Metabolic brain networks associated with cognitive function in Parkinson's disease

18F-FDG PET findings in Parkinson's disease associated to RAB32 S71R variant

OBJECTIVE

The RAB32 S71R variant has been linked to autosomal dominant Parkinson's disease (RAB32-PD), sharing common biological mechanisms with the leucine-rich repeat kinase-2 (LRRK2) gene. Measurement of regional differences in glucose metabolism with 18F-fluorodeoxyglucose (FDG) PET may improve the understanding of the neural mechanisms of RAB32-related PD and non-mutated PD (NM-PD). In this brief communication, we compared FDG-PET findings of eight RAB32-PD with a cohort of NM-PD.

METHODS

Brain FDG-PET study was performed during the ON medication condition under chronic dopaminergic treatment. All images were normalized to a standard FDG-PET template, then a semi-quantitative analysis was performed on a commercially available fully-automated post-processing software (Cortex ID SUITE, GE Healthcare). Clinical assessment included the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Montreal Cognitive Assessment (MoCA). Continuous variables between groups were compared through the Mann-Whitney test while nominal/ordinal variables through the chi-squared test.

RESULTS

Eight RAB32-PD patients (males:3/8; age:65.38 years [±8.73]; disease duration:10.50 years [±5.88]; H&Y:2.81[±1.22]; MDS-UPDRS-III:36.38 [±25.34]; MoCA:24.88[±5.86]) and 19 NM-PD patients (males:11/19; age:60.53 years [±8.00]; disease duration:8.68 years [±5.70]; H&Y:2.39 [±.51]; MDS-UPDRS-III:29.95 [±11.14]; MoCA:24.21 [±6.07]) were included. No statistically significant differences in FDG-PET data and clinical variables were found between RAB32-PD and NM-PD cohorts. In the majority of RAB-32 PD patients a prevalent parietal hypometabolism was observed, similar to previous findings reported in LRRK2-related PD and NM-PD.

INTERPRETATION

This study represents the first description of FDG-PET findings in RAB32-PD patients, highlighting a possible similar pattern of hypometabolism with LRRK2- and NM-PD. Additional studies with matched and comparable control cohorts are needed to confirm these preliminary results.

Preparing for Parkinson's disease prevention trials: Current progress and future directions

In recent decades, numerous clinical trials have aimed to delay or prevent Parkinson's disease (PD) progression. Despite the theoretical promise and encouraging preclinical data, none have shown clear efficacy in slowing or preventing PD progression, related to several key limitations. Conventional motor and non-motor scales often fall short in detecting early disease changes, while the heterogeneity of PD phenotypes complicates treatment efficacy. The timing of interventions is also critical, as most trials target patients already in advanced stages of neurodegeneration. A deeper understanding of the preclinical phase and the emergence of new pathological frameworks have shifted the focus toward preventing the onset of clinical PD. Recent advances in biomarker research, including tissue, fluid, and imaging markers, are poised to transform PD research by improving patient selection, stratification, and disease progression monitoring. New biologically grounded frameworks for classifying synucleinopathies aim to distinguish biological subtypes from clinical phenotypes, enabling more targeted prevention trials. Successful PD prevention trials will require early enrollment of individuals at the highest risk, employing low-risk personalized interventions, with biomarkers or sensitive clinical markers as endpoints. Early involvement of key stakeholders will be essential to ensure that trials are timely, ethically sound, and aligned with the needs of the PD community.

Patterns of cerebellar cortex hypermetabolism on motor and cognitive functions in PD

Previous studies suggest the cerebellum may play a role in both motor and non-motor symptoms of Parkinson's disease (PD), though molecular evidence remains insufficient. We enrolled 104 PD patients to analyze the correlation between cerebellar glucose metabolism and motor and cognitive functions. Metabolic differences across motor subtypes and cognitive stages were examined, along with their relationship to supratentorial structures. Results showed that glucose metabolism in left cerebellar lobules IV and V was negatively correlated with motor function, with no significant differences between tremor-dominant (TD) and postural instability gait difficulty (PIGD) groups. Metabolism in lobules VI, VIII, and the dentate nucleus negatively correlated with cognitive function, with significant differences across cognitive stages. Cerebellar metabolism was closely linked to the cerebral cortex, and a correlation with the thalamus was observed in the TD group. These findings suggest cerebellar glucose metabolism may reflect compensatory mechanisms, highlighting the cerebellum as a potential therapeutic target.

Correlation of Parkinson's disease severity and 18F-FDG and 18F-FP-DTBZ PET

Background

Positron emission tomography (PET) using the tracer 18F-fluorodeoxyglucose (18F-FDG) and [18F] 9-fluoropropyl-(+)-dihydrotetrabenazine (18F-FP-DTBZ) is widely utilized to measure metabolic activity and dopaminergic integrity in neurodegenerative diseases such as Parkinson's disease (PD). Previous studies employing 18F-FDG PET have primarily focused on motor or non-motor symptoms, rather than the severity of PD. This study aimed to measure the glucose metabolism of 18F-FDG and the dopaminergic function of 18F-FP-DTBZ across various Hoehn-Yahr (H&Y) stages, analyzing the correlation between metabolic activity, dopaminergic function, and H&Y stages to monitor the severity of PD.

Methods

The cross-sectional study recruited 78 PD patients in 3 groups of H&Y stages I, II, and III-V and 18 healthy control (HC) participants to undergo 18F-FDG and 18F-FP-DTBZ PET scans. Differences in cerebral metabolism and dopaminergic function between groups were evaluated using Student's t-test and Mann-Whitney U test. Moreover, Pearson correlation analysis was used to explore the association between cerebral metabolism, dopaminergic function, and H&Y stages in all patients.

Results

Patients with PD exhibited significant hypometabolic activity in the frontal cortex and relative hypermetabolic activity in the putamen, globus pallidus, thalamus, and cerebellum when compared to HC individuals (P<0.05). Further imaging-clinical correlation research depicted the negative correlation between the metabolic activity in the frontal and putamen regions with H&Y stage. Furthermore, the 18F-FP-DTBZ binding reductions were 18.6%, 46.6%, and 56.9% for the caudate, anterior putamen, and posterior putamen at H&Y stages I; 36.0%, 56.9%, and 65.9% at H&Y stages II; and 41.2%, 61.9%, and 68.5% at H&Y stages III-V, respectively. The 18F-FP-DTBZ binding of caudate, anterior putamen, and posterior putamen exhibited significantly negative correlations to H&Y stage.

Conclusions

In PD, 18F-FDG and 18F-FP-DTBZ PET imaging represent potential biomarkers for tracking metabolic activity and dopaminergic degeneration, offering valuable insights into estimating the severity of disease.

Cholinergic Denervation Patterns in Parkinson's Disease Associated With Cognitive Impairment Across Domains

Cognitive impairment is considered to be one of the key features of Parkinson's disease (PD), ultimately resulting in PD-related dementia in approximately 80% of patients over the course of the disease. Several distinct cognitive syndromes of PD have been suggested, driven by different neurotransmitter deficiencies and thus requiring different treatment regimes. In this study, we aimed to identify characteristic brain covariance patterns that reveal how cholinergic denervation is related to PD and to cognitive impairment, focusing on four domains, including attention, executive functioning, memory, and visuospatial cognition. We applied scaled sub-profile model principal component analysis to reveal cholinergic-specific disease-related and cognition-related covariance patterns using [18F]fluoroethoxybenzovesamicol PET imaging. Stepwise logistic regression was applied to predict disease state (PD vs. healthy control). Linear regression models were applied to predict cognitive functioning within the PD group, for each cognitive domain separately. We assessed the performance of the identified patterns with leave-one-out cross validation and performed bootstrapping to assess pattern stability. We included 34 PD patients with various levels of cognitive dysfunction and 10 healthy controls, with similar age, sex, and educational level. The disease-related cholinergic pattern was strongly discriminative (AUC 0.91), and was most prominent in posterior brain regions, with lower tracer uptake in patients compared to controls. We found largely overlapping cholinergic-specific patterns across cognitive domains, with positive correlations between tracer uptake in the opercular cortex, left dorsolateral prefrontal cortex and posterior cingulate gyrus, among other regions, and attention, executive, and visuospatial functioning. Cross validation showed significant correlations between predicted and measured cognition scores, with the exception of memory. We identified a robust structural covariance pattern for the assessment of cholinergic dysfunction related to PD, as well as overlapping cholinergic patterns related to attentional, executive- and visuospatial impairment in PD patients.

