Posterior parietooccipital hypometabolism may differentiate mild cognitive impairment from dementia in Parkinson's disease

[Clinical and neuropsychological features and changes to regional cerebral blood flow in ‍patients with Parkinson's disease dementia]

This study aimed to clarify associations of clinical and neuropsychological features and change in regional cerebral blood flow (rCBF) on 123I-IMP-SPECT in patients with Parkinson's disease (PD) who developed dementia. Sixty-one PD patients (mean age, 65.9 ± 8.6 years; mean disease duration, 11.0 ± 11.0 years) were recruited and followed-up for two years. Clinical and neuropsychological characteristics, and rCBF from SPECT were compared between PD patients who developed dementia (PDD+) and those who remained undemented (PDD-). Thirty-eight PD patients (62.3%) were diagnosed with PD-MCI at baseline. During follow-up, 22 PD patients (36%) developed dementia (PDD+). Univariate logistic regression models showed that Hoehn and Yahr scale 4 (odds ratio [OR] 5.85; 95% confidence interval [CI] 1.35-30.75]), visual hallucination (OR 5.95; 95%CI 1.67-25.4]), and PD-MCI (OR 6.47; 95%CI 1.57-39.63]) represented a significant risk factor for PDD+. Among neuropsychological parameters, WAIS (Wechsler Adult Intelligence Scale)-III block design (OR 6.55; 95%CI 1.66-29.84), letter number sequencing (OR 7.01; 95%CI 1.65-36.64), digit-symbol coding (OR 3.90; 95%CI 1.13-14.2), Wechsler Memory Scale, revised (WMS-R) visual paired associates II (delayed recall) (OR 4.68; 95%CI 1.36-17.36), Logical memory I (immediate recall) (OR 8.30; 95%CI 1.37-90.89), Logical memory II (delayed recall) (OR 6.61; 95%CI 1.35-44.33), Visual reproduction I (immediate recall) (OR 7.67; 95%CI 2.11-31.40), and Visual reproduction II (delayed recall) (OR 5.64; 95%CI 1.62-21.47) were significant risk factors. Decreased rCBF assessed using the general linear model (two-sample t-test) by SPM8 was observed in the left precuneus (0, -66, 16), right cuneus (6, -76, 30), and left angular gyrus (-46, -74, 32) in PDD+ compared with PDD- patients. Collectively, we have here shown that clinical and neuropsychological characteristics as well as changes to rCBF in PD patients who converted to PDD+. These features should be carefully monitored to detect the development of dementia in PD patients.

Structure-function coupling in macroscale human brain networks

Precisely how the anatomical structure of the brain gives rise to a repertoire of complex functions remains incompletely understood. A promising manifestation of this mapping from structure to function is the dependency of the functional activity of a brain region on the underlying white matter architecture. Here, we review the literature examining the macroscale coupling between structural and functional connectivity, and we establish how this structure-function coupling (SFC) can provide more information about the underlying workings of the brain than either feature alone. We begin by defining SFC and describing the computational methods used to quantify it. We then review empirical studies that examine the heterogeneous expression of SFC across different brain regions, among individuals, in the context of the cognitive task being performed, and over time, as well as its role in fostering flexible cognition. Last, we investigate how the coupling between structure and function is affected in neurological and psychiatric conditions, and we report how aberrant SFC is associated with disease duration and disease-specific cognitive impairment. By elucidating how the dynamic relationship between the structure and function of the brain is altered in the presence of neurological and psychiatric conditions, we aim to not only further our understanding of their aetiology but also establish SFC as a new and sensitive marker of disease symptomatology and cognitive performance. Overall, this Review collates the current knowledge regarding the regional interdependency between the macroscale structure and function of the human brain in both neurotypical and neuroatypical individuals.

Intracerebral hemodynamic abnormalities in patients with Parkinson's disease: Comparison between multi-delay arterial spin labelling and conventional single-delay arterial spin labelling

PURPOSE

The purpose of this study was to analyze the intracerebral abnormalities of hemodynamics in patients with Parkinson's disease (PD) through arterial spin labelling (ASL) technique with multi-delay ASL (MDASL) and conventional single-delay ASL (SDASL) protocols and to verify the potential clinical application of these features for the diagnosis of PD.

MATERIALS AND METHODS

Perfusion data of the brain obtained using MDASL and SDASL in patients with PD were compared to those obtained in healthy control (HC) subjects. Intergroup comparisons of z-scored cerebral blood flow (zCBF), arterial transit time (zATT) and cerebral blood volume (zCBV) were performed via voxel-based analysis. Performance of these perfusion metrics were estimated using area under the receiver operating characteristic curve (AUC) and compared using Delong test.

RESULTS

A total of 47 patients with PD (29 men; 18 women; mean age, 69.0 ± 7.6 (standard deviation, [SD]) years; range: 50.0-84.0 years) and 50 HC subjects (28 men; 22 women; mean age, 70.1 ± 6.2 [SD] years; range: 50.0-93.0 years) were included. Relative to the uncorrected-zCBF map, the corrected-zCBF map further refined the distributed brain regions in the PD group versus the HC group, manifested as the extension of motor-related regions (PFWE < 0.001). Compared to the HC subjects, patients with PD had elevated zATT and zCBV in the right putamen, a shortened zATT in the superior frontal gyrus, and specific zCBV variations in the left precuneus and the right supplementary motor area (PFWE < 0.001). The corrected-zCBF (AUC, 0.90; 95% confidence interval [CI]: 0.84-0.96) showed better classification performance than uncorrected-zCBF (AUC, 0.84; 95% CI: 0.75-0.92) (P = 0.035). zCBV achieved an AUC of 0.89 (95% CI: 0.82-0.96) and zATT achieved an AUC of 0.66 (95% CI: 0.55-0.77). The integration model of hemodynamic features from MDASL provided improved performance (AUC, 0.97; 95% CI: 0.95-0.98) for the diagnosis of PD by comparison with each perfusion model (P < 0.001).

CONCLUSION

ASL identifies impaired hemodynamics in patients with PD including regional abnormalities of CBF, CBV and ATT, which can better be mapped with MDASL compared to SDASL. These findings provide complementary depictions of perfusion abnormalities in patients with PD and highlight the clinical feasibility of MDASL.

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.

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.

