Longitudinal White Matter Damage Evolution in Parkinson's Disease

White matter lesions contribute to motor and non-motor disorders in Parkinson's disease: a critical review

Parkinson's disease (PD) is a prevalent neurodegenerative disease, characterized by movement disorders and non-motor symptoms like cognitive impairment and depression. Degeneration of dopaminergic neurons in the substantia nigra and Lewy bodies have long been considered as main neuropathological changes. However, recent magnetic resonance imaging (MRI) studies have shown that white matter lesions (WMLs) were present in PD patients. WMLs are characterized by loss or impairment of myelin sheath in central nerve fibers, which are closely correlated with motor and cognitive dysfunction in PD. WMLs alterations precede nigrostriatal neuronal losses and can independently affect the clinical severity or characteristics of motor coordination in PD patients. Currently, the exact mechanism of WMLs involvement in the occurrence and development of PD remains unclear. It is speculated that WMLs may participate in the pathogenesis of PD by disrupting important connections in brain or promoting axonal degeneration. In this review, we will discuss the pathological changes and mechanisms of WMLs, elaborate the impact of WMLs on the progression of PD, clarify the importance of WMLs in PD pathogenesis, and thus provide novel targets for PD treatments.

Executive dysfunction in Parkinson's disease: From neurochemistry to circuits, genetics and neuroimaging

Cognitive decline is one of the most significant non-motor symptoms of Parkinson's disease (PD), with executive dysfunction (EDF) being the most prominent characteristic of PD-associated cognitive deficits. Currently, lack of uniformity in the conceptualization and assessment scales for executive functions impedes the early and accurate diagnosis of EDF in PD. The neurobiological mechanisms of EDF in PD remain poorly understood. Moreover, the treatment of cognitive impairment in PD has progressed slowly and with limited efficacy. Thus, this review explores the characteristics and potential mechanisms of EDF in PD from multiple perspectives, including the concept of executive function, commonly used neuropsychological tests, neurobiochemistry, genetics, electroencephalographic activity and neuroimaging. The available evidence indicates that degeneration of the frontal-striatal circuit, along with mutations in the Catechol-O-methyltransferase (COMT) gene and Leucine-rich repeat kinase 2 (LRRK2) gene, may contribute to EDF in patients with PD. The increase in theta and delta waves, along with the decrease in alpha waves, offers potential biomarkers for the early identification and monitoring of EDF, as well as the development of dementia in patients with PD. The PD cognition-related pattern (PDCP) pattern may serve as a tool for monitoring and assessing cognitive function progression in these patients and is anticipated to become a biomarker for cognitive disorders associated with PD. The aim is to provide new insights for the early and precise diagnosis and treatment of EDF in PD.

Brain white matter damage biomarkers

White matter (WM), constituting nearly half of the human brain's mass, is pivotal for the rapid transmission of neural signals across different brain regions, significantly influencing cognitive processes like learning, memory, and problem-solving. The integrity of WM is essential for brain function, and its damage, which can occur due to conditions such as multiple sclerosis (MS), stroke, and traumatic brain injury, results in severe neurological deficits and cognitive decline. The primary objective of this book chapter is to discuss the clinical significance of fluid biomarkers in assessing WM damage within the central nervous system (CNS). It explores the biological underpinnings and pathological changes in WM due to various neurological conditions and details how alterations can be detected and quantified through fluid biomarkers. By examining biomarkers like Myelin Basic Protein (MBP), Neurofilament light chain (NFL), and others, the chapter highlights their role in enhancing diagnostic precision, monitoring disease progression, and guiding therapeutic interventions, thus providing crucial insights into maintaining WM integrity and preventing cognitive and physical disabilities.

Glymphatic function from diffusion-tensor MRI to predict conversion from mild cognitive impairment to dementia in Parkinson's disease

BACKGROUND

Although brain glymphatic dysfunction is a contributing factor to the cognitive deficits in Parkinson's disease (PD), its role in the longitudinal progression of cognitive dysfunction remains unknown.

OBJECTIVE

To investigate the glymphatic function in PD with mild cognitive impairment (MCI) that progresses to dementia (PDD) and to determine its predictive value in identifying individuals at high risk for developing dementia.

METHODS

We included 64 patients with PD meeting criteria for MCI and categorized them as either progressed to PDD (converters) (n = 29) or did not progress to PDD (nonconverters) (n = 35), depending on whether they developed dementia during follow-up. Meanwhile, 35 age- and gender-matched healthy controls (HC) were included. Bilateral diffusion-tensor imaging analysis along the perivascular space (DTI-ALPS) indices and enlarged perivascular spaces (EPVS) volume fraction in bilateral centrum semiovale, basal ganglia (BG), and midbrain were compared among the three groups. Correlations among the DTI-ALPS index and EPVS, as well as cognitive performance were analyzed. Additionally, we investigated the mediation effect of EPVS on DTI-ALPS and cognitive function.