Managing cognitive impairment in Parkinson's disease: an update of the literature

INTRODUCTION

Cognitive impairment in Parkinson's disease (PD) substantially affects patient outcomes, function, and quality of life. PD-related cognitive dysfunction is often heterogeneous in clinical presentation and rates of progression. As cognitive changes occur in many people with PD, it is essential to evaluate cognition, provide education, and implement management strategies for cognitive symptoms.

AREAS COVERED

This article describes the symptomatology, epidemiology, risk factors, and pathobiology of cognitive impairment in PD. Additionally, the article provides an overview of evidence-based management and other therapeutic and coping strategies for cognitive impairment and dementia in PD. Comment is offered on challenges and opportunities for trials and emerging therapeutics targeting cognitive symptoms or decline.

EXPERT OPINION

While our understanding of cognitive dysfunction in PD has grown, effective and safe therapeutics are still needed to not only treat cognitive impairment and dementia symptomatically but also slow down or prevent cognitive decline. Further research is needed to elucidate the pathobiology of PD cognitive impairment, develop validated biomarkers reflecting cognitive change, and ultimately, integrate clinical and biological frameworks. Consensus regarding cognitive evaluations, definitions, and criteria of cognitive impairment, evaluating functional abilities in the context of cognitive impairment, and determining optimal outcome measures for clinical trials remain unmet needs.

Cuneus atrophy and Parkinsonian phenoconversion in cognitively unimpaired patients with isolated REM sleep behavior disorder

Isolated rapid-eye-movement sleep behavior disorder (iRBD) is a strong predictor of Parkinson's disease and Dementia with Lewy bodies. Previous studies indicate that cortical atrophy in iRBD patients may be linked to cognitive impairment, but the pattern of atrophy is inconsistently reported. This study aimed to elucidate cortical atrophy patterns in a cognitively unimpaired iRBD cohort, focusing on regions associated with cognitive functions, particularly the cuneus/precuneus, and evaluated the predictive value for future phenoconversion. We conducted voxel-based morphometry and region of interest (ROI) analysis of structural MRI scans of 36 healthy controls and 19 iRBD patients, nine of whom also received a 3-year follow-up MRI scan. The iRBD patients were followed clinically for 8 years, and time-to-event analyses, using Cox regression, were performed based on baseline ROI volumes. The iRBD patients had lower gray-matter volume in the cuneus/precuneus region as well as in subcortical structures (caudate nuclei and putamen) compared to controls. Eight iRBD patients developed either Parkinson's disease (N = 4) or Dementia with Lewy bodies (N = 4) during the follow-up period. Time-to-event analyses showed that lower right cuneus volume was associated with a higher risk of phenoconversion to alpha-synuclein-linked Parkinsonism in the iRBD patients (Hazard ratio = 13.0, CI: 1.53-110), and correlated with shorter time to conversion. In addition, lower volumes of the bilateral precuneus trended to indicate a higher risk of phenoconversion. These findings suggest a potential predictive value of cuneus and precuneus volumes in identifying iRBD patients at risk of disease progression, even before the onset of cognitive impairment.

PET, SPECT, and MRI imaging for evaluation of Parkinson's disease

This review assesses the primary neuroimaging techniques used to evaluate Parkinson's disease (PD) - a neurological condition characterized by gradual dopamine-producing nerve cell degeneration. The neuroimaging techniques explored include positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI). These modalities offer varying degrees of insights into PD pathophysiology, diagnostic accuracy, specificity by way of exclusion of other Parkinsonian syndromes, and monitoring of disease progression. Neuroimaging is thus crucial for diagnosing and managing PD, with integrated multimodal approaches and novel techniques further enhancing early detection and treatment evaluation.

Arterial spin labeling perfusion MRI in the Alzheimer's Disease Neuroimaging Initiative: Past, present, and future

On the 20th anniversary of the Alzheimer's Disease Neuroimaging Initiative (ADNI), this paper provides a comprehensive overview of the role of arterial spin labeling (ASL) magnetic resonance imaging (MRI) in understanding perfusion changes in the aging brain and the relationship with Alzheimer's disease (AD) pathophysiology and its comorbid conditions. We summarize previously used acquisition protocols, available data, and the motivation for adopting a multi-post-labeling delay (PLD) acquisition scheme in the latest ADNI MRI protocol (ADNI 4). We also detail the process of setting up this scheme on different scanners, emphasizing the potential of ASL imaging in future AD research. HIGHLIGHTS: The Alzheimer's Disease Neuroimaging Initiative (ADNI) adopted multimodal arterial spin labeling magnetic resonance imaging (ASL MRI) to meet evolving biomarker requirements. The ADNI provides one of the largest multisite, multi-vendor ASL data collections. The ADNI 4 incorporates multi-post-labeling delay ASL techniques to jointly quantify cerebral blood flow and arterial transit time. ADNI 4 ASL MRI protocol is apt for detecting early Alzheimer's disease with cerebrovascular pathology.

Multimodal neuroimaging-based prediction of Parkinson's disease with mild cognitive impairment using machine learning technique

This study aimed to identify potential markers that can predict Parkinson's disease with mild cognitive impairment (PDMCI). We retrospectively collected general demographic data, clinically relevant scales, plasma samples, and neuroimaging data (T1-weighted magnetic resonance imaging (MRI) data as well as resting-state functional MRI [Rs-fMRI] data) from 173 individuals. Subsequently, based on the aforementioned multimodal indices, a support vector machine was employed to investigate the machine learning (ML) classification of PD patients with normal cognition (PDNC) and PDMCI. The performance of 29 classifiers was assessed based on various combinations of indicators. Results demonstrated that the optimal classifier in the validation set was composed by clinical + Rs-fMRI+ neurofilament light chain, exhibiting a mean Accuracy of 0.762, a mean area under curve of 0.840, a mean sensitivity of 0.745, along with a mean specificity of 0.783. The ML algorithm based on multimodal data demonstrated enhanced discriminative ability between PDNC and PDMCI patients.

Exploring symptomatology and innovative treatment modalities for prefrontal cortex lesions: a systematic review

BACKGROUND

Pre-frontal cortex operates a combination of emotional, cognitive and behavioural functions. Understanding the symptoms of pre-frontal cortex lesions serves as paramount for accurate diagnosis and management.

AIMS

This review aims to determine an association between the causes of prefrontal cortex lesions and the resulting symptoms, as well as the ideal form of treatment.

STUDY DESIGN

A systematic review through utilisation of 3 databases was done using the keywords "Prefrontal cortex lesions," "dysfunction," "symptoms," &" treatment".

METHODOLOGY

RCTs, observational studies, and systematic reviews were searched using Cochrane/EMBASE, PubMed/Medline, and Pedro between 1948 and2024. Studies published in English only were included, and two reviewers were involved in the data extraction process.