A crazy trio in Parkinson's disease: metabolism alteration, α-synuclein aggregation, and oxidative stress

Parkinson's disease (PD) is an aging-associated neurodegenerative disorder, characterized by the progressive loss of dopaminergic neurons in the pars compacta of the substantia nigra and the presence of Lewy bodies containing α-synuclein within these neurons. Oligomeric α-synuclein exerts neurotoxic effects through mitochondrial dysfunction, glial cell inflammatory response, lysosomal dysfunction and so on. α-synuclein aggregation, often accompanied by oxidative stress, is generally considered to be a key factor in PD pathology. At present, emerging evidences suggest that metabolism alteration is closely associated with α-synuclein aggregation and PD progression, and improvement of key molecules in metabolism might be potentially beneficial in PD treatment. In this review, we highlight the tripartite relationship among metabolic changes, α-synuclein aggregation, and oxidative stress in PD, and offer updated insights into the treatments of PD, aiming to deepen our understanding of PD pathogenesis and explore new therapeutic strategies for the disease.

GLP-1 Receptor Agonists: A New Treatment in Parkinson's Disease

Parkinson's disease (PD) is one of the most common neurodegenerative diseases. Recent data highlight similarities between neurodegenerative diseases, including PD and type 2 diabetes mellitus (T2DM), suggesting a crucial interplay between the gut-brain axis. Glucagon-like peptide-1 receptor (GLP-1R) agonists, known for their use in T2DM treatment, are currently extensively studied as novel PD modifying agents. For this narrative review article, we searched PubMed and Scopus databases for peer-reviewed research, review articles and clinical trials regarding GLP-1R agonists and PD published in the English language with no time restrictions. We also screened the references of the selected articles for possible additional articles in order to include most of the key recent evidence. Many data on animal models and preclinical studies show that GLP1-R agonists can restore dopamine levels, inhibit dopaminergic loss, attenuate neuronal degeneration and alleviate motor and non-motor features of PD. Evidence from clinical studies is also very promising, enhancing the possibility of adding GLP1-R agonists to the current armamentarium of drugs available for PD treatment.

Subspace corrected relevance learning with application in neuroimaging

In machine learning, data often comes from different sources, but combining them can introduce extraneous variation that affects both generalization and interpretability. For example, we investigate the classification of neurodegenerative diseases using FDG-PET data collected from multiple neuroimaging centers. However, data collected at different centers introduces unwanted variation due to differences in scanners, scanning protocols, and processing methods. To address this issue, we propose a two-step approach to limit the influence of center-dependent variation on the classification of healthy controls and early vs. late-stage Parkinson's disease patients. First, we train a Generalized Matrix Learning Vector Quantization (GMLVQ) model on healthy control data to identify a "relevance space" that distinguishes between centers. Second, we use this space to construct a correction matrix that restricts a second GMLVQ system's training on the diagnostic problem. We evaluate the effectiveness of this approach on the real-world multi-center datasets and simulated artificial dataset. Our results demonstrate that the approach produces machine learning systems with reduced bias - being more specific due to eliminating information related to center differences during the training process - and more informative relevance profiles that can be interpreted by medical experts. This method can be adapted to similar problems outside the neuroimaging domain, as long as an appropriate "relevance space" can be identified to construct the correction matrix.

Cognitive Reserve in Parkinson's Disease without Dementia: β-Amyloid and Metabolic Assessment

BACKGROUND

Cognitive reserve (CR) is the mismatch between preserved cognition and neuropathological damage. Amyloidopathy in Parkinson's disease (PD) could be associated with faster progression to dementia, but the putative protective effect of CR is unknown.

OBJECTIVES

To evaluate the effect of CR on β-amyloid burden and brain metabolism in non-demented PD subjects.

METHODS

Participants with PD (n = 53) underwent a clinical evaluation, [18 F]-fluorodeoxyglucose and [18 F]-flutemetamol positron emission tomography magnetic resonances, and were classified according to CR. The metabolic pattern of 16 controls was compared to PD subjects.

RESULTS

The PD subjects showed hypometabolism mainly in the bilateral posterior cortex. Superior-CR subjects (n = 22) exhibited better cognitive performance, increased amyloid burden, and higher metabolism in several right hemisphere areas compared to low-medium-CR subjects (n = 31).

CONCLUSIONS

Higher CR in non-demented PD is associated with better cognitive performance, which might reduce vulnerability to the effect of β-amyloid. Whether superior CR leads to protection against metabolic deterioration, and predominantly right hemisphere involvement, deserves further exploration.

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.

Decreased beta-band activity in left supramarginal gyrus reflects cognitive decline: Evidence from a large clinical dataset in patients with dementia

Cognitive impairment is a major concern in clinical medicine. It is usually evaluated with neuropsychological assessments, which have inherent limitations. To compensate for them, magnetoencephalography has already come into clinical use to evaluate the level of cognitive impairment. It evaluates global changes in the frequency of resting-state brain activity, which are associated with cognitive status. However, it remains unclear what neural mechanism causes the frequency changes. To understand this, it is important to identify cortical regions that mainly contribute to these changes. We retrospectively analysed the clinical records from 310 individuals with cognitive impairment who visited the outpatient department at our hospital. The analysis included resting-state magnetoencephalography, neuropsychological assessment, and clinical diagnosis data. Regional oscillatory intensities were estimated from the magnetoencephalography data, which were statistically analysed, along with neuropsychological assessment scores, and the severity of cognitive impairment associated with clinical diagnosis. The regional oscillatory intensity covering a wide range of regions and frequencies was significantly associated with neuropsychological assessment scores and differed between healthy individuals and patients with cognitive impairment. However, these associations and differences in all conditions were overlapped by a single change in beta frequency in the left supramarginal gyrus. High frequency oscillatory intensity in the left supramarginal gyrus is associated with cognitive impairment levels among patients who were concerned about dementia. It provides new insights into cognitive status measurements using magnetoencephalography, which is expected to develop as an objective index to be used alongside traditional neuropsychological assessments.

Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex

Recent work has demonstrated that the relationship between structural and functional connectivity varies regionally across the human brain, with reduced coupling emerging along the sensory-association cortical hierarchy. The biological underpinnings driving this expression, however, remain largely unknown. Here, we postulate that intracortical myelination and excitation-inhibition (EI) balance mediate the heterogeneous expression of structure-function coupling (SFC) and its temporal variance across the cortical hierarchy. We employ atlas- and voxel-based connectivity approaches to analyze neuroimaging data acquired from two groups of healthy participants. Our findings are consistent across six complementary processing pipelines: 1) SFC and its temporal variance respectively decrease and increase across the unimodal-transmodal and granular-agranular gradients; 2) increased myelination and lower EI-ratio are associated with more rigid SFC and restricted moment-to-moment SFC fluctuations; 3) a gradual shift from EI-ratio to myelination as the principal predictor of SFC occurs when traversing from granular to agranular cortical regions. Collectively, our work delivers a framework to conceptualize structure-function relationships in the human brain, paving the way for an improved understanding of how demyelination and/or EI-imbalances induce reorganization in brain disorders.