RESULTS

PDD converters had lower cognitive composites scores in the executive domains than did nonconverters (P < 0.001). Besides, PDD converters had a significantly lower DTI-ALPS index in the left hemisphere (P < 0.001) and a larger volume fraction of BG-PVS (P = 0.03) compared to HC and PDD nonconverters. Lower DTI-ALPS index and increased BG-PVS volume fraction were associated with worse performance in the global cognitive performance and executive function. However, there was no significant mediating effect. Receiver operating characteristic analysis revealed that the DTI-ALPS could effectively identify PDD converters with an area under the curve (AUC) of 0.850.

CONCLUSION

The reduction of glymphatic activity, measured by the DTI-ALPS, could potentially be used as a non-invasive indicator in forecasting high risk of dementia conversion before the onset of dementia in PD patients.

Emerging insights into Lipocalin-2: Unraveling its role in Parkinson's Disease

Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, marked by a complex pathogenesis. Lipocalin-2 (LCN2) emerges as a crucial factor during the progression of PD. Belonging to the lipocalin family, LCN2 is integral to several biological functions, including glial cell activation, iron homeostasis regulation, immune response, inflammatory reactions, and oxidative stress mitigation. Substantial research has highlighted marked increases in LCN2 expression within the substantia nigra (SN), cerebrospinal fluid (CSF), and blood of individuals with PD. This review focuses on the pathological roles of LCN2 in neuroinflammation, aging, neuronal damage, and iron dysregulation in PD. It aims to explore the underlying mechanisms of LCN2 in the disease and potential therapeutic targets that could inform future treatment strategies.

Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions

A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.

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)-2β-carboxymethoxy-3β-(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.

The role of neurovascular coupling dysfunction in cognitive decline of diabetes patients

Neurovascular coupling (NVC) is an important mechanism to ensure adequate blood supply to active neurons in the brain. NVC damage can lead to chronic impairment of neuronal function. Diabetes is characterized by high blood sugar and is considered an important risk factor for cognitive impairment. In this review, we provide fMRI evidence of NVC damage in diabetic patients with cognitive decline. Combined with the exploration of the major mechanisms and signaling pathways of NVC, we discuss the effects of chronic hyperglycemia on the cellular structure of NVC signaling, including key receptors, ion channels, and intercellular connections. Studying these diabetes-related changes in cell structure will help us understand the underlying causes behind diabetes-induced NVC damage and early cognitive decline, ultimately helping to identify the most effective drug targets for treatment.

Neuroimaging Biomarkers in Parkinson's Disease

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple systems in the body and is characterized by a variety of motor and non-motor (e.g., psychiatric, autonomic) symptoms. As the fastest growing neurological disorder expected to affect over 12 million people globally by 2040 (Dorsey, Bloem JAMA Neurol 75(1):9-10. https://doi.org/10.1001/jamaneurol.2017.3299 . PMID: 29131880, 2018), PD poses an enormous individual and public health burden. Currently, there are no therapies that can slow down the disease progression in PD, and existing therapies are limited to symptomatic treatment. Importantly, people in the prodromal phase who are at high risk of developing PD can now be identified, which makes disease prevention an achievable goal. An in-depth understanding of the pathological processes in PD is crucial for prevention and treatment development. Advanced multimodal neuroimaging techniques provide unique biomarkers that can further our understanding of PD at multiple levels ranging from neurotransmitters to neural networks. These neuroimaging biomarkers also have value in clinical application, for example, in the differential diagnosis of PD. As the field continues to advance, neuroimaging biomarkers are expected to become more specific, more widely accessible, and can be readily incorporated into translational research for treatment development in PD.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

White matter hyperintensities in cognitive impairment with Lewy body disease: a multicentre study

BACKGROUND AND PURPOSE

White matter hyperintensities (WMHs) are associated with cognitive deficits and worse clinical outcomes in dementia, but rare studies have been carried out of cognitive impairment in Lewy body disease (CI-LB) patients. The objective was to investigate the associations between WMHs and clinical manifestations in patients with CI-LB.