RESULTS

Results showed a notable correlation between right-handed individuals and prefrontal cortex lesions with cognition impairment, particularly executive dysfunction, being the most prevalent symptom. Emotional instability followed as the second most common issue, while aphasia remained the primary language deficit. Noninvasive brain stimulation emerged as an effective treatment option for various prefrontal cortex-related disorders.

CONCLUSION

Further investigation is needed to understand the mechanism linking handedness to lesion occurrence. Noninvasive brain stimulation should be prioritised for treating prefrontal injuries.

Cerebral Glucose Metabolism Is a Valuable Predictor of Survival in Patients with Lewy Body Diseases

OBJECTIVE

Patients with Lewy body diseases have an increased risk of dementia, which is a significant predictor for survival. Posterior cortical hypometabolism on [18F]fluorodeoxyglucose positron emission tomography (PET) precedes the development of dementia by years. We therefore examined the prognostic value of cerebral glucose metabolism for survival.

METHODS

We enrolled patients diagnosed with Parkinson's disease (PD), Parkinson's disease with dementia, or dementia with Lewy bodies who underwent [18F]fluorodeoxyglucose PET. Regional cerebral metabolism of each patient was analyzed by determining the expression of the PD-related cognitive pattern (Z-score) and by visual PET rating. We analyzed the predictive value of PET for overall survival using Cox regression analyses (age- and sex-corrected) and calculated prognostic indices for the best model.

RESULTS

Glucose metabolism was a significant predictor of survival in 259 included patients (n = 118 events; hazard ratio: 1.4 [1.2-1.6] per Z-score; hazard ratio: 1.8 [1.5-2.2] per visual PET rating score; both p < 0.0001). Risk stratification with visual PET rating scores yielded a median survival of 4.8, 6.8, and 12.9 years for patients with severe, moderate, and mild posterior cortical hypometabolism (median survival not reached for normal cortical metabolism). Stratification into 5 groups based on the prognostic index revealed 10-year survival rates of 94.1%, 78.3%, 34.7%, 0.0%, and 0.0%.

INTERPRETATION

Regional cerebral glucose metabolism is a significant predictor of survival in Lewy body diseases and may allow an earlier survival prediction than the clinical milestone "dementia." Thus, [18F]fluorodeoxyglucose PET may improve the basis for therapy decisions, especially for invasive therapeutic procedures like deep brain stimulation in Parkinson's disease. ANN NEUROL 2024;96:539-550.

Biomarkers of Parkinson's disease in perspective of early diagnosis and translation of neurotrophic therapies

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by progressive loss of dopamine neurons and aberrant deposits of alpha-synuclein (α-syn) in the brain. The symptomatic treatment is started after the onset of motor manifestations in a late stage of the disease. Preclinical studies with neurotrophic factors (NTFs) show promising results of disease-modifying neuroprotective or even neurorestorative effects. Four NTFs have entered phase I-II clinical trials with inconclusive outcomes. This is not surprising because the preclinical evidence is from acute early-stage disease models, but the clinical trials included advanced PD patients. To conclude the value of NTF therapies, clinical studies should be performed in early-stage patients with prodromal symptoms, that is, before motor manifestations. In this review, we summarize currently available diagnostic and prognostic biomarkers that could help identify at-risk patients benefiting from NTF therapies. Focus is on biochemical and imaging biomarkers, but also other modalities are discussed. Neuroimaging is the most important diagnostic tool today, but α-syn imaging is not yet viable. Modern techniques allow measuring various forms of α-syn in cerebrospinal fluid, blood, saliva, and skin. Digital biomarkers and artificial intelligence offer new means for early diagnosis and longitudinal follow-up of degenerative brain diseases.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

PET-based brain molecular connectivity in neurodegenerative disease

PURPOSE OF REVIEW

Molecular imaging has traditionally been used and interpreted primarily in the context of localized and relatively static neurochemical processes. New understanding of brain function and development of novel molecular imaging protocols and analysis methods highlights the relevance of molecular networks that co-exist and interact with functional and structural networks. Although the concept and evidence of disease-specific metabolic brain patterns has existed for some time, only recently has such an approach been applied in the neurotransmitter domain and in the context of multitracer and multimodal studies. This review briefly summarizes initial findings and highlights emerging applications enabled by this new approach.

RECENT FINDINGS

Connectivity based approaches applied to molecular and multimodal imaging have uncovered molecular networks with neurodegeneration-related alterations to metabolism and neurotransmission that uniquely relate to clinical findings; better disease stratification paradigms; an improved understanding of the relationships between neurochemical and functional networks and their related alterations, although the directionality of these relationships are still unresolved; and a new understanding of the molecular underpinning of disease-related alteration in resting-state brain activity.

SUMMARY

Connectivity approaches are poised to greatly enhance the information that can be extracted from molecular imaging. While currently mostly contributing to enhancing understanding of brain function, they are highly likely to contribute to the identification of specific biomarkers that will improve disease management and clinical care.

Disrupted Brain Network Measures in Parkinson's Disease Patients with Severe Hyposmia and Cognitively Normal Ability

Neuroscience has revolved around brain structural changes, functional activity, and connectivity alteration in Parkinson's Disease (PD); however, how the network topology organization becomes altered is still unclear, specifically in Parkinson's patients with severe hyposmia. In this study, we have examined the functional network topological alteration in patients affected by Parkinson's Disease with normal cognitive ability (ODN), Parkinson's Disease with severe hyposmia (ODP), and healthy controls (HCs) using resting-state functional magnetic resonance imaging (rsfMRI) data. We have analyzed brain topological organization using popular graph measures such as network segregation (clustering coefficient, modularity), network integration (participation coefficient, path length), small-worldness, efficiency, centrality, and assortativity. Then, we used a feature ranking approach based on the diagonal adaptation of neighborhood component analysis, aiming to determine a graph measure that is sensitive enough to distinguish between these three different groups. We noted significantly lower segregation and local efficiency and small-worldness in ODP compared to ODN and HCs. On the contrary, we did not find differences in network integration in ODP compared to ODN and HCs, which indicates that the brain network becomes fragmented in ODP. At the brain network level, a progressive increase in the DMN (Default Mode Network) was observed from healthy controls to ODN to ODP, and a continuous decrease in the cingulo-opercular network was observed from healthy controls to ODN to ODP. Further, the feature ranking approach has shown that the whole-brain clustering coefficient and small-worldness are sensitive measures to classify ODP vs. ODN, as well as HCs. Looking at the brain regional network segregation, we have found that the cerebellum and limbic, fronto-parietal, and occipital lobes have higher ODP reductions than ODN and HCs. Our results suggest network topological measures, specifically whole-brain segregation and small-worldness decreases. At the network level, an increase in DMN and a decrease in the cingulo-opercular network could be used as biomarkers to characterize ODN and ODP.

A longitudinal evaluation of personalized intrinsic network topography and cognitive decline in Parkinson's disease

Resting state functional magnetic resonance imaging (R-fMRI) offers insight into how synchrony within and between brain networks is altered in disease states. Individual and disease-related variability in intrinsic connectivity networks may influence our interpretation of R-fMRI data. We used a personalized approach designed to account for individual variation in the spatial location of correlation maxima to evaluate R-fMRI differences between Parkinson's disease (PD) patients who showed cognitive decline, those who remained cognitively stable and cognitively stable controls. We compared fMRI data from these participant groups, studied at baseline and 18 months later, using both network-based statistics (NBS) and calculations of mean inter- and intra-network connectivity within pre-defined functional networks. The NBS analysis showed that PD participants who remained cognitively stable showed exclusively (at baseline) or predominantly (at follow-up) increased intra-network connectivity, whereas decliners showed exclusively reduced intra-network and inter- (ventral attention and default mode) connectivity, in comparison with the control group. Evaluation of mean connectivity between all regions of interest (ROIs) within a priori networks showed that decliners had consistently reduced inter-network connectivity for ventral attention, somatomotor, visual and striatal networks and reduced intra-network connectivity for ventral attention network to striatum and cerebellum. These findings suggest that specific functional connectivity covariance patterns differentiate PD cognitive subtypes and may predict cognitive decline. Further, increased intra and inter-network synchrony may support cognitive function in the face of PD-related network disruptions.

