of presynaptic nigrostriatal dopaminergic (DAT) imaging in parkinsonism have never been evaluated against the diagnostic gold standard of neuropathology. The aim of this study was to evaluate the diagnostic parameters of DAT imaging compared with pathologic diagnosis in patients with parkinsonism. METHODS: Retrospective cohort study of patients with DAT imaging for the investigation of a clinically uncertain parkinsonism with brain donation between 2010 and 2021 to the Queen Square Brain Bank (London). Patients with DAT imaging for investigation of pure ataxia or dementia syndromes without parkinsonism were excluded. Those with a pathologic diagnosis of PD, MSA, PSP, or CBD were considered presynaptic dopaminergic parkinsonism, and other pathologies were considered postsynaptic for the analysis. DAT imaging was performed in routine clinical practice and visually classified by hospital nuclear medicine specialists as normal or abnormal. The results were correlated with neuropathologic diagnosis to calculate diagnostic accuracy parameters for the diagnosis of presynaptic dopaminergic parkinsonism. RESULTS: All of 47 patients with PD, 41 of 42 with MSA, 68 of 73 with PSP, and 6 of 10 with CBD (sensitivity 100%, 97.6%, 93.2%, and 60%, respectively) had abnormal presynaptic dopaminergic imaging. Eight of 17 patients with presumed postsynaptic parkinsonism had abnormal scans (specificity 52.9%). DISCUSSION: DAT imaging has very high sensitivity and negative predictive value for the diagnosis of presynaptic dopaminergic parkinsonism, particularly for PD. However, patients with CBD, and to a lesser extent PSP (of various phenotypes) and MSA (with predominant ataxia), can show normal DAT imaging. A range of other neurodegenerative disorders may have abnormal DAT scans with low specificity in the differential diagnosis of parkinsonism. DAT imaging is a useful diagnostic tool in the differential diagnosis of parkinsonism, although clinicians should be aware of its diagnostic properties and limitations. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that DAT imaging does not accurately distinguish between presynaptic dopaminergic parkinsonism and non-presynaptic dopaminergic parkinsonism.

Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease.

PURPOSE: To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). METHODS: In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis. RESULTS: Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively. CONCLUSION: The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Regional nigral neuromelanin degeneration in asymptomatic leucine-rich repeat kinase 2 gene carrier using MRI.

Asymptomatic Leucine-Rich Repeat Kinase 2 Gene (LRRK2) carriers are at risk for developing Parkinson's disease (PD). We studied presymptomatic substantia nigra pars compacta (SNc) regional neurodegeneration in asymptomatic LRRK2 carriers compared to idiopathic PD patients using neuromelanin-sensitive MRI technique (NM-MRI). Fifteen asymptomatic LRRK2 carriers, 22 idiopathic PD patients, and 30 healthy controls (HCs) were scanned using NM-MRI. We computed volume and contrast-to-noise ratio (CNR) derived from the whole SNc and the sensorimotor, associative, and limbic SNc regions. An analysis of covariance was performed to explore the differences of whole and regional NM-MRI values among the groups while controlling the effect of age and sex. In whole SNc, LRRK2 had significantly lower CNR than HCs but non-significantly higher volume and CNR than PD patients, and PD patients significantly lower volume and CNR compared to HCs. Inside SNc regions, there were significant group effects for CNR in all regions and for volumes in the associative region, with a trend in the sensorimotor region but no significant changes in the limbic region. PD had reduced volume and CNR in all regions compared to HCs. Asymptomatic LRRK2 carriers showed globally decreased SNc volume and CNR suggesting early nigral neurodegeneration in these subjects at risk of developing PD.

Increased prevalence of vertebrobasilar dolichoectasia in Parkinson's disease and its effect on white matter microstructure and network.