A comparative study of posterior cingulate metabolism in patients with mild cognitive impairment due to Parkinson's disease or Alzheimer's disease

Few comparative studies have assessed metabolic brain changes in cognitive impairment among neurodegenerative disorders, and the posterior cingulate cortex (PCC) is a metabolically active brain region with high involvement in multiple cognitive processes. Therefore, in this study, metabolic abnormalities of the PCC were compared in patients with mild cognitive impairment (MCI) due to Parkinson's disease (PD) or Alzheimer's disease (AD), as examined by proton magnetic resonance spectroscopy (1H-MRS). Thirty-eight patients with idiopathic PD, including 20 with mild cognitive impairment (PDMCI) and 18 with normal cognitive function (PDN), 18 patients with probable mild cognitive impairment (ADMCI), and 25 healthy elderly controls (HCs) were recruited and underwent PCC 1H-MRS scans. Compared with HCs, patients with PDMCI exhibited significantly reduced concentrations of N-acetyl aspartate (NAA), total NAA (tNAA), choline (Cho), glutathione (GSH), glutamate + glutamine (Glx) and total creatine (tCr), while ADMCI cases exhibited significantly elevated levels of myo-inositol (Ins) and Ins/tCr ratio, as well as reduced NAA/Ins ratio. No significant metabolic changes were detected in PDN subjects. Compared with ADMCI, reduced NAA, Ins and tCr concentrations were detected in PDMCI. Besides, ROC curve analysis revealed that tCr concentration could differentiate PDMCI from PDN with an AUC of 0.71, and NAA/Ins ratio could differentiate patients with MCI from controls with normal cognitive function with an AUC of 0.74. Patients with PDMCI and ADMCI exhibited distinct PCC metabolic 1H-MRS profiles. The findings suggested cognitively normal PD patients with low NAA and tCr in the PCC might be at risk of preclinical PDMCI, and Ins and/or NAA/MI ratio in the PCC should be reconsidered a possible biomarker of preclinical MCI in clinical practice. So, comparing PCC's 1H-MRS profiles of cognitive impairment among neurodegenerative illnesses may provide useful information for better defining the disease process and elucidate possible treatment mechanisms.

Videofluoroscopic Swallowing Study Features and Resting-State Functional MRI Brain Activity for Assessing Swallowing Differences in Patients with Mild Cognitive Impairment and Risk of Dysphagia

To examine the swallowing characteristics in patients with mild cognitive impairment (MCI) and dysphagia risk and explore brain activity changes using regional homogeneity (ReHo) with resting-state functional magnetic resonance imaging (rs-fMRI). We included 28 patients with MCI and dysphagia risk and 17 age-matched older adults. All participants underwent neurological, cognitive examinations, and a videofluoroscopic swallowing study (VFSS). We quantitatively analyzed the VFSS temporal and kinetic parameters of the 5- and 10-mL swallows. The participants underwent rs-fMRI, and the ReHo values were calculated. Differences in the swallowing physiology and rs-fMRI findings between participants with MCI and controls were analyzed. Correlation analyses were also conducted. Compared to the control group, patients with MCI and dysphagia risk had lower global cognition scores, longer 10-mL oral transit times (OTTs), and lower executive function scores. ReHo in the bilateral inferior occipital lobes (IOLs) and left prefrontal lobe decreased in patients with MCI and dysphagia risk compared to participants in the control group. In patients with MCI, the 10-mL OTT was negatively correlated with the Montreal Cognitive Assessment (MoCA) score, and the ReHo values were positive correlated with quantitative temporal swallowing measurements using canonical correlation analysis. Mediation analysis revealed that the ReHo values of the left and right IOL acted as significant mediators between the MoCA score and the 10-mL OTT. We found that individuals with MCI and dysphagia risk, verified by reduced MoCA scores, demonstrated prolonged OTTs when swallowing larger boluses compared with age-matched controls. There was a negative correlation between the MoCA score and 10-mL OTT, which was partially mediated by the left and right IOL ReHo values, suggesting that functional changes in the IOLs and left prefrontal lobe associated with oral swallowing status and cognitive level in individuals with MCI and dysphagia risk.

Differences in Striatal Metabolism in [18F]FDG PET in Parkinson's Disease and Atypical Parkinsonism

Neurodegenerative parkinsonisms affect mainly cognitive and motor functions and are syndromes of overlapping symptoms and clinical manifestations such as tremor, rigidness, and bradykinesia. These include idiopathic Parkinson's disease (PD) and the atypical parkinsonisms, namely progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA) and dementia with Lewy body (DLB). Differences in the striatal metabolism among these syndromes are evaluated using [18F]FDG PET, caused by alterations to the dopaminergic activity and neuronal loss. A study cohort of three patients with PD, 29 with atypical parkinsonism (10 PSP, 6 CBD, 2 MSA, 7 DLB, and 4 non-classifiable), and a control group of 25 patients with normal striatal metabolism is available. Standardized uptake value ratios (SUVR) are extracted from the striatum, and the caudate and the putamen separately. SUVRs are compared among the study groups. In addition, hemispherical and caudate-putamen differences are evaluated in atypical parkinsonisms. Striatal hypermetabolism is detected in patients with PD, while atypical parkinsonisms show hypometabolism, compared to the control group. Hemispherical differences are observed in CBD, MSA and DLB, with the latter also showing statistically significant caudate-putamen asymmetry (p = 0.018). These results indicate disease-specific metabolic uptake patterns in the striatum that can support the differential diagnosis.

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

BACKGROUND AND OBJECTIVES

¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson's disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory.

METHODS

We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories.

RESULTS

The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman's rho =0.62, P=0.004).

CONCLUSION

In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages.

[Neuropsychological and regional cerebral blood flow of posterior parietal area features in patients with Parkinson's disease with mild cognitive impairment]