Neuroanatomical Signature of the Transition from Normal Cognition to MCI in Parkinson's Disease

The progression of Parkinson's disease (PD) is often accompanied by cognitive decline. We had previously developed a brain age estimation program utilizing structural MRI data of 949 healthy individuals from publicly available sources. Structural MRI data of 244 PD patients who were cognitively normal at baseline was acquired from the Parkinson Progression Markers Initiative (PPMI). 192 of these showed stable normal cognitive function from baseline out to 5 years (PD-SNC), and the remaining 52 had unstable normal cognition and developed mild cognitive impairment within 5 years (PD-UNC). 105 healthy controls were also included in the analysis as a reference. First, we examined if there were any baseline differences in regional brain structure between PD-UNC and PD-SNC cohorts utilizing the three most widely used atrophy estimation pipelines, i.e., voxel-based morphometry (VBM), deformation-based morphometry and cortical thickness analyses. We then investigated if accelerated brain age estimation with our multivariate regressive machine learning algorithm was different across these groups (HC, PD-SNC, and PD-UNC). As per the VBM analysis, PD-UNC patients demonstrated a noticeable increase in GM volume in the posterior and anterior lobes of the cerebellum, sub-lobar, extra-nuclear, thalamus, and pulvinar regions when compared to PD-SNC at baseline. PD-UNC patients were observed to have significantly older brain age compared to both PD-SNC patients (p=0.009) and healthy controls (p<0.009). The increase in GM volume in the PD-UNC group could potentially indicate an inflammatory or neuronal hypertrophy response, which could serve as a biomarker for future cognitive decline among this population.

Radionuclide Imaging of the Neuroanatomical and Neurochemical Substrate of Cognitive Decline in Parkinson's Disease

Cognitive impairment is a frequent manifestation of Parkinson's disease (PD), resulting in decrease in patients' quality of life and increased societal and economic burden. However, cognitive decline in PD is highly heterogenous and the mechanisms are poorly understood. Radionuclide imaging techniques like positron emission tomography (PET) and single photon emission computed tomography (SPECT) have been used to investigate the neurochemical and neuroanatomical substrate of cognitive decline in PD. These techniques allow the assessment of different neurotransmitter systems, changes in brain glucose metabolism, proteinopathy, and neuroinflammation in vivo in PD patients. Here, we review current radionuclide imaging research on cognitive deficit in PD with a focus on predicting accelerating cognitive decline. This research could assist in the development of prognostic biomarkers for patient stratification and have utility in the development of ameliorative or disease-modifying therapies targeting cognitive deficit in PD.

New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment

Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.

Refining the clinical diagnosis of Parkinson's disease

Our ability to define, understand, and classify Parkinson's disease (PD) has undergone significant changes since the disorder was first described in 1817. Clinical features and neuropathologic signatures can now be supplemented by in-vivo interrogation of genetic and biological substrates of disease, offering great opportunity for further refining the diagnosis of PD. In this mini-review, we discuss the historical perspectives which shaped our thinking surrounding the definition and diagnosis of PD. We highlight the clinical, genetic, pathologic and biologic diversity which underpins the condition, and proceed to discuss how recent developments in our ability to define biologic and pathologic substrates of disease might impact PD definition, diagnosis, individualised prognostication, and personalised clinical care. We argue that Parkinson's 'disease', as currently diagnosed in the clinic, is actually a syndrome. It is the outward manifestation of any array of potential dysfunctional biologic processes, neuropathological changes, and disease aetiologies, which culminate in common outward clinical features which we term PD; each person has their own unique disease, which we can now define with increasing precision. This is an exciting time in PD research and clinical care. Our ability to refine the clinical diagnosis of PD, incorporating in-vivo assessments of disease biology, neuropathology, and neurogenetics may well herald the era of biologically-based, precision medicine approaches PD management. With this however comes a number of challenges, including how to integrate these technologies into clinical practice in a way which is acceptable to patients, promotes meaningful changes to care, and minimises health economic impact.

Association of Parkinson's disease to Parkinson's plus syndromes, Lewy body dementia, and Alzheimer's dementia

Background

Parkinson's disease (PD) is a condition that affects movement and is usually seen in those over the age of 50. It is caused by the death of dopaminergic neurons, particularly in the substantia nigra. PD has shifted from being perceived as an uncommon condition to a significant neurological illness, mostly due to the increasing number of elderly individuals and the impact of environmental factors. Parkinson's plus syndromes, such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and vascular Parkinsonism (VaP), provide difficulties in distinguishing them clinically from PD since they have similar characteristics.

Methodology

A thorough examination was performed utilizing the PubMed, Medline, Scopus, and Web of Science databases. The search utilized specific keywords like "Parkinson's disease," "Parkinson's plus syndrome," "Lewy body dementia," "Alzheimer's dementia," "progressive supranuclear palsy," and "multiple system atrophy." The selection criteria were aimed at English-language literature, with a particular focus on examining the connection between PD and associated disorders or dementias.

Results and Discussion

Parkinson's plus syndromes, such as PSP, MSA, CBD, and VaP, exhibit unique clinical characteristics, imaging results, and diverse reactions to levodopa. This makes it difficult to distinguish them from PD. LBD is characterized by Lewy bodies containing α-synuclein, which leads to both motor and cognitive deficits. PD and Alzheimer's disease (AD) exhibit a complex interaction, including common pathogenic processes, genetic predispositions, and clinical characteristics of dementia.

Conclusion

The interrelatedness of PD, Parkinson's plus syndromes, LBD, and AD highlights the significance of comprehending shared disease-causing processes. Aberrant protein clumping, impaired functioning of mitochondria, increased oxidative stress, and inflammation in the brain are common factors which can be addressed for specific treatments. More research is essential for understanding complicated connections and developing effective therapies for these sophisticated neurological illnesses.

A review of the neurotransmitter system associated with cognitive function of the cerebellum in Parkinson's disease

The dichotomized brain system is a concept that was generalized from the 'dual syndrome hypothesis' to explain the heterogeneity of cognitive impairment, in which anterior and posterior brain systems are independent but partially overlap. The dopaminergic system acts on the anterior brain and is responsible for executive function, working memory, and planning. In contrast, the cholinergic system acts on the posterior brain and is responsible for semantic fluency and visuospatial function. Evidence from dopaminergic/cholinergic imaging or functional neuroimaging has shed significant insight relating to the involvement of the cerebellum in the cognitive process of patients with Parkinson's disease. Previous research has reported evidence that the cerebellum receives both dopaminergic and cholinergic projections. However, whether these two neurotransmitter systems are associated with cognitive function has yet to be fully elucidated. Furthermore, the precise role of the cerebellum in patients with Parkinson's disease and cognitive impairment remains unclear. Therefore, in this review, we summarize the cerebellar dopaminergic and cholinergic projections and their relationships with cognition, as reported by previous studies, and investigated the role of the cerebellum in patients with Parkinson's disease and cognitive impairment, as determined by functional neuroimaging. Our findings will help us to understand the role of the cerebellum in the mechanisms underlying cognitive impairment in Parkinson's disease.