This study aimed to investigate the prevalence of vertebrobasilar dolichoectasia (VBD) in Parkinson's disease (PD) patients and analyze its role in gray matter changes, white matter (WM) microstructure and network alterations in PD. This is a cross-sectional study including 341 PD patients. Prevalence of VBD in these PD patients was compared with general population. Diffusion tensor imaging and T1-weighted imaging analysis were performed among 174 PD patients with or without VBD. Voxel-based morphometry analysis was used to estimate gray matter volume changes. Tract-based spatial statistics and region of interest-based analysis were used to evaluate WM microstructure changes. WM network analysis was also performed. Significantly higher prevalence of VBD in PD patients was identified compared with general population. Lower fractional anisotropy and higher diffusivity, without significant gray matter involvement, were found in PD patients with VBD in widespread areas. Decreased global and local efficiency, increased hierarchy, decreased degree centrality at left Rolandic operculum, increased betweenness centrality at left postcentral gyrus and decreased average connectivity strength between and within several modules were identified in PD patients with VBD. VBD is more prevalent in PD patients than general population. Widespread impairments in WM microstructure and WM network involving various motor and nonmotor PD symptom-related areas are more prominent in PD patients with VBD compared with PD patients without VBD.

Reduced cerebrospinal fluid motion in patients with Parkinson's disease revealed by magnetic resonance imaging with low b-value diffusion weighted imaging.

BACKGROUND: Parkinson's disease is characterized by dopamine-responsive symptoms as well as aggregation of α-synuclein protofibrils. New diagnostic methods assess α-synuclein aggregation characteristics from cerebrospinal fluid (CSF) and recent pathophysiologic mechanisms suggest that CSF circulation disruptions may precipitate α-synuclein retention. Here, diffusion-weighted MRI with low-to-intermediate diffusion-weightings was applied to test the hypothesis that CSF motion is reduced in Parkinson's disease relative to healthy participants. METHODS: Multi-shell diffusion weighted MRI (spatial resolution = 1.8 × 1.8 × 4.0 mm) with low-to-intermediate diffusion weightings (b-values = 0, 50, 100, 200, 300, 700, and 1000 s/mm2) was applied over the approximate kinetic range of suprasellar cistern fluid motion at 3 Tesla in Parkinson's disease (n = 27; age = 66 ± 6.7 years) and non-Parkinson's control (n = 32; age = 68 ± 8.9 years) participants. Wilcoxon rank-sum tests were applied to test the primary hypothesis that the noise floor-corrected decay rate of CSF signal as a function of b-value, which reflects increasing fluid motion, is reduced within the suprasellar cistern of persons with versus without Parkinson's disease and inversely relates to choroid plexus activity assessed from perfusion-weighted MRI (significance-criteria: p < 0.05). RESULTS: Consistent with the primary hypothesis, CSF decay rates were higher in healthy (D = 0.00673 ± 0.00213 mm2/s) relative to Parkinson's disease (D = 0.00517 ± 0.00110 mm2/s) participants. This finding was preserved after controlling for age and sex and was observed in the posterior region of the suprasellar cistern (p < 0.001). An inverse correlation between choroid plexus perfusion and decay rate in the voxels within the suprasellar cistern (Spearman's-r=-0.312; p = 0.019) was observed. CONCLUSIONS: Multi-shell diffusion MRI was applied to identify reduced CSF motion at the level of the suprasellar cistern in adults with versus without Parkinson's disease; the strengths and limitations of this methodology are discussed in the context of the growing literature on CSF flow.

Real-Time Monitoring of Tyrosine Hydroxylase Activity with a Ratiometric Fluorescent Probe.

Parkinson's disease (PD) represents the second most widespread neurodegenerative disease, and early monitoring and diagnosis are urgent at present. Tyrosine hydroxylase (TH) is a key enzyme for producing dopamine, the levels of which can serve as an indicator for assessing the severity and progression of PD. This renders the specific detection and visualization of TH a strategically vital way to meet the above demands. However, a fluorescent probe for TH monitoring is still missing. Herein, three rationally designed wash-free ratiometric fluorescent probes were proposed. Among them, TH-1 exhibited ideal photophysical properties and specific dual-channel bioimaging of TH activity in SH-SY5Y nerve cells. Moreover, the probe allowed for in vivo imaging of TH activity in zebrafish brain and living striatal slices of mice. Overall, the ratiometric fluorescent probe TH-1 could serve as a potential tool for real-time monitoring of PD in complex biosystems.