METHODS

In this retrospective multicentre cohort study, 929 patients (486 with dementia with Lewy bodies [DLB], 262 with Parkinson's disease dementia [PDD], 74 with mild cognitive impairment [MCI] with Lewy bodies [MCI-LB] and 107 with Parkinson's disease with MCI [PD-MCI]) were analysed from 22 memory clinics between January 2018 and June 2022. Demographic and clinical data were collected by reviewing medical records. WMHs were semi-quantified according to the Fazekas method. Associations between WMHs and clinical manifestations were investigated by multivariate linear or logistic regression models.

RESULTS

Dementia with Lewy bodies patients had the highest Fazekas scores compared with PDD, MCI-LB and PD-MCI. Multivariable regressions showed the Fazekas score was positively associated with the scores of Unified Parkinson's Disease Rating Scale Part III (p = 0.001), Hoehn-Yahn stage (p = 0.004) and total Neuropsychiatric Inventory (p = 0.001) in MCI-LB and PD-MCI patients. In patients with DLB and PDD, Fazekas scores were associated with the absence of rapid eye movement sleep behaviour disorder (p = 0.041) and scores of Unified Parkinson's Disease Rating Scale Part III (p < 0.001), Hoehn-Yahn stage (p < 0.001) and the Montreal Cognitive Assessment (p = 0.014).

CONCLUSION

White matter hyperintensity burden of DLB was higher than for PDD, MCI-LB and PD-MCI. The greater WMH burden was significantly associated with poorer cognitive performance, worse motor function and more severe neuropsychiatric symptoms in CI-LB.

Fabry disease and sleep disorders: a systematic review

Background

Fabry disease (FD) is an X-chromosome-linked disorder characterized by a reduced or complete absence of the enzyme α-galactosidase, resulting in the accumulation of lysosomal globotriaosylceramide. Despite the presence of these deposits in multiple organs, the problem of sleep disorders within this population has very rarely been documented.

Objective

This study aimed to investigate the types and prevalence of sleep disorders among patients with FD.

Methods

Screening of the following medical databases using key terms was performed on 10 February 2023: PubMed, Scopus, and Embase. A total of 136 records were identified. The quality assessment of the studies was conducted by using tools from the National Institutes of Health (NIH) and critical appraisal tools from the Joanna Briggs Institute (JBI).

Results

The study included nine studies on sleep disorders in patients with FD. The overall quality of the majority of these studies was assessed as either poor or fair. Among 330 patients, there was a slightly higher representation of female patients (56%). Sleep problems manifested 4-5 years after the onset of FD and sometimes even after 10-11 years. Genotypes of disease associated with sleep problems were rarely described. Within the FD population, the most commonly reported conditions were excessive daytime sleepiness (EDS) as well as obstructive and central sleep apnea (OSA, CSA). However, EDS occurred more frequently in FD patients, while the prevalence of OSA and CSA was within the ranges observed in the general population. The studies included indicated a lack of association between organ impairment by primary disease and EDS and OSA. The effectiveness of enzyme replacement therapy (ERT) in treating sleep disorders was not demonstrated.

Conclusion

The findings of this report revealed the presence of many sleep-related disorders within the FD population. However, very few studies on this subject are available, and their limited results make it difficult to truly assess the real extent of the prevalence of sleep disturbances among these individuals. There is a need to conduct further studies on this topic, involving a larger group of patients. It is important to note that there are no guidelines available for the treatment of sleep disorders in patients with FD.

The Association of the Glymphatic Function with Parkinson's Disease Symptoms: Neuroimaging Evidence from Longitudinal and Cross-Sectional Studies

OBJECTIVE

Emerging pathological evidence suggests that there is an association between glymphatic dysfunction and the progression of Parkinson's disease (PD). However, the clinical evidence of this association remains lacking.

METHODS

In this study, the index for diffusion tensor image analysis along the perivascular space (ALPS index) was calculated to evaluate glymphatic function.

RESULTS

Overall, 289 patients with PD were enrolled in the cross-sectional study. The ALPS index was found to be negatively correlated with age, disease severity, and dyskinesia. In the longitudinal study, the information on a total of 95 PD patients with 5-year follow-up examinations was collected from the Parkinson's Progression Marker Initiative, 33 of which were classified into the low ALPS index group, and all others were classified into the mid-high ALPS index group based on the first tertile of the baseline ALPS index. The results of longitudinal regression indicated that there was a significant main group effect on autonomic dysfunction, as well as on activities of daily living. In addition, the low ALPS index group had faster deterioration in MDS-UPDRS part III and part II, Symbol Digit Modalities Test and Hopkins Verbal Learning Test. Path analysis showed that ALPS index acted as a significant mediator between tTau/ Aβ1-42 and cognitive change in the Symbol Digit Modalities Test score at year 4 and year 5.

