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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.

Idiopathic Parkinson's disease (iPD) is associated with two distinct brain networks, PD-related pattern (PDRP) and PD-related cognitive pattern (PDCP), which correlate respectively with motor and cognitive symptoms. The relationship between the two networks in individual patients is unclear.To determine whether a consistent relationship exists between these networks, we measured the difference between PDRP and PDCP expression, termed delta, on an individual basis in independent populations of patients with iPD (n = 356), patients with idiopathic REM sleep behavioral disorder (iRBD) (n = 21), patients with genotypic PD (gPD) carrying GBA1 variants (n = 12) or the LRRK2-G2019S mutation (n = 14), patients with atypical parkinsonian syndromes (n = 238), and healthy control subjects (n = 95) from the United States, Slovenia, India, and South Korea.We used [Delta was abnormally elevated in each of the four iPD samples (P 0.05), as well as in the at-risk iRBD group (P 0.05), with increasing values over time (P 0.001). PDRP predominance was also present in gPD, with higher values in patients with GBA1 variants compared with the less aggressive LRRK2-G2019S mutation (P = 0.005). This trend was not observed in patients with atypical parkinsonian syndromes, who were accurately discriminated from iPD based on PDRP expression and delta (area under the curve = 0.85; P 0.0001).PDRP predominance, quantified by delta, assays the spread of dysfunction from motor to cognitive networks in patients with PD. Delta may therefore aid in differential diagnosis and in tracking disease progression in individual patients. © 2022 International Parkinson and Movement Disorder Society.

Background and purpose: Although sporadic Creutzfeldt–Jakob disease (sCJD) is a rare cause of dementia, it is critical to understand its functional networks as the prion protein spread throughout the brain may share similar mechanisms with other more common neurodegenerative disorders. In this study, the metabolic brain network associated with sCJD was investigated and its internal network organization was explored. Methods: We explored 2-[$^{18}$F]fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) brain scans of 29 sCJD patients, 56 normal controls (NCs) and 46 other dementia patients from two independent centers. sCJD-related pattern (CJDRP) was identified in a cohort of 16 pathologically proven sCJD patients and 16 age-matched NCs using scaled subprofile modeling/principal component analysis and was prospectively validated in an independent cohort of 13 sCJD patients and 20 NCs. The pattern's specificity was tested on other dementia patients and its clinical relevance by clinical correlations. The pattern's internal organization was further studied using graph theory methods. Results: The CJDRP was characterized by relative hypometabolism in the bilateral caudate, thalami, middle and superior frontal gyri, parietal lobe and posterior cingulum in association with relative hypermetabolism in the hippocampi, parahippocampal gyri and cerebellum. The pattern's expression significantly discriminated sCJD from NCs and other dementia patients (p < 0.005 receiver operating characteristic analysis CJD vs. NCs area under the curve [AUC] 0.90–0.96, sCJD vs. Alzheimer's disease AUC 0.78, sCJD vs. behavioral variant of frontotemporal dementia AUC 0.84). The pattern's expression significantly correlated with cognitive, functional decline and disease duration. The metabolic connectivity analysis revealed inefficient information transfer with specific network reorganization. Conclusions: The CJDRP is a robust metabolic biomarker of sCJD. Due to its excellent clinical correlations it has the potential to monitor disease in emerging disease-modifying trials.

Cell transplants are being developed for patients with Parkinson disease (PD) who have insufficient benefit with standard medical treatment. We describe the clinical features of five patients who developed persistent dyskinesias after fetal dopaminergic tissue transplantation. All had levodopa-induced dyskinesias preoperatively. We implanted fetal mesencephalic dopaminergic tissue into the putamina bilaterally in 34 patients with advanced PD. They were not immunosuppressed. Five of 34 patients (15%) developed troublesome choreic or dystonic dyskinesias that persisted despite lowering or discontinuing medications. Attempts to treat the involuntary movements with amantadine, clozapine, anticholinergics, dopamine depletors and other medicines had limited success. Metyrosine eliminated dyskinesias but led to the parkinsonian “off” state. Increasing the dose of levodopa worsened the dyskinesias. Three patients required placement of pallidal stimulators, bilaterally in two and unilaterally in one patient who had only contralateral dyskinesias. The two with the bilateral stimulators had improvement in dyskinesias. The patient with the unilateral pallidal stimulator had a substantial reduction of the dyskinesias, but attempts to treat residual “off” symptoms with levodopa were limited by worsening dyskinesias. Although the number of patients developing these persistent dyskinesias was small, these five patients had dramatic improvement after transplant. As a group, they had milder Parkinson signs at baseline and improved to the point of having minimal parkinsonism, with reduction or elimination of levodopa therapy prior to developing persistent dyskinesias. These involuntary movements establish the principle that fetal dopaminergic tissue transplants can mimic the effects of levodopa, not only in reducing bradykinesia, but also in provoking dyskinesias.