This study aimed to clarify associations between neuropsychological scales and regional cerebral blood flow (rCBF) of on ‍¹²³I-IMP-SPECT in patients with Parkinson's disease with mild cognitive impairment (PD-MCI). Forty-two participants (mean age, 65.5 ± 8.9 years; mean disease duration, 11.1 ±5.7 years) were evaluated using the Wechsler Adult Intelligence Scale, third edition (WAIS-III), Wechsler Memory Scale, revised (WMS-R), Stroop test, Category word fluency, Auditory verbal learning test, Raven colored progressive matrices, Trail Making Test-B, and Clock drawing test. Participants were classified into PD-MCI and PD non-demented (PD-ND) using ten of these scales or its subtests. The rCBF of the posterior cingulate gyrus, precuneus, and parietal lobes was evaluated by ‍¹²³I-IMP-SPECT using the easy Z-‍score imaging system (eZIS analysis). Extent was the extent index of voxels showing z-score > 2, and Severity was mean z-score in those regions on eZIS analysis. Cingulate island sign score (CIScore) was the ratio of integrated z-scores of the posterior cingulate gyrus to those of the posterior cortex.Twenty-three participants were diagnosed with PD-MCI (55%). The rCBF indices were significantly increased in the PD-MCI group compared to the PD-ND group (Extent: P = 0.047; CIScore: P = 0.006). These indices were significantly correlated with WAIS-III Processing Speed (Extent: P = 0.041, R = -0.317; Severity: P = 0.047, R = -0.309), Stroop effect (Extent: P = 0.003, R = 0.443; Severity: P = 0.004, R = 0.437), WMS-R Visual memory (Extent: P = 0.019, R = -0.361; Severity: P = 0.014, R = -0.375), and Delayed memory score (Extent: P = 0.005, R = -0.423; Severity: P = 0.044, R = -0.312). The rCBF indices showed no correlations with the number of impaired cognitive domains. Collectively, decreased posterior parietal area rCBF and lower scores on selective neuropsychological scales might be helpful to detect a transition period from PD-MCI to PD-D.

Therapeutic application of GLP-1 and GIP receptor agonists in Parkinson's disease

INTRODUCTION

Diabetes is a risk factor for Parkinson's disease (PD) and shares similar dysregulated insulin pathways. Glucagon-like peptide-1 (GLP-1) analogs originally designed to treat diabetes have shown potent neuroprotective activity in preclinical studies of PD. They are neuroprotective by inhibiting inflammation, improving neuronal survival, maintenance of synapses, and dopaminergic transmission in the brain. Building on this, three clinical studies have reported impressive effects in patients with PD, testing exendin-4 (Exenatide, Bydureon) or liraglutide (Victoza, Saxenda). Glucose-dependent insulinotropic peptide (GIP) is another peptide hormone that has shown good effects in animal models of PD. Novel dual GLP-1/GIP agonists have been developed that can penetrate the blood-brain barrier (BBB) and show superior effects in animal models compared to GLP-1 drugs.

AREAS COVERED

The review summarizes preclinical and clinical studies testing GLP-1R agonists and dual GLP-1/GIPR agonists in PD and discusses possible mechanisms of action.

EXPERT OPINION

Current strategies to treat PD by lowering the levels of alpha-synuclein have not shown effects in clinical trials. It is time to move on from the 'misfolding protein' hypothesis. Growth factors such as GLP-1 that can cross the BBB have already shown impressive effects in patients and are the future of drug discovery in PD.

Neural correlates and predictors of subjective cognitive decline in patients with Parkinson's disease

BACKGROUND

Subjective cognitive decline (SCD) may occur very early in the course of Parkinson's disease (PD) before the onset of objective cognitive decline. Data on neural correlates and determinants of SCD in PD are rare.

OBJECTIVE

The aim of the present study was to identify neural correlates as well as sociodemographic, clinical, and neuropsychological predictors of SCD in patients with PD.

METHODS

We retrospectively analyzed 30 patients with PD without cognitive impairment (23% female, 66.90 ± 7.20 years, UPDRS-III: 19.83 ± 9.29), of which n = 12 patients were classified as having no SCD (control group, PD-CG) and n = 18 as having SCD (PD-SCD). Neuropsychological testing and 18-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) were conducted. SCD was assessed using a questionnaire covering multiple cognitive domains.

RESULTS

SCD subscores differed significantly between PD-CG and PD-SCD and correlated significantly with other scales measuring related concepts. FDG-PET whole-brain voxel-wise regression analysis revealed hypometabolism in middle frontal, middle temporal, and occipital areas, and the angular gyrus as neural correlates of SCD in PD. Next to this hypometabolism, depressive symptoms were an independent significant determinant of SCD in a stepwise regression analysis (adjusted R2 = 50.3%).

CONCLUSION

This study strengthens the hypothesis of SCD being an early manifestation of future cognitive decline in PD and, more generally, early pathological changes in PD. The early identification of the vulnerability for future cognitive decline constitutes the basis for successful prevention and delay of this non-motor symptom.

Effects of Exercise on Parkinson’s Disease: A Meta-Analysis of Brain Imaging Studies

Background

Exercise is increasingly recognized as a key component of Parkinson’s disease (PD) treatment strategies, but the underlying mechanism of how exercise affects PD is not yet fully understood.

Objective

The activation likelihood estimation (ALE) method is used to study the mechanism of exercise affecting PD, providing a theoretical basis for studying exercise and PD, and promoting the health of patients with PD.

Methods

Relevant keywords were searched on the PubMed, Cochrane Library, and Web of Science databases. Seven articles were finally included according to the screening criteria, with a total sample size of 97 individuals. Using the GingerALE 3.0.2 software, an ALE meta-analysis was performed using seven studies that met the requirements, and the probability of the cross-experiment activation of each voxel was calculated.

Results

The meta-analysis produced seven clusters, and major activations were found in the cerebellum, occipital lobe, parietal lobe, and frontal lobe brain regions.

Conclusion

Exercise for PD mainly results in the enhanced activation of the cerebellum, occipital lobe, parietal lobe, and frontal lobe. Exercise for PD does not cause a change in the activation of a single brain area, and the observed improvement may result from coordinated changes in multiple brain areas.

Metabolic Features of Brain Function with Relevance to Clinical Features of Alzheimer and Parkinson Diseases

Brain metabolism is comprised in Alzheimer’s disease (AD) and Parkinson’s disease (PD). Since the brain primarily relies on metabolism of glucose, ketone bodies, and amino acids, aspects of these metabolic processes in these disorders—and particularly how these altered metabolic processes are related to oxidative and/or nitrosative stress and the resulting damaged targets—are reviewed in this paper. Greater understanding of the decreased functions in brain metabolism in AD and PD is posited to lead to potentially important therapeutic strategies to address both of these disorders, which cause relatively long-lasting decreased quality of life in patients.

Impact of Visual Impairment on Vision-Related Quality of Life in Parkinson's Disease

BACKGROUND

Visual impairment is frequent and highly disabling in Parkinson's disease (PD); however, few studies have comprehensively evaluated its impact on vision-related quality of life.

OBJECTIVE

To evaluate the relationship between visual function tests and the visual impairment perceived by PD patients in daily living activities.

METHODS

We cross-sectionally evaluated 62 PD patients and 33 healthy controls (HC). Visual disability was measured with a comprehensive battery of primary visual function and visual cognition tests (visual outcomes), and vision-related quality of life was evaluated with the National Eye Institute 25-Item Visual Function Questionnaire (NEI VFQ-25). The relationship between visual outcomes and NEI VFQ-25 sub-scores was analyzed with Pearson's correlations and stepwise linear regression.