INTERPRETATION

The ALPS index, an neuroimaging marker of glymphatic function, is correlated with PD disease severity, motor symptoms, and autonomic function, and is predictive of faster deterioration in motor symptoms and cognitive function. Additionally, glymphatic function may mediate the pathological role of toxic protein in cognitive decline. ANN NEUROL 2023;94:672-683.

Detection of mild cognitive impairment in Parkinson's disease using gradient boosting decision tree models based on multilevel DTI indices

BACKGROUND

Cognitive dysfunction is the most common non-motor symptom in Parkinson's disease (PD), and timely detection of a slight cognitive decline is crucial for early treatment and prevention of dementia. This study aimed to build a machine learning model based on intra- and/or intervoxel metrics extracted from diffusion tensor imaging (DTI) to automatically classify PD patients without dementia into mild cognitive impairment (PD-MCI) and normal cognition (PD-NC) groups.

METHODS

We enrolled PD patients without dementia (52 PD-NC and 68 PD-MCI subtypes) who were assigned to the training and test datasets in an 8:2 ratio. Four intravoxel metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), and two novel intervoxel metrics, local diffusion homogeneity (LDH) using Spearman's rank correlation coefficient (LDHs) and Kendall's coefficient concordance (LDHk), were extracted from the DTI data. Decision tree, random forest, and eXtreme gradient boosting (XGBoost) models based on individual and combined indices were built for classification, and model performance was assessed and compared via the area under the receiver operating characteristic curve (AUC). Finally, feature importance was evaluated using SHapley Additive exPlanation (SHAP) values.

RESULTS

The XGBoost model based on a combination of the intra- and intervoxel indices achieved the best classification performance, with an accuracy of 91.67%, sensitivity of 92.86%, and AUC of 0.94 in the test dataset. SHAP analysis showed that the LDH of the brainstem and MD of the right cingulum (hippocampus) were important features.

CONCLUSIONS

More comprehensive information on white matter changes can be obtained by combining intra- and intervoxel DTI indices, improving classification accuracy. Furthermore, machine learning methods based on DTI indices can be used as alternatives for the automatic identification of PD-MCI at the individual level.

White matter hyperintensity burden predicts cognitive but not motor decline in Parkinson's disease: results from the Ontario Neurodegenerative Diseases Research Initiative

BACKGROUND AND PURPOSE

The pathophysiology of Parkinson's disease (PD) negatively affects brain network connectivity, and in the presence of brain white matter hyperintensities (WMHs) cognitive and motor impairments seem to be aggravated. However, the role of WMHs in predicting accelerating symptom worsening remains controversial. The objective was to investigate whether location and segmental brain WMH burden at baseline predict cognitive and motor declines in PD after 2 years.

METHODS

Ninety-eight older adults followed longitudinally from Ontario Neurodegenerative Diseases Research Initiative with PD of 3-8 years in duration were included. Percentages of WMH volumes at baseline were calculated by location (deep and periventricular) and by brain region (frontal, temporal, parietal, occipital lobes and basal ganglia + thalamus). Cognitive and motor changes were assessed from baseline to 2-year follow-up. Specifically, global cognition, attention, executive function, memory, visuospatial abilities and language were assessed as were motor symptoms evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III, spatial-temporal gait variables, Freezing of Gait Questionnaire and Activities Specific Balance Confidence Scale.

RESULTS

Regression analysis adjusted for potential confounders showed that total and periventricular WMHs at baseline predicted decline in global cognition (p < 0.05). Also, total WMH burden predicted the decline of executive function (p < 0.05). Occipital WMH volumes also predicted decline in global cognition, visuomotor attention and visuospatial memory declines (p < 0.05). WMH volumes at baseline did not predict motor decline.

CONCLUSION

White matter hyperintensity burden at baseline predicted cognitive but not motor decline in early to mid-stage PD. The motor decline observed after 2 years in these older adults with PD is probably related to the primary neurodegenerative process than comorbid white matter pathology.

Age and sex differentially shape brain networks in Parkinson's disease

AIMS

Age and sex are important individual factors modifying the clinical symptoms of patients with Parkinson's disease (PD). Our goal is to evaluate the effects of age and sex on brain networks and clinical manifestations of PD patients.

METHODS

Parkinson's disease participants (n = 198) receiving functional magnetic resonance imaging from Parkinson's Progression Markers Initiative database were investigated. Participants were classified into lower quartile group (age rank: 0%~25%), interquartile group (age rank: 26%~75%), and upper quartile group (age rank: 76%~100%) according to their age quartiles to examine how age shapes brain network topology. The differences of brain network topological properties between male and female participants were also investigated.