Recent studies on a rodent model of Parkinson’s disease (PD) have raised the possibility of increased blood–brain barrier (BBB) permeability, demonstrated by histology, autoradiography, and positron emission tomography (PET). However, in human PD patients, in vivo evidence of increased BBB permeability is lacking. We examined the hypothesis that levodopa treatment increases BBB permeability in human subjects with PD, particularly in those with levodopa-induced dyskinesia (LID). We used rubidium-82 (82Rb) and PET to quantify BBB influx in vivo in 19 PD patients, including eight with LID, and 12 age- and sex-matched healthy subjects. All subjects underwent baseline 82Rb scans. Seventeen chronically levodopa-treated patients were additionally rescanned during intravenous levodopa infusion. Influx rate constant, K1, by compartmental modeling or net influx transport, Ki, by graphical approach could not be estimated reliably. However, Vd, the “apparent volume of distribution” based on the 82Rb concentration in brain tissue and blood, was estimated with good stability as a local measure of the volume of distribution. Rubidium influx into brain tissue was undetectable in PD patients with or without LID, scanned on and off drug. No significant differences in regional Vd were observed for PD patients with or without LID relative to healthy subjects, except in left thalamus. Moreover, changes in Vd measured off- and on-levodopa infusion were also not significant for dyskinetic and non-dyskinetic subjects. 82Rb PET did not reveal significant changes in BBB permeability in PD patients.

Background: Parkinson’s disease (PD) is characterized by brain metabolic networks, specifically associated with motor and cognitive manifestations. Few studies have investigated network changes in cerebral hemispheres ipsilateral and contralateral to the clinically more affected body side. Objective: We examined hemispheric network abnormalities and their relationship to striatal dopaminergic deficits in PD patients at different stages. Methods: 45 PD patients underwent dual-tracer positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) and 18F-fluorodopa (FDOPA) in a high-resolution PET scanner. In all patients, we computed expression levels for the PD-related motor/cognition metabolic patterns (PDRP/PDCP) as well as putamen/caudate FDOPA uptake values in both hemispheres. Resulting hemispheric measures in the PD group were compared with corresponding healthy control values and assessed across disease stages. Results: Hemispheric PDRP and PDCP expression was significantly elevated contralateral and ipsilateral to the more affected body side in patients with unilateral symptoms (H&Y 1: p

Background Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson's disease (PD). Biallelic GBA mutations cause the lysosomal storage disorder Gaucher's disease. The GBA variants p.E365K and p.T408M are associated with PD but not with Gaucher's disease. The pathophysiological role of these variants needs to be further explored. Objective This study analyzed clinical, neuropsychological, metabolic, and neuroimaging phenotypes of patients with PD carrying the GBA variants p.E365K and p.T408M. Methods GBA was sequenced in 56 patients with mid-stage PD. Carriers of GBA variants were compared with noncarriers regarding clinical history and symptoms, neuropsychological features, metabolomics, and multimodal neuroimaging. Blood plasma gas chromatography coupled to mass spectrometry, 6-[18 F]fluoro-L-Dopa positron emission tomography (PET), [18 F]fluorodeoxyglucose PET, and resting-state functional magnetic resonance imaging were performed. Results Sequence analysis detected 13 heterozygous GBA variant carriers (7 with p.E365K, 6 with p.T408M). One patient carried a GBA mutation (p.N409S) and was excluded. Clinical history and symptoms were not significantly different between groups. Global cognitive performance was lower in variant carriers. Metabolomic group differences were suggestive of more severe PD-related alterations in carriers versus noncarriers. Both PET scans showed signs of a more advanced disease; [18 F]fluorodeoxyglucose PET and functional magnetic resonance imaging showed similarities with Lewy body dementia and PD dementia in carriers. Conclusions This is the first study to comprehensively assess (neuro-)biological phenotypes of GBA variants in PD. Metabolomics and neuroimaging detected more significant group differences than clinical and behavioral evaluation. These alterations could be promising to monitor effects of disease-modifying treatments targeting glucocerebrosidase metabolism. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The concept of repairing the brain with growth factors has been pursued for many years in a variety of neurodegenerative diseases including primarily Parkinson's disease (PD) using glial cell line-derived neurotrophic factor (GDNF). This neurotrophic factor was discovered in 1993 and shown to have selective effects on promoting survival and regeneration of certain populations of neurons including the dopaminergic nigrostriatal pathway. These observations led to a series of clinical trials in PD patients including using infusions or gene delivery of GDNF or the related growth factor, neurturin (NRTN). Initial studies, some of which were open label, suggested that this approach could be of value in PD when the agent was injected into the putamen rather than the cerebral ventricles. In subsequent double-blind, placebo-controlled trials, the most recent reporting in 2019, treatment with GDNF did not achieve its primary end point. As a result, there has been uncertainty as to whether GDNF (and by extrapolation, related GDNF family neurotrophic factors) has merit in the future treatment of PD. To critically appraise the existing work and its future, a special workshop was held to discuss and debate this issue. This paper is a summary of that meeting with recommendations on whether there is a future for this therapeutic approach and also what any future PD trial involving GDNF and other GDNF family neurotrophic factors should consider in its design.