Longitudinal study investigating the influence of COMT gene polymorphism on cortical thickness changes in Parkinson's disease over four years.

Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting over 3% of those over 65. It's caused by reduced dopaminergic neurons and Lewy bodies, leading to motor and non-motor symptoms. The relationship between COMT gene polymorphisms and PD is complex and not fully elucidated. Some studies have reported associations between certain COMT gene variants and PD risk, while others have not found significant associations. This study investigates how COMT gene variations impact cortical thickness changes in PD patients over time, aiming to link genetic factors, especially COMT gene variations, with PD progression. This study analyzed data from 44 PD patients with complete 4-year imaging follow-up from the Parkinson Progression Marker Initiative (PPMI) database. Magnetic resonance imaging (MRI) scans were acquired using consistent methods across 9 different MRI scanners. COMT single-nucleotide polymorphisms (SNPs) were assessed based on whole genome sequencing data. Longitudinal image analysis was conducted using FreeSurfer's processing pipeline. Linear mixed-effect models were employed to examine the interaction effect of genetic variations and time on cortical thickness, while controlling for covariates and subject-specific variations. The rs165599 SNP stands out as a potential contributor to alterations in cortical thickness, showing a significant reduction in overall mean cortical thickness in both hemispheres in homozygotes (Left: P = 0.023, Right: P = 0.028). The supramarginal, precentral, and superior frontal regions demonstrated significant bilateral alterations linked to rs165599. Our findings suggest that the rs165599 variant leads to earlier manifestation of cortical thinning during the course of the disease. However, it does not result in more severe cortical thinning outcomes over time. There is a need for larger cohorts and control groups to validate these findings and consider genetic variant interactions and clinical features to elucidate the specific mechanisms underlying COMT-related neurodegenerative processes in PD.

Hypothalamic involvement in multiple system atrophy: A structural MRI study.

OBJECTIVE: To investigate hypothalamic atrophy and its clinical correlates in multiple system atrophy (MSA) in-vivo. BACKGROUND: MSA is characterized by autonomic dysfunction and parkinsonian/cerebellar manifestations. The hypothalamus regulates autonomic and homeostatic functions and is also involved in memory and learning processes. METHODS: 11 MSA, 18 Parkinson's Disease (PD) and 18 Healthy Controls (HC) were included in this study. A validated and automated hypothalamic segmentation tool was applied to 3D-T1-weighted images acquired on a 3T MRI scanner. MSA hypothalamic volumes were compared to those of PD and HC. Furthermore, the association between hypothalamic volumes and scores of autonomic, depressive, sleep and cognitive manifestations were investigated. RESULTS: Posterior hypothalamus volume was reduced in MSA compared to controls (t = 2.105, p = 0.041) and PD (t = 2.055, p = 0.046). Total hypothalamus showed a trend towards a reduction in MSA vs controls (t = 1.676, p = 0.101). Reduced posterior hypothalamus volume correlated with worse MoCA scores in the parkinsonian (MSA + PD) group and in each group separately, but not with autonomic, sleep, or depression scores. CONCLUSIONS: In-vivo structural hypothalamic involvement may be present in MSA. Reduced posterior hypothalamus volume, which includes the mammillary bodies and lateral hypothalamus, is associated with worse cognitive functioning. Larger studies on hypothalamic involvement in MSA and its clinical correlates are needed.

Hypoperfusion in Alzheimer's Disease-Prone Regions and Dementia Conversion in Parkinson's Disease.