Hippocampal Perfusion Affects Motor and Cognitive Functions in Parkinson Disease: An Early Phase 18 F-FP-CIT Positron Emission Tomography Study

OBJECTIVE

We investigated whether hippocampal perfusion changes are associated with cognitive decline, motor deficits, and the risk of dementia conversion in patients with Parkinson disease (PD).

METHODS

We recruited patients with newly diagnosed and nonmedicated PD and healthy participants who underwent dual phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane positron emission tomography scans. Patients were classified into 3 groups according to hippocampal perfusion measured by standard uptake value ratios (SUVRs): (1) PD hippocampal hypoperfusion group (1 standard deviation [SD] below the mean hippocampal SUVR of healthy controls; PD-hippo-hypo), (2) PD hippocampal hyperperfusion group (1 SD above the mean; PD-hippo-hyper), and (3) the remaining patients (PD-hippo-normal). We compared the baseline cognitive performance, severity of motor deficits, hippocampal volume, striatal dopamine transporter (DAT) availability, and risk of dementia conversion among the groups.

RESULTS

We included 235 patients (PD-hippo-hypo, n = 21; PD-hippo-normal, n = 157; PD-hippo-hyper, n = 57) and 48 healthy participants. Patients in the PD-hippo-hypo group were older and had smaller hippocampal volumes than those in the other PD groups. The PD-hippo-hypo group showed less severely decreased DAT availability in the putamen than the other groups despite similar severities of motor deficit. The PD-hippo-hypo group had a higher risk of dementia conversion compared to the PD-hippo-normal (hazard ratio = 2.59, p = 0.013) and PD-hippo-hyper (hazard ratio = 3.73, p = 0.006) groups, despite similar cognitive performance at initial assessment between groups.

INTERPRETATION

Hippocampal hypoperfusion may indicate a reduced capacity to cope with neurodegenerative processes in terms of the development of motor deficits and cognitive decline in patients with PD. ANN NEUROL 2024;95:388-399.

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.

Is the cingulate island sign a marker for early dementia conversion in Parkinson's disease?

BACKGROUND

To investigate whether the cingulate island sign (CIS) ratio (i.e., the ratio of regional uptake in the posterior cingulate cortex relative to the precuneus and cuneus on cerebral perfusion scans) is associated with early dementia conversion in Parkinson's disease (PD).

METHODS

We enrolled 226 patients with newly diagnosed PD and 48 healthy controls who underwent dual-phase 18 F-FP-CIT PET scans. Patients with PD were classified into three groups according to the CIS ratio on early-phase 18 F-FP-CIT PET images: a PD group with CIS or high CIS ratios (PD-CIS; n = 96), a PD group with inverse CIS or low CIS ratios (PD-iCIS; n = 40), and a PD group consisting of the remaining patients with normal CIS ratios (PD-nCIS; n = 90). We compared the risk of dementia conversion within a 5-year time point between the groups.

RESULTS

There were no significant differences in age, sex, education, or baseline cognitive function between the PD groups. The PD-CIS group had higher Unified Parkinson's Disease Rating Scale (UPDRS) motor scores and more severely decreased dopamine transporter availability in the putamen. The PD-iCIS group had a smaller hippocampal volume compared with the other groups. The risk of dementia conversion in the PD-CIS group did not differ from that in the PD-iCIS and PD-nCIS groups. Meanwhile, the PD-iCIS group had a higher risk of dementia conversion than the PD-nCIS group.

CONCLUSION

The results of this study suggest that inverse CIS, rather than CIS, is relevant to early dementia conversion in patients with PD.

How should we be using biomarkers in trials of disease modification in Parkinson's disease?

The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.

Salience network and cognitive impairment in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson's Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We tested the hypothesis that cognitive impairments in PD involve altered connectivity of the salience network (SN), a key cortical network that detects and integrates responses to salient stimuli. We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. We report two major results. First, in 82 PD patients we found significant relationships between lower intra-network connectivity of the frontoparietal network (FPN; comprising the dorsolateral prefrontal and posterior parietal cortices bilaterally) with lower MoCA scores. Second, we found significant relationships between lower inter-network connectivity between the SN and the basal ganglia network (BGN) and the default mode network (DMN) with lower MoCA scores. These data support our hypothesis about the SN and provide new insights into the brain networks contributing to cognitive impairments in PD.

A Network Imaging Biomarker of X-Linked Dystonia-Parkinsonism

OBJECTIVE

The purpose of this study was to characterize a metabolic brain network associated with X-linked dystonia-parkinsonism (XDP).

METHODS

Thirty right-handed Filipino men with XDP (age = 44.4 ± 8.5 years) and 30 XDP-causing mutation negative healthy men from the same population (age = 37.4 ± 10.5 years) underwent [18 F]-fluorodeoxyglucose positron emission tomography. Scans were analyzed using spatial covariance mapping to identify a significant XDP-related metabolic pattern (XDPRP). Patients were rated clinically at the time of imaging according to the XDP-Movement Disorder Society of the Philippines (MDSP) scale.

RESULTS

We identified a significant XDPRP topography from 15 randomly selected subjects with XDP and 15 control subjects. This pattern was characterized by bilateral metabolic reductions in caudate/putamen, frontal operculum, and cingulate cortex, with relative increases in the bilateral somatosensory cortex and cerebellar vermis. Age-corrected expression of XDPRP was significantly elevated (p < 0.0001) in XDP compared to controls in the derivation set and in the remaining 15 patients (testing set). We validated the XDPRP topography by identifying a similar pattern in the original testing set (r = 0.90, p < 0.0001; voxel-wise correlation between both patterns). Significant correlations between XDPRP expression and clinical ratings for parkinsonism-but not dystonia-were observed in both XDP groups. Further network analysis revealed abnormalities of information transfer through the XDPRP space, with loss of normal connectivity and gain of abnormal functional connections linking network nodes with outside brain regions.

INTERPRETATION

XDP is associated with a characteristic metabolic network associated with abnormal functional connectivity among the basal ganglia, thalamus, motor regions, and cerebellum. Clinical signs may relate to faulty information transfer through the network to outside brain regions. ANN NEUROL 2023;94:684-695.

Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease

Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials.

Role of Arterial Spin Labeling (ASL) Images in Parkinson's Disease (PD): A Systematic Review

RATIONALE AND OBJECTIVES

Parkinson's disease is a chronic progressive neurodegenerative disorder with standard structural MRIs often showing no gross abnormalities. Quantitative perfusion MRI modality Arterial Spin Labeling (ASL) is helpful in identifying PD specific perfusion patterns. Absolute Cerebral blood flow (CBF) measurement using ASL provides insights into regional perfusion abnormalities. We reviewed the role of ASL to identify specific brain regions responsible for motor, non-motor symptoms and neurovascular changes observed in PD. Challenges in assessing the blood perfusion level are discussed with future development for improving the evaluation of ASL perfusion maps.

MATERIALS AND METHODS

We included CBF quantification studies using ASL for PD diagnosis. A systematic search was performed in Pubmed, Scopus and Web of Science. The perfusion parameters CBF and arterial arrival time (AAT) measured using ASL were considered for brain region assessment. Clinical aspects of PD have been analyzed using ASL perfusion maps.

RESULTS

The systematic search identified 153 unique records. Thirty articles were selected after verification of inclusion and exclusion criteria. Voxel and region-based analyses in white and gray matter tissues have been performed to identify PD-specific perfusion patterns by reported articles. Predominant brain regions such as basal ganglia sub-regions, frontoparietal network, precuneus, occipital lobe, sensory motor area regions, visual network, which are associated with motor and non-motor symptoms in PD, were identified with CBF hypoperfusion, indicating neuronal loss and cerebrovascular dysfunction.