Background An ideal imaging biomarker for a neurodegenerative disorder should be able to measure abnormalities in the earliest stages of the disease. Objective We investigated metabolic network changes in two independent cohorts of drug-naive Parkinson's disease (PD) patients who have not been exposed to dopaminergic medication. Methods We scanned 85 de novo, drug-naive PD patients and 85 age-matched healthy control subjects from Italy (n = 96) and the United States (n = 74) with [18 F]-fluorodeoxyglucose PET. All patients had clinical follow-ups to verify the diagnosis of idiopathic PD. Spatial covariance analysis was used to identify and validate de novo PD-related metabolic patterns in the Italian and U.S. cohorts. We compared the de novo PD-related metabolic patterns to the original PD-related pattern that was identified in more advanced patients who had been on chronic dopaminergic treatment. Results De novo PD-related metabolic patterns were identified in each of the two independent cohorts of drug-naive PD patients, and each differentiated PD patients from healthy control subjects. Expression values for these disease patterns were elevated in drug-naive PD patients relative to healthy controls in the identification as well as in each of the validation subgroups. The two de novo PD-related metabolic patterns were topographically very similar to each other and to the original PD-related pattern. Conclusions Reproducible PD-related patterns are expressed in de novo, drug-naive PD patients. In PD, disease-related metabolic patterns have stereotyped topographies that develop independently of chronic levodopa treatment. © 2019 International Parkinson and Movement Disorder Society.

Levodopa-induced dyskinesia (LID) represents a significant source of discomfort for people with Parkinson's disease (PD). It negatively affects quality of life, it is associated with both motor and nonmotor fluctuations, and it brings an increased risk of disability, balance problems, and falls. Although the prevalence of severe LID appears to be lower than in previous eras (likely owing to a more conservative use of oral levodopa), we have not yet found a way to prevent the development of this complication. Advanced surgical therapies, such as deep brain stimulation, ameliorate LID, but only a minority of PD patients qualify for these interventions. Although some have argued that PD patients would rather be ON with dyskinesia than OFF, the deeper truth is that patients would very much prefer to be ON without dyskinesia. As researchers and clinicians, we should aspire to make that goal a reality. To this end, translational research on LID is to be encouraged and persistently pursued. © 2019 International Parkinson and Movement Disorder Society.

Regional changes in brain metabolism upgraded with measurements of specific metabolic brain patterns and automated diagnostic algorithms can help to differentiate among neurodegenerative parkinsonisms, but with few reports on pathological confirmation. Here we describe a parkinsonian patient with atypical presentation and 18F-FDG-PET imaging consistent with idiopathic Parkinson's disease. The latter was confirmed at the pathohistological examination.

Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for Parkinson's disease (PD) but can have an adverse effect on speech. In normal speakers and in those with spinocerebellar ataxia, an inverse relationship between regional cerebral blood flow (rCBF) in the left inferior frontal (IFG) region and the right caudate (CAU) is associated with speech rate. This pattern was examined to determine if it was present in PD, and if so, whether it was altered by STN-DBS.Methods: Positron Emission Tomography (PET) measured rCBF during speech in individuals with PD not treated with STN-DBS (n = 7), and those treated with bilateral STN-DBS (n = 7). Previously reported results from non-PD control subjects (n = 16) were reported for comparison. The possible relationships between speech rate during scanning and data from the left and right IFG and CAU head regions were investigated using a step-wise multiple linear regression to identify brain regions that interacted to predict speech rate.Results: The multiple linear regression analysis replicated previously reported predictive coefficients for speech rate involving the left IFG and right CAU regions. However, the relationships between these predictive coefficients and speech rates were abnormal in both PD groups. In PD who had not received STN-DBS, the right CAU coefficient decreased normally with increasing speech rate but the left IFG coefficient abnormally decreased. With STN-DBS, this pattern was partially normalized with the addition of a left IFG coefficient that increased with speech rate, as in normal controls, but the abnormal left IFG decreasing coefficient observed in PD remained. The magnitudes of both cortical predictive coefficients but not the CAU coefficient were exaggerated with STN-DBS.Conclusions: STN-DBS partially corrects the abnormal relationships between rCBF and speech rate found in PD by introducing a left IFG subregion that increases with speech rate, but the conflicting left IFG subregion response remained. Conflicting IFG responses may account for some of the speech problems observed after STN-DBS. Cortical and subcortical regions may be differentially affected by STN-DBS.

ObjectiveTo determine whether the Alzheimer disease (AD) dementia conversion-related pattern (ADCRP) on [18F]FDG PET can serve as a valid predictor for the development of AD dementia, the individual expression of the ADCRP (subject score) and its prognostic value were examined in patients with mild cognitive impairment (MCI) and biologically defined AD.MethodsA total of 269 patients with available [18F]FDG PET, [18F]AV-45 PET, phosphorylated and total tau in CSF, and neurofilament light chain in plasma were included. Following the AT(N) classification scheme, where AD is defined biologically by in vivo biomarkers of β-amyloid (Aβ) deposition (“A”) and pathologic tau (“T”), patients were categorized to the A−T−, A+T−, A+T+ (AD), and A−T+ groups.ResultsThe mean subject score of the ADCRP was significantly higher in the A+T+ group compared to each of the other group (all p < 0.05) but was similar among the latter (all p > 0.1). Within the A+T+ group, the subject score of ADCRP was a significant predictor of conversion to dementia (hazard ratio, 2.02 per z score increase; p < 0.001), with higher predictive value than of alternative biomarkers of neurodegeneration (total tau and neurofilament light chain). Stratification of A+T+ patients by the subject score of ADCRP yielded well-separated groups of high, medium, and low conversion risks.ConclusionsThe ADCRP is a valuable biomarker of neurodegeneration in patients with MCI and biologically defined AD. It shows great potential for stratifying the risk and estimating the time to conversion to dementia in patients with MCI and underlying AD (A+T+).Classification of EvidenceThis study provides Class I evidence that [18F]FDG PET predicts the development of AD dementia in individuals with MCI and underlying AD as defined by the AT(N) framework.

Purpose Multiple system atrophy (MSA) is an atypical parkinsonian syndrome and often difficult to discriminate clinically from progressive supranuclear palsy (PSP) and Parkinson's disease (PD) in early stages. Although a characteristic metabolic brain network has been reported for MSA, it is unknown whether this network can provide a clinically useful biomarker in different centers. This study was aimed to identify and cross-validate MSA-related brain network and assess its ability for differential diagnosis and clinical correlations in Chinese and American patient cohorts. Methods We included 18F-FDG PET scans retrospectively from 128 clinically diagnosed parkinsonian patients (34 MSA, 34 PSP and 60 PD) and 40 normal subjects in China and in the USA. Using PET images from 20 moderate-stage MSA patients of parkinsonian subtype and 20 normal subjects in both centers, we reproduced MSA-related pattern (MSAPRP) of spatial covariance and estimated its reliability. MSAPRP scores were evaluated in assessing differential diagnosis among moderate- and early-stage MSA, PSP or PD patients and clinical correlations with disease severity. Regional metabolic differences were detected using statistical parameter mapping analysis. MSA-related network and regional topographies of metabolic abnormality were cross-validated between the Chinese and American cohorts. Results We generated a highly reliable MSAPRP characterized by decreased loading in inferior frontal cortex, striatum and cerebellum, and increased loading in sensorimotor, parietal and occipital cortices. MSAPRP scores discriminated between normal, MSA, PSP and PD subjects and correlated with standardized ratings of clinical stages and motor symptoms in MSA. High similarities in MSAPRPs, network scores and corresponding maps of metabolic abnormality were observed between two different cohorts. Conclusion We have demonstrated reproducible metabolic topographies associated with MSA at both network and regional levels in two independent patient cohorts. Moreover, MSAPRP scores are sensitive for evaluating disease discrimination and clinical correlates. This study supports differential diagnosis of MSA regardless of different patient populations, PET scanners and imaging protocols.