PURPOSE OF THE REPORT: Although early detection of individuals at risk of dementia conversion is important in patients with Parkinson's disease (PD), there is still no consensus on neuroimaging biomarkers for predicting future cognitive decline. We aimed to investigate whether cerebral perfusion patterns on early-phase 18 F-N-(3-fluoropropyl)-2ß-carboxymethoxy-3ß-(4-iodophenyl) nortropane ( 18 F-FP-CIT) PET have the potential to serve as a neuroimaging predictor for early dementia conversion in patients with PD. MATERIALS AND METHODS: In this retrospective analysis, we enrolled 187 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET at initial assessment and serial cognitive assessments during the follow-up period (>5 years). Patients with PD were classified into 2 groups: the PD with dementia (PDD)-high-risk (PDD-H; n = 47) and the PDD-low-risk (PDD-L; n = 140) groups according to dementia conversion within 5 years of PD diagnosis. We explored between-group differences in the regional uptake in the early-phase 18 F-FP-CIT PET images. We additionally performed a linear discriminant analysis to develop a prediction model for early PDD conversion. RESULTS: The PDD-H group exhibited hypoperfusion in Alzheimer's disease (AD)-prone regions (inferomedial temporal and posterior cingulate cortices, and insula) compared with the PDD-L group. A prediction model using regional uptake in the right entorhinal cortex, left amygdala, and left isthmus cingulate cortex could optimally distinguish the PDD-H group from the PDD-L group. CONCLUSIONS: Regional hypoperfusion in the AD-prone regions on early-phase 18 F-FP-CIT PET can be a useful biomarker for predicting early dementia conversion in patients with PD.

Is white matter hyperintensity burden associated with cognitive and motor impairment in patients with parkinson's disease? A systematic review and meta-analysis.

White matter damage quantified as white matter hyperintensities (WMH) may aggravate cognitive and motor impairments, but whether and how WMH burden impacts these problems in Parkinson's disease (PD) is not fully understood. This study aimed to examine the association between WMH and cognitive and motor performance in PD through a systematic review and meta-analysis. We compared the WMH burden across the cognitive spectrum (cognitively normal, mild cognitive impairment, dementia) in PD including controls. Motor signs were compared in PD with low/negative and high/positive WMH burden. We compared baseline WMH burden of PD who did and did not convert to MCI or dementia. MEDLINE and EMBASE databases were used to conduct the literature search resulting in 50 studies included for data extraction. Increased WMH burden was found in individuals with PD compared with individuals without PD (i.e. control) and across the cognitive spectrum in PD (i.e. PD, PD-MCI, PDD). Individuals with PD with high/positive WMH burden had worse global cognition, executive function, and attention. Similarly, PD with high/positive WMH presented worse motor signs compared with individuals presenting low/negative WMH burden. Only three longitudinal studies were retrieved from our search and they showed that PD who converted to MCI or dementia, did not have significantly higher WMH burden at baseline, although no data was provided on WMH burden changes during the follow up. We conclude, based on cross-sectional studies, that WMH burden appears to increase with PD worse cognitive and motor status in PD.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

OBJECTIVE: This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). METHODS: Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. RESULTS: A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. CONCLUSION: The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

Hippocampal resting-state connectivity is associated with posterior-cortical cognitive impairment in Parkinson's disease.

AIM: Frontal and posterior-cortical cognitive subtypes in Parkinson's disease (PD) present with executive/attention and memory/visuospatial deficits, respectively. As the posterior-cortical subtype is predicted to progress rapidly toward dementia, the present study aimed to explore biological markers of this group using resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: K-means cluster analysis delineated subtypes (cognitively intact, frontal, posterior-cortical, and globally impaired) among 85 people with PD. A subset of PD participants (N = 42) and 20 healthy controls (HCs) underwent rs-fMRI. Connectivity of bilateral hippocampi with regions of interest was compared between posterior-cortical, cognitively intact, and HC participants using seed-based analysis, controlling for age. Exploratory correlations were performed between areas of interest from the group analysis and a series of cognitive tests. RESULTS: The posterior-cortical subtype (N = 19) showed weaker connectivity between the left hippocampus and right anterior temporal fusiform cortex compared to the cognitively intact (N = 11) group, p-false discovery rate (FDR) = .01, and weaker connectivity between bilateral hippocampi and most fusiform regions compared to HCs (N = 20). No differences were found between HCs and cognitively intact PD. Exploratory analyses revealed strongest associations between connectivity of the right anterior temporal fusiform cortex and left hippocampus with category fluency (p-FDR = .01). CONCLUSION: Results suggest that weakened connectivity between the hippocampus and fusiform region is a unique characteristic of posterior-cortical cognitive deficits in PD. Further exploration of hippocampal and fusiform functional integrity as a marker of cognitive decline in PD is warranted.