RESULTS

In PD patients, and not in HC, most NEI VFQ-25 sub-scores were significantly correlated with Cube Analysis and Dot Counting from Visual Object and Space Perception (VOSP) battery (visual perception), Clock Drawing Test (visuoconstructive capacity) and Trail Making Test part-A (visual attention and processing speed) and to a lesser extent with high- and low-contrast visual acuity. Dot Counting (VOSP) was the test primarily associated with most NEI VFQ-25 sub-scores (5 out of 12). Roth-28 color test was the one that best explained the variance of Peripheral Vision (R2: 0.21) and Role Difficulties (R2: 0.36) sub-scores of NEI VFQ-25, while photopic contrast sensitivity explained 41% of Driving sub-score variance.

CONCLUSION

Vision-related quality of life in PD is mainly influenced by alterations in visual perception, visuoconstructive capacity and visual attention and processing speed. Future studies are warranted to confirm and further extend our findings.

Imaging Cognitive Impairment and Impulse Control Disorders in Parkinson's Disease

Dementia and mild forms of cognitive impairment as well as neuropsychiatric symptoms (i. e., impulse control disorders) are frequent and disabling non-motor symptoms of Parkinson's disease (PD). The identification of changes in neuroimaging studies for the early diagnosis and monitoring of the cognitive and neuropsychiatric symptoms associated with Parkinson's disease, as well as their pathophysiological understanding, are critical for the development of an optimal therapeutic approach. In the current literature review, we present an update on the latest structural and functional neuroimaging findings, including high magnetic field resonance and radionuclide imaging, assessing cognitive dysfunction and impulse control disorders in PD.

Detection of visual and frontoparietal network perfusion deficits in Parkinson's disease dementia

Mild cognitive impairment of Parkinson's disease (PD) may be an early manifestation that may progressively worsen to dementia. Cognitive decline has been associated with changes in the brain perfusion pattern. This study aimed to evaluate cerebral blood flow (CBF) deficits specific to different stages of cognitive decline. Seventeen patients with cognitively normal PD (PD-CN), 18 patients with PD with mild cognitive impairment (PD-MCI), and 16 patients with PD with dementia (PDD) were included in this study. The participants were scanned using a 3 T Philips MRI scanner. Arterial spin labelling magnetic resonance (ASL-MR) images were acquired, followed by calculation of the CBF maps, and registration onto the MNI152 brain atlas. A whole-brain voxel-based CBF comparison was performed among the patient groups using age as a covariate. The mean age of patients with PDD was significantly higher than that of patients with PD-MCI (P = 0.015) and PD-CN (P = 0.001). The CBF values of the three groups were significantly different in the left cuneus of the visual network (VN), left inferior frontal gyrus of the frontoparietal network (FPN), and left dorsomedial nucleus of the thalamus. PDD had lower perfusion values than PD-MCI group in the same regions detected in the main group analysis. Additionally, comparison of PDD with PD-CN and non-demented groups revealed that the perfusion reduction extended into the bilateral cuneus of the VN, bilateral thalami, and left inferior frontal gyrus of the FPN. PDD could be separated from PD-MCI and PD-CN stages with CBF deficits in non-dopaminergically mediated posterior and dopaminergically mediated frontal networks.

Altered microstructural properties of superficial white matter in patients with Parkinson's disease

Parkinson's disease (PD), a chronic neurodegenerative disease, is characterized by sensorimotor and cognitive deficits. Previous diffusion tensor imaging (DTI) studies found abnormal DTI metrics in white matter bundles, such as the corpus callosum, cingulate, and frontal-parietal bundles, in PD patients. These studies mainly focused on alterations in microstructural features of long-range bundles within the deep white matter (DWM) that connects pairs of distant cortical regions. However, less is known about the DTI metrics of the superficial white matter (SWM) that connects local cortical regions in PD patients. To determine whether the DTI metrics of the SWM were different between the PD patients and the healthy controls, we recruited DTI data from 34 PD patients and 29 gender- and age-matched healthy controls. Using a probabilistic tractographic approach, we first defined a population-based SWM mask across all the subjects. Using a tract-based spatial statistical (TBSS) analytic approach, we then identified the SWM bundles showing abnormal DTI metrics in the PD patients. We found that the PD patients showed significantly lower DTI metrics in the SWM bundles connecting the sensorimotor cortex, cingulate cortex, posterior parietal cortex (PPC), and parieto-occipital cortex than the healthy controls. We also found that the clinical measures in the PD patients was significantly negatively correlated with the fractional anisotropy in the SWM (FA_SWM) that connects core regions in the default mode network (DMN). The FA_SWM in the bundles that connected the PPC was significantly positively correlated with cognitive performance in the PD patients. Our findings suggest that SWM may serve as the brain structural basis underlying the sensorimotor deficits and cognitive degeneration in PD patients.

Cognition-Related Functional Topographies in Parkinson's Disease: Localized Loss of the Ventral Default Mode Network

Cognitive dysfunction in Parkinson's disease (PD) is associated with increased expression of the PD cognition-related pattern (PDCP), which overlaps with the normal default mode network (DMN). Here, we sought to determine the degree to which the former network represents loss of the latter as a manifestation of the disease process. To address this, we first analyzed metabolic images (fluorodeoxyglucose positron emission tomography [PET]) from a large PD sample with varying cognitive performance. Cognitive impairment in these patients correlated with increased PDCP expression as well as DMN loss. We next determined the spatial relationship of the 2 topographies at the subnetwork level. To this end, we analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from an independent population. This approach uncovered a significant PD cognition-related network that resembled previously identified PET- and rs-fMRI-based PDCP topographies. Further analysis revealed selective loss of the ventral DMN subnetwork (precuneus and posterior cingulate cortex) in PD, whereas the anterior and posterior components were not affected by the disease. Importantly, the PDCP also included a number of non-DMN regions such as the dorsolateral prefrontal and medial temporal cortex. The findings show that the PDCP is a reproducible cognition-related network that is topographically distinct from the normal DMN.