RESULTS

Parkinson's disease patients in the upper quartile age group exhibited disrupted network topology of white matter networks and impaired integrity of white matter fibers compared to lower quartile age group. In contrast, sex preferentially shaped the small-world topology of gray matter covariance network. Differential network metrics mediated the effects of age and sex on cognitive function of PD patients.

CONCLUSION

Age and sex have diverse effects on brain structural networks and cognitive function of PD patients, highlighting their roles in the clinical management of PD.

Clinical and MRI features of gait and balance disorders in neurodegenerative diseases

Gait and balance disorders are common signs in several neurodegenerative diseases such as Parkinson's disease, atypical parkinsonism, idiopathic normal pressure hydrocephalus, cerebrovascular disease, dementing disorders and multiple sclerosis. According to each condition, patients present with different gait and balance alterations depending on the structural and functional brain changes through the disease course. In this review, we will summarize the main clinical characteristics of gait and balance disorders in the major neurodegenerative conditions, providing an overview of the significant structural and functional MRI brain alterations underlying these deficits. We also will discuss the role of neurorehabilitation strategies in promoting brain plasticity and gait/balance improvements in these patients.

MRI biomarkers of freezing of gait development in Parkinson’s disease

This study investigated longitudinal clinical, structural and functional brain alterations in Parkinson’s disease patients with freezing of gait (PD-FoG) and in those developing (PD-FoG-converters) and not developing FoG (PD-non-converters) over two years. Moreover, this study explored if any clinical and/or MRI metric predicts FoG development. Thirty PD-FoG, 11 PD-FoG-converters and 11 PD-non-converters were followed for two years. Thirty healthy controls were included at baseline. Participants underwent clinical and MRI visits. Cortical thickness, basal ganglia volumes and functional network graph metrics were evaluated at baseline and over time. In PD groups, correlations between baseline MRI and clinical worsening were tested. A ROC curve analysis investigated if baseline clinical and MRI measures, selected using a stepwise model procedure, could differentiate PD-FoG-converters from PD-non-converters. At baseline, PD-FoG patients had widespread cortical/subcortical atrophy, while PD-FoG-converters and non-converters showed atrophy in sensorimotor areas and basal ganglia relative to controls. Over time, PD-non-converters accumulated cortical thinning of left temporal pole and pallidum without significant clinical changes. PD-FoG-converters showed worsening of disease severity, executive functions, and mood together with an accumulation of occipital atrophy, similarly to PD-FoG. At baseline, PD-FoG-converters relative to controls and PD-FoG showed higher global and parietal clustering coefficient and global local efficiency. Over time, PD-FoG-converters showed reduced parietal clustering coefficient and sensorimotor local efficiency, PD-non-converters showed increased sensorimotor path length, while PD-FoG patients showed stable graph metrics. Stepwise prediction model including dyskinesia, postural instability and gait disorders scores and parietal clustering coefficient was the best predictor of FoG conversion. Combining clinical and MRI data, ROC curves provided the highest classification power to predict the conversion (AUC = 0.95, 95%CI: 0.86–1). Structural MRI is a useful tool to monitor PD progression, while functional MRI together with clinical features may be helpful to identify FoG conversion early.

Morphological basis of Parkinson disease-associated cognitive impairment: an update

Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.

Recent advances in using diffusion tensor imaging to study white matter alterations in Parkinson's disease: A mini review

Parkinson's disease (PD) is the second most common age-related neurodegenerative disease with cardinal motor symptoms. In addition to motor symptoms, PD is a heterogeneous disease accompanied by many non-motor symptoms that dominate the clinical manifestations in different stages or subtypes of PD, such as cognitive impairments. The heterogeneity of PD suggests widespread brain structural changes, and axonal involvement appears to be critical to the pathophysiology of PD. As α-synuclein pathology has been suggested to cause axonal changes followed by neuronal degeneration, diffusion tensor imaging (DTI) as an in vivo imaging technique emerges to characterize early detectable white matter changes due to PD. Here, we reviewed the past 5-year literature to show how DTI has helped identify axonal abnormalities at different PD stages or in different PD subtypes and atypical parkinsonism. We also showed the recent clinical utilities of DTI tractography in interventional treatments such as deep brain stimulation (DBS). Mounting evidence supported by multisite DTI data suggests that DTI along with the advanced analytic methods, can delineate dynamic pathophysiological processes from the early to late PD stages and differentiate distinct structural networks affected in PD and other parkinsonism syndromes. It indicates that DTI, along with recent advanced analytic methods, can assist future interventional studies in optimizing treatments for PD patients with different clinical conditions and risk profiles.