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.A cohort of 79 participants with DLB, 63 with dementia due to Alzheimer's disease (AD) and 41 normal controls (NCs) and their 2-[The newly identified DLBRP shared topographic similarities with ADRP (RDLBRP 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.

Summary Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.

Progressive supranuclear palsy (PSP) is a rare movement disorder and often difficult to distinguish clinically from Parkinson’s disease (PD) and multiple system atrophy (MSA) in early phases. In this study, we report reproducible disease-related topographies of brain network and regional glucose metabolism associated with PSP in clinically-confirmed independent cohorts of PSP, MSA and PD patients and healthy controls in the USA and China. Using (18)F-FDG PET images from PSP and healthy subjects, we applied spatial covariance analysis with bootstrapping to identify a PSP-related pattern (PSPRP) and estimate its reliability, and evaluated the ability of network scores for differential diagnosis. We also detected regional metabolic differences using statistical parametric mapping analysis. We produced a highly reliable PSPRP characterized by relative metabolic decreases in the middle prefrontal cortex/cingulate, ventrolateral prefrontal cortex, striatum, thalamus and midbrain, covarying with relative metabolic increases in the hippocampus, insula and parieto-temporal regions. PSPRP network scores correlated positively with PSP duration and accurately discriminated between healthy, PSP, MSA and PD groups in two separate cohorts of parkinsonian patients at both early and advanced stages. Moreover, PSP patients shared many overlapping areas with abnormal metabolism in the same cortical and subcortical regions as in the PSPRP. With rigorous cross-validation, this study demonstrated highly comparable and reproducible PSP-related metabolic topographies at network and regional levels across different patient populations and PET scanners. Metabolic brain network activity may serve as a reliable and objective marker of PSP, although cross-validation applying recent diagnostic criteria and classification is warranted.

Introduction The heterogeneity of behavioral variant frontotemporal dementia (bvFTD) calls for multivariate imaging biomarkers. Methods We studied a total of 148 dementia patients from the Feinstein Institute (Center‐A: 25 bvFTD and 10 Alzheimer's disease), Technical University of Munich (Center‐B: 44 bvFTD and 29 FTD language variants), and Alzheimer's Disease Neuroimaging Initiative (40 Alzheimer's disease subjects). To identify the covariance pattern of bvFTD (behavioral variant frontotemporal dementia–related pattern [bFDRP]), we applied principal component analysis to combined 18F‐fluorodeoxyglucose–positron emission tomography scans from bvFTD and healthy subjects. The phenotypic specificity and clinical correlates of bFDRP expression were assessed in independent testing sets. Results The bFDRP was identified in Center‐A data (24.1% of subject × voxel variance; P

In healthy subjects, brain activation in motor regions is greater during the visual perception of "natural" target motion, which complies with the two-thirds power law, than of "unnatural" motion, which does not. It is unknown whether motion perception is normally mediated by a specific network that can be altered in the setting of disease. We used block-design functional magnetic resonance imaging and covariance analysis to identify normal network topographies activated in response to "natural" versus "unnatural" motion. A visual motion perception-related pattern (VPRP) was identified in 12 healthy subjects, characterized by covarying activation responses in the inferior parietal lobule, frontal operculum, lateral occipitotemporal cortex, amygdala, and cerebellum (Crus I). Selective VPRP activation during "natural" motion was confirmed in 12 testing scans from healthy subjects. Consistent network activation was not seen, however, in 29 patients with dystonia, a neurodevelopmental disorder in which motion perception pathways may be involved. Using diffusion tractography, we evaluated the integrity of anatomical connections between the major VPRP nodes. Indeed, fiber counts in these pathways were substantially reduced in the dystonia subjects. In aggregate, the findings associate normal motion perception with a discrete brain network which can be disrupted under pathological conditions.

Molecular imaging has proven to be a powerful tool for investigation of parkinsonian disorders. One current challenge is to identify biomarkers of early changes that may predict the clinical trajectory of parkinsonian disorders. Exciting new tracer developments hold the potential for in vivo markers of underlying pathology. Herein, we provide an overview of molecular imaging advances and how these approaches help us to understand PD and atypical parkinsonisms. © 2016 International Parkinson and Movement Disorder Society.