Impaired Structural Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment: A Study Based on Probabilistic Tractography

Background: Probabilistic tractography, in combination with graph theory, has been used to reconstruct the structural whole-brain connectome. Threshold-free network-based statistics (TFNBS) is a useful technique to study structural connectivity in neurodegenerative disorders; however, there are no previous studies using TFNBS in Parkinson's disease (PD) with and without mild cognitive impairment (MCI). Materials and Methods: Sixty-two PD patients, 27 of whom classified as PD-MCI, and 51 healthy controls (HC) underwent diffusion-weighted 3T magnetic resonance imaging. Probabilistic tractography, using FMRIB Software Library (FSL), was used to compute the number of streamlines (NOS) between regions. NOS matrices were used to find group differences with TFNBS, and to calculate global and local measures of network integrity using graph theory. A binominal logistic regression was then used to assess the discrimination between PD with and without MCI using non-overlapping significant tracts. Tract-based spatial statistics were also performed with FSL to study changes in fractional anisotropy (FA) and mean diffusivity. Results: PD-MCI showed 37 white matter connections with reduced connectivity strength compared with HC, mainly involving temporal/occipital regions. These were able to differentiate PD-MCI from PD without MCI with an area under the curve of 83-85%. PD without MCI showed disrupted connectivity in 18 connections involving frontal/temporal regions. No significant differences were found in graph measures. Only PD-MCI showed reduced FA compared with HC. Discussion: TFNBS based on whole-brain probabilistic tractography can detect structural connectivity alterations in PD with and without MCI. Reduced structural connectivity in fronto-striatal and posterior cortico-cortical connections is associated with PD-MCI.

Brain Molecular Connectivity in Neurodegenerative Conditions

Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

Blood-brain barrier opening with focused ultrasound in Parkinson's disease dementia

MR-guided focused ultrasound (MRgFUS), in combination with intravenous microbubble administration, has been applied for focal temporary BBB opening in patients with neurodegenerative disorders and brain tumors. MRgFUS could become a therapeutic tool for drug delivery of putative neurorestorative therapies. Treatment for Parkinson’s disease with dementia (PDD) is an important unmet need. We initiated a prospective, single-arm, non-randomized, proof-of-concept, safety and feasibility phase I clinical trial (NCT03608553), which is still in progress. The primary outcomes of the study were to demonstrate the safety, feasibility and reversibility of BBB disruption in PDD, targeting the right parieto-occipito-temporal cortex where cortical pathology is foremost in this clinical state. Changes in β-amyloid burden, brain metabolism after treatments and neuropsychological assessments, were analyzed as exploratory measurements. Five patients were recruited from October 2018 until May 2019, and received two treatment sessions separated by 2–3 weeks. The results are set out in a descriptive manner. Overall, this procedure was feasible and reversible with no serious clinical or radiological side effects. We report BBB opening in the parieto-occipito-temporal junction in 8/10 treatments in 5 patients as demonstrated by gadolinium enhancement. In all cases the procedures were uneventful and no side effects were encountered associated with BBB opening. From pre- to post-treatment, mild cognitive improvement was observed, and no major changes were detected in amyloid or fluorodeoxyglucose PET. MRgFUS-BBB opening in PDD is thus safe, reversible, and can be performed repeatedly. This study provides encouragement for the concept of BBB opening for drug delivery to treat dementia in PD and other neurodegenerative disorders.

Blood brain barrier (BBB) opening is being investigated as a therapeutic approach for neurodegenerative diseases. Here, the authors report the results of a phase I trial to evaluate the feasibility and safety of BBB opening of the right parieto-occipito-temporal cortex in Parkinson´s disease with dementia.

Organisational and neuromodulatory underpinnings of structural-functional connectivity decoupling in patients with Parkinson's disease

Parkinson's dementia is characterised by changes in perception and thought, and preceded by visual dysfunction, making this a useful surrogate for dementia risk. Structural and functional connectivity changes are seen in humans with Parkinson's disease, but the organisational principles are not known. We used resting-state fMRI and diffusion-weighted imaging to examine changes in structural-functional connectivity coupling in patients with Parkinson's disease, and those at risk of dementia. We identified two organisational gradients to structural-functional connectivity decoupling: anterior-to-posterior and unimodal-to-transmodal, with stronger structural-functional connectivity coupling in anterior, unimodal areas and weakened towards posterior, transmodal regions. Next, we related spatial patterns of decoupling to expression of neurotransmitter receptors. We found that dopaminergic and serotonergic transmission relates to decoupling in Parkinson's overall, but instead, serotonergic, cholinergic and noradrenergic transmission relates to decoupling in patients with visual dysfunction. Our findings provide a framework to explain the specific disorders of consciousness in Parkinson's dementia, and the neurotransmitter systems that underlie these.

Repurposing GLP-1 Receptor Agonists for Parkinson's Disease: Current Evidence and Future Opportunities

The global burden of chronic disorders such as Parkinson's disease (PD) has rapidly increased over recent decades. Despite an increasing understanding of PD pathophysiology, there are no effective therapies capable of stopping or slowing the progression of this neurological condition. It has been suggested that type 2 diabetes mellitus (T2DM) may be a risk factor for PD and comorbid T2DM may worsen PD symptoms, as well as accelerate neurodegeneration. In fact, the similar pathological mechanisms shared by PD and T2DM have inspired several studies on the therapeutic potential of T2DM drugs against PD, among which glucagon-like peptide-1 receptor (GLP-1R) agonists are promising candidates. Here, we highlight the mechanisms linking T2DM and PD, as well as the links between insulin resistance (IR) and PD patients' risk of developing cognitive deficits. We also briefly review the effects of GLP-1R agonists on PD and discuss how the successful use of these substances in preclinical models of PD has paved the way for PD clinical trials. We further discuss how recent evidence on the beneficial effects of dulaglutide on cognitive function of T2DM patients may have important implications for PD drug repurposing.

An application of generalized matrix learning vector quantization in neuroimaging

BACKGROUND AND OBJECTIVE

Neurodegenerative diseases like Parkinson's disease often take several years before they can be diagnosed reliably based on clinical grounds. Imaging techniques such as MRI are used to detect anatomical (structural) pathological changes. However, these kinds of changes are usually seen only late in the development. The measurement of functional brain activity by means of [¹⁸F]fluorodeoxyglucose positron emission tomography (FDG-PET) can provide useful information, but its interpretation is more difficult. The scaled sub-profile model principal component analysis (SSM/PCA) was shown to provide more useful information than other statistical techniques. Our objective is to improve the performance further by combining SSM/PCA and prototype-based generalized matrix learning vector quantization (GMLVQ).

METHODS

We apply a combination of SSM/PCA and GMLVQ as a classifier. In order to demonstrate the combination's validity, we analyze FDG-PET data of Parkinson's disease (PD) patients collected at three different neuroimaging centers in Europe. We determine the diagnostic performance by performing a ten times repeated ten fold cross validation. Additionally, discriminant visualizations of the data are included. The prototypes and relevance of GMLVQ are transformed back to the original voxel space by exploiting the linearity of SSM/PCA. The resulting prototypes and relevance profiles have then been assessed by three neurologists.

RESULTS

One important finding is that discriminative visualization can help to identify disease-related properties as well as differences which are due to center-specific factors. Secondly, the neurologist assessed the interpretability of the method and confirmed that prototypes are similar to known activity profiles of PD patients.