CONCLUSION

CBF and AAT values derived from ASL can potentially be used as biomarkers to discriminate PD from similar brain-related disorders.

Cognitive Deficits in Parkinson's Disease Are Associated with Neuronal Dysfunction and Not White Matter Lesions

Background

Cognitive deficits considerably contribute to the patient's burden in Parkinson's disease (PD). While cognitive decline is linked to neuronal dysfunction, the additional role of white matter lesions (WML) is discussed controversially.

Objective

To investigate the influence of WML, in comparison to neuronal dysfunction, on cognitive deficits in PD.

Methods

We prospectively recruited patients with PD who underwent neuropsychological assessment using the Mattis Dementia Rating Scale 2 (DRS-2) or Parkinson Neuropsychometric Dementia Assessment (PANDA) and both MRI and PET with [¹⁸F]fluorodeoxyglucose (FDG). WML-load and PD cognition-related covariance pattern (PDCP) as a measure of neuronal dysfunction were read out. Relationship between cognitive performance and rank-transformed WML was analyzed with linear regression, controlling for the patients' age. PDCP subject scores were investigated likewise and in a second step adjusting for age and WML load.

Results

Inclusion criteria were met by 76 patients with a mean (± SD) age of 63.5 ± 9.0 years and disease duration of 10.7 ± 5.4 years. Neuropsychological testing revealed front executive and parietal deficits and a median DRS-2 score of 137 (range 119-144)/144 and PANDA score of 22 (range 3-30)/30. No association between WML and cognition was observed, whereas PDCP subject scores showed a trend-level negative correlation with the DRS-2 (P = 0.060) as well as a negative correlation with PANDA (P = 0.049) which persisted also after additional correction for WML (P = 0.039).

Conclusion

The present study indicates that microangiopathic WML do not have a relevant impact on neurocognitive performance in PD whereas neuronal dysfunction does.

Abnormal cerebellum connectivity patterns related to motor subtypes of Parkinson's disease

Cerebellar dysfunction may substantially contribute to the clinical symptoms of Parkinson's disease (PD). The role of cerebellar subregions in tremors and gait disturbances in PD remains unknown. To investigate alterations in cerebellar subregion volumes and functional connectivity (FC), as well as FC between the dentate nucleus (DN) and ventral lateral posterior nucleus (VLp) of the thalamus, which are potentially involved in different PD motor subtypes. We conducted morphometric and resting-state functional connectivity analyses in various cerebellar subregions in 22 tremor-dominant (TD)-PD and 35 postural instability gait difficulty dominant (PIGD)-PD patients and 38 sex- and age-matched healthy controls (HCs). The volume and FC alterations in various cerebellar subregions and the neural correlates of these changes with the clinical severity scores were investigated. The PIGD-PD group showed greater FC between the right motor cerebellum (CBMm) and left postcentral gyrus than the HC group, and a higher FC was associated with less severe PIGD symptoms. In contrast, the TD-PD group had decreased FC between the right DN and left VLp compared with the PIGD-PD and HC groups, and lower FC was associated with worse TD symptoms. Furthermore, the PIGD-PD group had higher FC between the left DN and left inferior temporal gyrus than the TD-PD group. Morphometric analysis revealed that the TD-PD group showed a significantly higher volume of left CBMm than the HC group. Our findings point to differential alteration patterns in cerebellar subregions and offer a new perspective on the pathophysiology of motor subtypes of PD.

Impaired self-awareness of cognitive deficits in Parkinson's disease relates to cingulate cortex dysfunction

BACKGROUND

Impaired self-awareness of cognitive deficits (ISAcog) has rarely been investigated in Parkinson's disease (PD). ISAcog is associated with poorer long-term outcome in other diseases. This study examines ISAcog in PD with and without mild cognitive impairment (PD-MCI), compared to healthy controls, and its clinical-behavioral and neuroimaging correlates.

METHODS

We examined 63 PD patients and 30 age- and education-matched healthy controls. Cognitive state was examined following the Movement Disorder Society Level II criteria. ISAcog was determined by subtracting z-scores (based on controls' scores) of objective tests and subjective questionnaires. Neural correlates were assessed by structural magnetic resonance imaging (MRI) and 2-[fluorine-18]fluoro-2-deoxy-d-glucose-positron emission tomography (FDG-PET) in 47 patients (43 with MRI) and 11 controls. We analyzed whole-brain glucose metabolism and cortical thickness in regions where FDG-uptake correlated with ISAcog.

RESULTS

PD-MCI patients (N = 23) showed significantly more ISAcog than controls and patients without MCI (N = 40). When all patients who underwent FDG-PET were examined, metabolism in the bilateral superior medial frontal gyrus, anterior and midcingulate cortex negatively correlated with ISAcog (FWE-corrected p < 0.001). In PD-MCI, ISAcog was related to decreased metabolism in the right superior temporal lobe and insula (N = 13; FWE-corrected p = 0.023) as well as the midcingulate cortex (FWE-corrected p = 0.002). Cortical thickness was not associated with ISAcog in these regions. No significant correlations were found between ISAcog and glucose metabolism in controls and patients without MCI.

CONCLUSIONS

Similar to Alzheimer's disease, the cingulate cortex seems to be relevant in ISAcog in PD. In PD-MCI patients, ISAcog might result from a disrupted network that regulates awareness of cognition and error processes.

Regional cortical hypoperfusion and atrophy correlate with striatal dopaminergic loss in Parkinson's disease: a study using arterial spin labeling MR perfusion

PURPOSE

To investigate the relationship of the striatal dopamine transporter density to changes in the gray matter (GM) volume and cerebral perfusion in patients with Parkinson's disease (PD).

METHODS

We evaluated the regional cerebral blood flow (CBF) and GM volume, concurrently measured using arterial spin labeling and T1-weighted magnetic resonance imaging, respectively, as well as the striatal specific binding ratio (SBR) in ¹²³I-N-ω-fluoropropyl-2β-carboxymethoxy-3β-(4-iodophenyl)nortropane (¹²³I-FP-CIT) single-photon emission computed tomography in 30 non-demented patients with PD (15 men and 15 women; mean age, 67.2 ± 8.8 years; mean Hoehn-Yahr stage, 2.2 ± 0.9). Voxel-wise regression analyses using statistical parametric mapping (SPM) were performed to explore the brain regions that showed correlations of the striatal SBR to the GM volume and CBF, respectively, with a height threshold of p < 0.0005 at the voxel level and p < 0.05 family-wise error-corrected at the cluster level.

RESULTS

SPM analysis showed a significant positive correlation between the SBR and GM volume in the inferior frontal gyrus (IFG). Whereas, a positive correlation between the SBR and CBF was widely found in the frontotemporal and parietotemporal regions, including the IFG. Notably, the opercular part of the IFG showed significant correlations in both SPM analyses of the GM volume (r² = 0.90, p < 0.0001) and CBF (r² = 0.88, p < 0.0001).

CONCLUSION

The voxel-wise analyses revealed the brain regions, mainly the IFG, that showed hypoperfusion and atrophy related to dopaminergic loss, which suggests that the progression of dopaminergic neurodegeneration leads to regional cortical dysfunction in PD.

Functional brain networks in the evaluation of patients with neurodegenerative disorders

Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.