Free-Water Imaging of the Nucleus Basalis of Meynert in Patients With Idiopathic REM Sleep Behavior Disorder and Parkinson Disease.

BACKGROUND AND OBJECTIVES: Cognitive impairments are common in idiopathic REM sleep behavior disorder (iRBD), in which the cholinergic degeneration of nucleus basalis of Meynert (NBM) may play an important role. However, the progressive changes of NBM, the relationship between progressive NBM degeneration and progression of cognitive impairments, and whether degeneration of the NBM can predict cognitive decline in patients with iRBD remain unclear. This study aimed to investigate the cross-sectional and longitudinal microstructural alterations in the NBM of patients with iRBD using free-water imaging and whether free water in the NBM is related to cognitive, mood, and autonomic function. METHODS: We compared the baseline free-water values in the NBM between 59 healthy controls (HCs), 57 patients with iRBD, 57 patients with Parkinson disease (PD) with normal cognition (PD-NC), and 64 patients with PD with cognitive impairment (PD-CI). Thirty patients with iRBD and 40 HCs had one longitudinal data. In patients with iRBD, we explored the associations between baseline and longitudinal changes of free-water values in the NBM and clinical characteristics and whether baseline free-water values in the NBM could predict cognitive decline. RESULTS: IRBD, PD-NC, and PD-CI groups had significantly increased free-water values in the NBM compared with HCs, whereas PD-CI had higher free-water values compared with iRBD and PD-NC. In patients with iRBD, free-water values in the NBM were progressively elevated over follow-up and correlated with the progression of cognitive impairment and depression. Free-water values in the NBM could predict cognitive decline in the iRBD group. Furthermore, we found that patients with iRBD with cognitive impairment had higher relative change of free-water value in the NBM compared with patients with iRBD with normal cognition over follow-up. DISCUSSION: This study proves that free-water values in the NBM are elevated cross-sectionally and longitudinally and are associated with the progression of cognitive impairment and depression in patients with iRBD. Moreover, the free-water value in the NBM can predict cognitive decline in patients with iRBD. Whether free-water imaging of the NBM has the potential to be a marker for monitoring progressive cognitive impairment and predicting the conversion to dementia in synucleinopathies needs further investigation.

Differential connectivity of the posterior piriform cortex in Parkinson's disease and postviral olfactory dysfunction: an fMRI study.

Olfactory dysfunction is a common feature of both postviral upper respiratory tract infections (PV) and idiopathic Parkinson's disease (PD). Our aim was to investigate potential differences in the connectivity of the posterior piriform cortex, a major component of the olfactory cortex, between PV and PD patients. Fifteen healthy controls (median age 66 years, 9 men), 15 PV (median age 63 years, 7 men) and 14 PD patients (median age 70 years, 9 men) were examined with task-based olfactory fMRI, including two odors: peach and fish. fMRI data were analyzed with the co-activation pattern (CAP) toolbox, which allows a dynamic temporal assessment of posterior piriform cortex (PPC) connectivity. CAP analysis revealed 2 distinct brain networks interacting with the PPC. The first network included regions related to emotion recognition and attention, such as the anterior cingulate and the middle frontal gyri. The occurrences of this network were significantly fewer in PD patients compared to healthy controls (p = 0.023), with no significant differences among PV patients and the other groups. The second network revealed a dissociation between the olfactory cortex (piriform and entorhinal cortices), the anterior cingulate gyrus and the middle frontal gyri. This second network was significantly more active during the latter part of the stimulation, across all groups, possibly due to habituation. Our study shows how the PPC interacts with areas that regulate higher order processing and how this network is substantially affected in PD. Our findings also suggest that olfactory habituation is independent of disease.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease.

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.