CONCLUSION

We have shown that the presented combination of SSM/PCA and GMLVQ can provide useful means to assess and better understand characteristic differences in FDG-PET data from PD patients and HCs. Based on the assessments by medical experts and the results of our computational analysis we conclude that the first steps towards a diagnostic support system have been taken successfully.

Regional Parieto-occipital Hypoperfusion on Arterial Spin Labeling Associates with Major Depressive Disorder

Background:

Reduced cerebral blood flow in parieto-occipital regions has been reported in neurodegenerative disorders using ASL. We aimed to investigate neuropsychiatric and neurodegenerative comorbidities that may associate with parieto-occipital region hypoperfusion.

Methods:

This was a retrospective single-center study. Between March 2017 to May 2018, adult patients who underwent brain MRI with the inclusion of ASL perfusion and who had bilateral reductions of CBF in the parieto-occipital regions were included. ASL was performed using a pseudo-continuous arterial spin labeling (pCASL) technique on 1.5T MR system. Age and gender-matched patients with no perfusion defect were concurrently collected. Comorbidity data was collected from EMR, including major depressive disorder, Alzheimer’s disease, Parkinson’s disease, Schizophrenia, anxiety disorder, hypertension, diabetes mellitus type II, coronary artery disease, and chronic kidney disease. A Pearson’s Chi-Square test was performed to assess for comorbidities associated with hypoperfusion of the parieto-occipital lobes.

Results:

Our patient cohort consisted of 93 patients with bilateral hypoperfusion in the parieto-occipital lobes and 93 age and gender-matched patients without corresponding perfusion defects based on ASL-CBF. Among the comorbidities assessed, there was a statistically significant association between hypoperfusion of the parieto-occipital lobes and major depressive disorder (p=0.004) and Parkinson’s disease (p=0.044). There was no statistically significant association for Alzheimer’s disease, generalized anxiety disorder, diabetes mellitus type II, hypertension, coronary artery disease, or chronic kidney disease.

Conclusion:

Major depressive disorder may be linked to regional parieto-occipital hypoperfusion on ASL.

Association Between REM Sleep Behavior Disorder and Cognitive Dysfunctions in Parkinson's Disease: A Systematic Review and Meta-Analysis of Observational Studies

Background: Rapid eye movement sleep behavior disorder (RBD) is thought to be a prodromal symptom of Parkinson's disease (PD). RBD is also thought to be involved in cognitive decline and dementia in PD. In PD, although the relationship between RBD and cognitive dysfunctions was confirmed by considerable studies, whether RBD was associated with distinct types of cognitive defects is worth of study. Objectives: This systematic review summarizes the evidence relating to cognitive dysfunction in PD patients with RBD (PD-RBD) and those without and explores their specificity to cognitive domains. Methods: A meta-analysis using a random-effects model was performed for 16 different cognitive domains, including global cognitive function, memory (long-term verbal recall, long-term verbal recognition, long-term visual recall, short-term spatial recall, and short-term verbal recall), executive function (general, fluid reasoning, generativity, shifting, inhibition, and updating), language, processing speed/complex attention/working memory, visuospatial/constructional ability, and psychomotor ability. The cognitive difference between the groups of patients was measured as a standardized mean difference (SMD, Cohen's d). PD-RBD patients were classified into Confirmed-RBD (definite diagnosis with polysomnography, PSG) and Probable-RBD (without PSG re-confirmation). In some domains, RBD patients could not be analyzed separately due to the exiguity of primary studies; this analysis refers to such RBD patients as "Mixed-RBD." Results: Thirty-nine studies with 6,695 PD subjects were finally included. Confirmed-RBD patients showed worse performance than those without in global cognitive function, long-term verbal recall, long-term verbal recognition, generativity, inhibition, shifting, language, and visuospatial/constructional ability; Probable-RBD, in global cognitive function and shifting; and Mixed-RBD, in long-term visual recall, short-term spatial recall, general executive function, and processing speed/complex attention/working memory. Conclusion: This meta-analysis strongly suggests a relationship between RBD, Confirmed-RBD in particular, and cognitive dysfunctions in PD patients. Early and routine screening by sensitive and targeted cognitive tasks is necessary for all PD-RBD patients because it may offer the therapeutic time window before they evolve to irreversible dementia.

Cognitive impairment in Parkinson's disease: A clinical and pathophysiological overview

Cognitive dysfunction in Parkinson's disease (PD) has received increasing attention, and, together with other non-motor symptoms, exert a significant functional impact in the daily lives of patients. This article aims to compile and briefly summarize selected published data about clinical features, cognitive evaluation, biomarkers, and pathophysiology of PD-related dementia (PDD). The literature search included articles indexed in the MEDLINE/PubMed database, published in English, over the last two decades. Despite significant progress on clinical criteria and cohort studies for PD-mild cognitive impairment (PD-MCI) and PDD, there are still knowledge gaps about its exact molecular and pathological basis. Here we overview the scientific literature on the role of functional circuits, neurotransmitter systems (monoaminergic and cholinergic), basal forebrain, and brainstem nuclei dysfunction in PD-MCI. Correlations between neuroimaging and cerebrospinal fluid (CSF) biomarkers, clinical outcomes, and pathological results are described to aid in uncovering the neurodegeneration pattern in PD-MCI and PDD.

Abnormal pattern of brain glucose metabolism in Parkinson's disease: replication in three European cohorts

Rationale

In Parkinson’s disease (PD), spatial covariance analysis of ¹⁸F-FDG PET data has consistently revealed a characteristic PD-related brain pattern (PDRP). By quantifying PDRP expression on a scan-by-scan basis, this technique allows objective assessment of disease activity in individual subjects. We provide a further validation of the PDRP by applying spatial covariance analysis to PD cohorts from the Netherlands (NL), Italy (IT), and Spain (SP).

Methods

The PDRP_NL was previously identified (17 controls, 19 PD) and its expression was determined in 19 healthy controls and 20 PD patients from the Netherlands. The PDRP_IT was identified in 20 controls and 20 “de-novo” PD patients from an Italian cohort. A further 24 controls and 18 “de-novo” Italian patients were used for validation. The PDRP_SP was identified in 19 controls and 19 PD patients from a Spanish cohort with late-stage PD. Thirty Spanish PD patients were used for validation. Patterns of the three centers were visually compared and then cross-validated. Furthermore, PDRP expression was determined in 8 patients with multiple system atrophy.