Abnormal intra- and inter-network functional connectivity of brain networks in early-onset Parkinson's disease and late-onset Parkinson's disease

Objective

The purpose of this study is to look into the altered functional connectivity of brain networks in Early-Onset Parkinson's Disease (EOPD) and Late-Onset Parkinson's Disease (LOPD), as well as their relationship to clinical symptoms.

Methods

A total of 50 patients with Parkinson' disease (28 EOPD and 22 LOPD) and 49 healthy controls (25 Young Controls and 24 Old Controls) were admitted to our study. Employing independent component analysis, we constructed the brain networks of EOPD and Young Controls, LOPD and Old Controls, respectively, and obtained the functional connectivity alterations in brain networks.

Results

Cerebellar network (CN), Sensorimotor Network (SMN), Executive Control Network (ECN), and Default Mode Network (DMN) were selected as networks of interest. Compared with their corresponding health controls, EOPD showed increased functional connectivity within the SMN and ECN and no abnormalities of inter-network functional connectivity were found, LOPD demonstrated increased functional connectivity within the ECN while decreased functional connectivity within the CN. Furthermore, in LOPD, functional connectivity between the SMN and DMN was increased. The functional connectivity of the post-central gyrus within the SMN in EOPD was inversely correlated with the Unified Parkinson's Disease Rating Scale Part III scores. Age, age of onset, and MMSE scores are significantly different between EOPD and LOPD (p < 0.05).

Conclusion

There is abnormal functional connectivity of networks in EOPD and LOPD, which could be the manifestation of the associated pathological damage or compensation.

Deep Brain Stimulation in the Subthalamic Nucleus Can Improve Skilled Forelimb Movements and Retune Dynamics of Striatal Networks in a Rat Stroke Model

Recovery of upper limb (UL) impairment after stroke is limited in stroke survivors. Since stroke can be considered as a network disorder, neuromodulation may be an approach to improve UL motor dysfunction. Here, we evaluated the effect of high-frequency stimulation (HFS) of the subthalamic nucleus (STN) in rats on forelimb grasping using the single-pellet reaching (SPR) test after stroke and determined costimulated brain regions during STN-HFS using 2-[18F]Fluoro-2-deoxyglucose-([18F]FDG)-positron emission tomography (PET). After a 4-week training of SPR, photothrombotic stroke was induced in the sensorimotor cortex of the dominant hemisphere. Thereafter, an electrode was implanted in the STN ipsilateral to the infarction, followed by a continuous STN-HFS or sham stimulation for 7 days. On postinterventional day 2 and 7, an SPR test was performed during STN-HFS. Success rate of grasping was compared between these two time points. [18F]FDG-PET was conducted on day 2 and 3 after stroke, without and with STN-HFS, respectively. STN-HFS resulted in a significant improvement of SPR compared to sham stimulation. During STN-HFS, a significantly higher [18F]FDG-uptake was observed in the corticosubthalamic/pallidosubthalamic circuit, particularly ipsilateral to the stimulated side. Additionally, STN-HFS led to an increased glucose metabolism within the brainstem. These data demonstrate that STN-HFS supports rehabilitation of skilled forelimb movements, probably by retuning dysfunctional motor centers within the cerebral network.

Deep learning signature of brain [18F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder

An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [¹⁸F]FDG PET based on deep learning (DL) for evaluating patients with iRBD. Fifty iRBD patients, 19 with mild cognitive impairment (MCI) (RBD-MCI) and 31 without MCI (RBD-nonMCI), were prospectively enrolled. A DL model for the cognitive signature was trained by using Alzheimer's Disease Neuroimaging Initiative database and transferred to baseline [¹⁸F]FDG PET from the iRBD cohort. The results showed that the DL-based cognitive dysfunction score was significantly higher in RBD-MCI than in RBD-nonMCI. The AUC of ROC curve for differentiating RBD-MCI from RBD-nonMCI was 0.70 (95% CI 0.56-0.82). The baseline DL-based cognitive dysfunction score was significantly higher in iRBD patients who showed a decrease in CERAD scores during 2 years than in those who did not. Brain metabolic features related to cognitive dysfunction-related regions of individual iRBD patients mainly included posterior cortical regions. This work demonstrates that the cognitive signature based on DL could be used to objectively evaluate cognitive function in iRBD. We suggest that this approach could be extended to an objective biomarker predicting cognitive decline and neurodegeneration in iRBD.

Management of psychiatric and cognitive complications in Parkinson's disease

Neuropsychiatric symptoms (NPSs) such as affective disorders, psychosis, behavioral changes, and cognitive impairment are common in Parkinson's disease (PD). However, NPSs remain under-recognized and under-treated, often leading to adverse outcomes. Their epidemiology, presentation, risk factors, neural substrate, and management strategies are incompletely understood. While psychological and psychosocial factors may contribute, hallmark PD neuropathophysiological changes, plus the associations between exposure to dopaminergic medications and occurrence of some symptoms, suggest a neurobiological basis for many NPSs. A range of psychotropic medications, psychotherapeutic techniques, stimulation therapies, and other non-pharmacological treatments have been studied, are used clinically, and are beneficial for managing NPSs in PD. Appropriate management of NPSs is critical for comprehensive PD care, from recognizing their presentations and timing throughout the disease course, to the incorporation of different therapeutic strategies (ie, pharmacological and non-pharmacological) that utilize a multidisciplinary approach.

Recent Investigations on the Functional Role of Cerebellar Neural Networks in Motor Functions & Nonmotor Functions -Neurodegeneration

The cerebellum is a well-established primary brain center in charge of controlling sensorimotor functions and non-motor functions. Recent reports depicted the significance of cerebellum in higher-order cognitive functions, including emotion-processing, language, reward-related behavior, working memory, and social behavior. As it can influence diverse behavioral patterns, any defects in cerebellar functions could invoke neuropsychiatric diseases as indicated by the incidence of alexithymia and induce alterations in emotional and behavioral patterns. Furthermore, its defects can trigger motor diseases, such as ataxia and Parkinson's disease (PD). In this review, we have extensively discussed the role of cerebellum in motor and non-motor functions and how the cerebellum malfunctions in relation to the neural circuit wiring as it could impact brain function and behavioral outcomes in patients with neuropsychiatric diseases. Relevant data regarding cerebellar non-motor functions have been vividly described, along with anatomy and physiology of these functions. In addition to the defects in basal ganglia, the lack of activity in motor related regions of the cerebellum could be associated with the severity of motor symptoms. All together, this review delineates the importance of cerebellar involvement in patients with PD and unravels a crucial link for various clinical aspects of PD with specific cerebellar sub-regions.

Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.

Neurobiological effects of deep brain stimulation: A systematic review of molecular brain imaging studies

Deep brain stimulation (DBS) is an established treatment for several brain disorders, including Parkinson's disease, essential tremor, dystonia and epilepsy, and an emerging therapeutic tool in many other neurological and psychiatric disorders. The therapeutic efficacy of DBS is dependent on the stimulation target, but its mechanisms of action are still relatively poorly understood. Investigating these mechanisms is challenging, partly because the stimulation devices and electrodes have limited the use of functional MRI in these patients. Molecular brain imaging techniques, such as positron emission tomography (PET) and single photon emission tomography (SPET), offer a unique opportunity to characterize the whole brain effects of DBS. Here, we investigated the direct effects of DBS by systematically reviewing studies performing an `on' vs `off' contrast during PET or SPET imaging. We identified 62 studies (56 PET and 6 SPET studies; 531 subjects). Approximately half of the studies focused on cerebral blood flow or glucose metabolism in patients Parkinson's disease undergoing subthalamic DBS (25 studies, n = 289), therefore Activation Likelihood Estimation analysis was performed on these studies. Across disorders and stimulation targets, DBS was associated with a robust local increase in ligand uptake at the stimulation site and target-specific remote network effects. Subthalamic nucleus stimulation in Parkinson's disease showed a specific pattern of changes in the motor circuit, including increased ligand uptake in the basal ganglia, and decreased ligand uptake in the primary motor cortex, supplementary motor area and cerebellum. However, there was only a handful of studies investigating other brain disorder and stimulation site combinations (1-3 studies each), or specific neurotransmitter systems, preventing definitive conclusions of the detailed molecular effects of the stimulation in these cases.