Results

A PDRP could be identified in each cohort. Each PDRP was characterized by relative hypermetabolism in the thalamus, putamen/pallidum, pons, cerebellum, and motor cortex. These changes co-varied with variable degrees of hypometabolism in posterior parietal, occipital, and frontal cortices. Frontal hypometabolism was less pronounced in “de-novo” PD subjects (Italian cohort). Occipital hypometabolism was more pronounced in late-stage PD subjects (Spanish cohort). PDRP_IT, PDRP_NL, and PDRP_SP were significantly expressed in PD patients compared with controls in validation cohorts from the same center (P < 0.0001), and maintained significance on cross-validation (P < 0.005). PDRP expression was absent in MSA.

Conclusion

The PDRP is a reproducible disease characteristic across PD populations and scanning platforms globally. Further study is needed to identify the topography of specific PD subtypes, and to identify and correct for center-specific effects.

Electronic supplementary material

The online version of this article (10.1007/s00259-019-04570-7) contains supplementary material, which is available to authorized users.

Correlations of Neuropsychological and Metabolic Brain Changes in Parkinson's Disease and Other α-Synucleinopathies

Cognitive impairment is a common feature in Parkinson's disease (PD) and other α-synucleinopathies as 80% of PD patients develop dementia within 20 years. Early cognitive changes in PD patients present as a dysexecutive syndrome, broadly characterized as a disruption of the fronto-striatal dopamine network. Cognitive deficits in other domains (recognition memory, attention processes and visuospatial abilities) become apparent with the progression of PD and development of dementia. In dementia with Lewy bodies (DLB) the cognitive impairment develops early or even precedes parkinsonism and it is more pronounced in visuospatial skills and memory. Cognitive impairment in the rarer α-synucleinopathies (multiple system atrophy and pure autonomic failure) is less well studied. Metabolic brain imaging with positron emission tomography and [¹⁸F]-fluorodeoxyglucose (FDG-PET) is a well-established diagnostic method in neurodegenerative diseases, including dementias. Changes in glucose metabolism precede those seen on structural magnetic resonance imaging (MRI). Reduction in glucose metabolism and atrophy have been suggested to represent consecutive changes of neurodegeneration and are linked to specific cognitive disorders (e.g., dysexecutive syndrome, memory impairment, visuospatial deficits etc.). Advances in the statistical analysis of FDG-PET images enabling a network analysis broadened our understanding of neurodegenerative brain processes. A specific cognitive pattern related to PD was identified by applying voxel-based network modeling approach. The magnitude of this pattern correlated significantly with patients' cognitive skills. Specific metabolic brain changes were observed also in patients with DLB as well as in a prodromal phase of α-synucleinopathy: REM sleep behavior disorder. Metabolic brain imaging with FDG-PET is a reliable biomarker of neurodegenerative brain diseases throughout their course, precisely reflecting their topographic distribution, stage and functional impact.

Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson’s Disease in 3D Nuclear Imaging Data

Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is a PET technique employed to obtain a representation of brain metabolic function. In this study we employed 3D CNNs in FDG-PET brain images with the purpose of discriminating patients diagnosed with Parkinson’s disease (PD) from controls. We employed Scaled Subprofile Modeling using Principal Component Analysis as a preprocessing step to focus on specific brain regions and limit the number of voxels that are used as input for the CNNs, thereby increasing the signal-to-noise ratio in our data. We performed hyperparameter optimization on three CNN architectures to estimate the classification accuracy of the networks on new data. The best performance that we obtained was [Formula: see text] and area under the receiver operating characteristic curve [Formula: see text] on the test set. We believe that, with larger datasets, PD patients could be reliably distinguished from controls by FDG-PET scans alone and that this technique could be applied to more clinically challenging tasks, like the differential diagnosis of neurological disorders with similar symptoms, such as PD, Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA).

Nigrostriatal dopamine transporter availability, and its metabolic and clinical correlates in Parkinson's disease patients with impulse control disorders

PURPOSE

Previous studies in patients with Parkinson's disease (PD) and impulse control disorders (ICDs) have produced heterogeneous results regarding striatal dopamine transporter (DaT) binding and activity in the mesocorticolimbic network. Our aim here was to study the relationship between striatal DaT availability and cortical metabolism, as well as motor, behavioural and cognitive features of PD patients with ICD.

METHODS

In a group of PD patients with ICD (PD-ICD, n = 16) and 16 matched PD patients without ICD (PD-noICD, n = 16), DaT single-photon emission computed tomography (SPECT) imaging (DaTSCAN) was used to study DaT availability in predefined striatal volumes of interest (VOIs): putamen, caudate nucleus and ventral striatum (VS). In addition, the specific association of striatal DaT binding with cortical limbic and associative metabolic activity was evaluated by ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in PD-ICD patients and investigated using statistical parametric mapping (SPM8). Finally, associations between DaT availability and motor, behavioural and cognitive features were assessed.

RESULTS

PD-ICD patients had a significantly lower DaT density in the VS than PD-noICD patients, which was inversely associated with ICD severity. Lower DaT availability in the VS was associated with lower FDG uptake in several cortical areas belonging to the limbic and associative circuits, and in other regions involved in reward and inhibition processes (p < 0.0001 uncorrected; k > 50 voxels). No significant results were observed using a higher conservative threshold (p < 0.05; FDR corrected). PD-ICD patients also displayed impairment in interference and attentional Stroop Task execution, and more anxiety, all associated with reduced DaT availability in the VS and caudate nucleus.

CONCLUSIONS

ICDs in PD patients are related to reduced DaT binding in the VS, which accounts for dysfunction in a complex cortico-subcortical network that involves areas of the mesolimbic and mesocortical systems, being associated with reward evaluation, salience attribution and inhibitory control processes.

Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies

Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.

Recent Advancement and Clinical Implications of 18FDG-PET in Parkinson's Disease, Atypical Parkinsonisms, and Other Movement Disorders

PURPOSE OF REVIEW

The molecular imaging field has been very instrumental in identifying the multiple network interactions that compose the human brain. The cerebral glucose metabolism is associated with neural function. 18F-fluoro-deoxyglucose-PET (FDG-PET) studies reflect brain metabolism in a pattern-specific manner. This article reviews FDG-PET studies in Parkinson's disease (PD), atypical parkinsonism (AP), Huntington's disease (HD), and dystonia.

RECENT FINDINGS

The metabolic pattern of PD, disease progression, non-motor symptoms such as fatigue, depression, apathy, impulse control disorders, and cognitive impairment, and the risk of progression to dementia have been identified with FDG-PET studies. In prodromal PD, the REM sleep behavior disorder-related covariance pattern has been described. In AP, FDG-PET studies have demonstrated to be superior to D2/D3 SPECT in differentiating PD from AP. The metabolic patterns of HD and dystonia have also been described. FDG-PET studies are an excellent tool to identify patterns of brain metabolism.

Can neuroimaging predict dementia in Parkinson's disease?

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.