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.

Metabolic brain pattern in dementia with Lewy bodies: Relationship to Alzheimer's disease topography

PURPOSE

Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia, that shares clinical and metabolic similarities with both Alzheimer's and Parkinson's disease. In this study we aimed to identify a DLB-related pattern (DLBRP), study its relationship with other metabolic brain patterns and explore its diagnostic and prognostic value.

METHODS

A cohort of 79 participants with DLB, 63 with dementia due to Alzheimer's disease (AD) and 41 normal controls (NCs) and their 2-[¹⁸F]FDG PET scans were analysed for identification and validation of DLBRP. Voxel-wise correlation and multiple linear regression were used to study the relation between DLBRP and Alzheimer's disease-related pattern (ADRP), Parkinson's disease-related pattern (PDRP) and PD-related cognitive pattern (PDCP). Diagnostic and prognostic value of DLBRP and of modified DLBRP after accounting for ADRP overlap (DLBRP ⊥ ADRP), were explored.

RESULTS

The newly identified DLBRP shared topographic similarities with ADRP (R² = 24%) and PDRP (R² = 37%), but not with PDCP. We could accurately discriminate between DLB and NC (AUC = 0.99) based on DLBRP expression, and between DLB and AD (AUC = 0.87) based on DLBRP ⊥ ADRP expression. DLBRP expression correlated with cognitive impairment, but the correlation was lost after accounting for ADRP overlap. DLBRP and DLBRP ⊥ ADRP correlated with patients' survival time.

CONCLUSION

DLBRP has proven to be a specific metabolic brain biomarker of DLB, sharing similarities with ADRP and PDRP, but not PDCP. We observed a similar metabolic mechanism underlying cognitive impairment in DLB and AD. DLB-specific metabolic changes were more detrimental for overall survival.

Action and emotion perception in Parkinson's disease: A neuroimaging meta-analysis

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The neural substrates for action and emotion perception deficits in PD are still unclear.

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We addressed this issue via coordinate-based meta-analyses of previous fMRI data.

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PD patients exhibit decreased response in the basal ganglia.

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PD patients exhibit a trend toward decreased response in the parietal areas.

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PD patients exhibit a trend toward increased activation in the posterior cerebellum.

Patients with Parkinson disease (PD) may show impairments in the social perception. Whether these deficits have been consistently reported, it remains to be clarified which brain alterations subtend them. To this aim, we conducted a neuroimaging meta-analysis to compare the brain activity during social perception in patients with PD versus healthy controls. Our results show that PD patients exhibit a significantly decreased response in the basal ganglia (putamen and pallidum) and a trend toward decreased activity in the mirror system, particularly in the left parietal cortex (inferior parietal lobule and intraparietal sulcus). This reduced activation may be tied to a disruption of cognitive resonance mechanisms and may thus constitute the basis of impaired others’ representations underlying action and emotion perception. We also found increased activation in the posterior cerebellum in PD, although only in a within-group analysis and not in comparison with healthy controls. This cerebellar activation may reflect compensatory mechanisms, an aspect that deserves further investigation. We discuss the clinical implications of our findings for the development of novel social skill training programs for PD patients.

Gait‐Related Metabolic Covariance Networks at Rest in Parkinson's Disease

Background

Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted.

Objective

The aim of this study was to identify neural networks of discrete gait impairments in PD.

Methods

Fifty‐five participants with early‐stage PD and 20 age‐matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [¹⁸F]‐2‐fluoro‐2‐deoxyglucose‐positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD.

Results

In PD, we identified two metabolic gait‐related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity.

Conclusions

We have identified two novel gait‐related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Neuroimaging approaches to cognition in Parkinson's disease

While direct visualization of Lewy body accumulation within the brain is not yet possible in living Parkinson's disease patients, brain imaging studies offer insights into how the buildup of Lewy body pathology impacts different regions of the brain. Unlike biological biomarkers and purely behavioral research, these brain imaging studies therefore offer a unique opportunity to relate brain localization to cognitive function and dysfunction in living patients. Magnetic resonance imaging studies can reveal physical changes in brain structure as they relate to different cognitive domains and task specific impairments. Functional imaging studies use a combination of task and resting state magnetic resonance imaging, as well as positron emission tomography and single photon emission computed tomography, and can be used to determine changes in blood flow, neuronal activation and neurochemical changes in the brain associated with PD cognition and cognitive impairments. Other unique advantages to brain imaging studies are the ability to monitor changes in brain structure and function longitudinally as patients progress and the ability to study changes in brain function when patients are exposed to different pharmacological manipulations. This is particularly true when assessing the effects of dopaminergic replacement therapy on cognitive function in Parkinson's disease patients. Together, this chapter will describe imaging studies that have helped identify structural and functional brain changes associated with cognition, cognitive impairment, and dementia in Parkinson's disease.

Metabolic imaging and plasticity

Positron emission tomography greatly advanced our understanding on the underlying neural mechanisms of movement disorders. PET with flurodeoxyglucose (FDG) is especially useful as it depicts regional metabolic activity level that can predict patients' symptoms. Multivariate pattern analysis has been used to determine and quantify the co-varying brain networks associated with specific clinical traits of neurodegenerative disease. The result is a biomarker, useful for diagnosis, treatments, and follow up studies. Parkinsonian traits and parkinsonisms are associated with specific spatial pattern of metabolic abnormality useful for differential diagnosis. This approach has also been used for monitoring disease progression and novel treatment responses mostly in Parkinson's disease. In this book chapter, we, illustrate and discuss the significance of the brain networks associated with disease and their modification with neuroplastic changes.

The Role of Monoaminergic Tones and Brain Metabolism in Cognition in De Novo Parkinson's Disease

BACKGROUND

Cognitive impairment is frequent in Parkinson's disease (PD) and several neurotransmitter changes have been reported since the time of diagnosis, although seldom investigated altogether in the same patient cohort.

OBJECTIVE

Our aim was to evaluate the association between neurotransmitter impairment, brain metabolism, and cognition in a cohort of de novo, drug-naïve PD patients.

METHODS

We retrospectively selected 95 consecutive drug-naïve PD patients (mean age 71.89±7.53) undergoing at the time of diagnosis a brain [18F]FDG-PET as a marker of brain glucose metabolism and proxy measure of neurodegeneration, [123I]FP-CIT-SPECT as a marker and dopaminergic deafferentation in the striatum and frontal cortex, as well as a marker of serotonergic deafferentation in the thalamus, and quantitative electroencephalography (qEEG) as an indirect measure of cholinergic deafferentation. Patients also underwent a complete neuropsychological battery.

RESULTS

Positive correlations were observed between (i) executive functions and left cerebellar cortex metabolism, (ii) prefrontal dopaminergic tone and working memory (r = 0.304, p = 0.003), (iii) qEEG slowing in the posterior leads and both memory (r = 0.299, p = 0.004) and visuo-spatial functions (r = 0.357, p < 0.001).

CONCLUSIONS

In subjects with PD, the impact of regional metabolism and diffuse projection systems degeneration differs across cognitive domains. These findings suggest possible tailored approaches to the treatment of cognitive deficits in PD.