Background Parkinson’s disease and related cognitive deficits have been associated with specific functional topographies termed functional PD-related pattern (fPDRP) and PD cognition-related pattern (fPDCP) ( Vo et al., 2017 ). Using multivariate analysis in resting-state functional MRI data this novel approach discriminated normal controls from PD patients based on their pattern expression and was associated with the severity of clinical measures. Aim We aim to investigate whether the functional PDCP topography is reproducible across different PD populations and whether fPDCP expression values can discriminate PD patients with and without mild cognitive impairment. Method Rs-fMRI scans from 22 PD patients in the on-state and 13 matched control subjects were analyzed using independent component analysis in conjunction with bootstrap resampling to identify a fPDCP topography in an independent cohort of PD patients from Berlin (Charite). Neuropsychological testing results were assessed and correlated with pattern expression. For further validation, subject scores for the fPDCP BERLIN pattern were computed in an independent group of 21 PD patients from North Shore (NS), USA. Subject scores and temporal dynamics were estimated for prospective cases with dual regression using the spatial maps generated from the Berlin derivation set and z-scored with regard to the normal control group. Results The fPDCP Berlin topography resembled the original fPDCP NS network topography ( Fig. 1 ). Subjects scores for the different fPDCP topographies from Berlin and North Shore were closely correlated in the Berlin sample (r = 0.67; p Fig. 2 ). fPDCP expression was significantly elevated in patients with MCI compared to their cognitively unimpaired counterparts in the NS cohort (p Fig. 2 ). Conclusions These findings suggest that fPDCP represents a stable disease related network topography across independent patient populations. This and the ability to discriminate PD patients with mild cognitive impairment indicate that fPDCP could be used as non-invasive imaging biomarker for cognitive dysfunction in PD patients.

A role for the cerebellum in causing ataxia, a disorder characterized by uncoordinated movement, is widely accepted. Recent work has suggested that alterations in activity, connectivity, and structure of the cerebellum are also associated with dystonia, a neurological disorder characterized by abnormal and sustained muscle contractions often leading to abnormal maintained postures. In this manuscript, the authors discuss their views on how the cerebellum may play a role in dystonia. The following topics are discussed: The relationships between neuronal/network dysfunctions and motor abnormalities in rodent models of dystonia. Data about brain structure, cerebellar metabolism, cerebellar connections, and noninvasive cerebellar stimulation that support (or not) a role for the cerebellum in human dystonia. Connections between the cerebellum and motor cortical and sub-cortical structures that could support a role for the cerebellum in dystonia. Overall points of consensus include: Neuronal dysfunction originating in the cerebellum can drive dystonic movements in rodent model systems. Imaging and neurophysiological studies in humans suggest that the cerebellum plays a role in the pathophysiology of dystonia, but do not provide conclusive evidence that the cerebellum is the primary or sole neuroanatomical site of origin.

Objective: To determine whether cognitive impairment in Parkinson disease (PD) and Alzheimer disease (AD) derives from the same network pathology. Methods: We analyzed 18 F-fluorodeoxyglucose PET scans from 40 patients with AD and 40 age-matched healthy controls from the Alzheimer’s Disease Neuroimaging Initiative and scanned an additional 10 patients with AD and 10 healthy controls at The Feinstein Institute for Medical Research to derive an AD-related metabolic pattern (ADRP) analogous to our previously established PD cognition-related pattern (PDCP) and PD motor-related pattern (PDRP). We computed individual subject expression values for ADRP and PDCP in 89 patients with PD and correlated summary scores for cognitive functioning with network expression. We also evaluated changes in ADRP and PDCP expression in a separate group of 15 patients with PD scanned serially over a 4-year period. Results: Analysis revealed a significant AD-related metabolic topography characterized by covarying metabolic reductions in the hippocampus, parahippocampal gyrus, and parietal and temporal association regions. Expression of ADRP, but not PDCP, was elevated in both AD groups and correlated with worse cognitive summary scores. Patients with PD showed slight ADRP expression, due to topographic overlap with the network underlying PD motor-related pattern degeneration, but only their PDCP expression values increased as cognitive function and executive performance declined. Longitudinal data in PD disclosed an analogous dissociation of network expression. Conclusions: Cognitive dysfunction in PD is associated with a specific brain network that is largely spatially and functionally distinct from that seen in relation to AD.

Background We have previously defined a parkinsonism-related metabolic brain network in rhesus macaques using a high-resolution research positron emission tomography camera. This brief article reports a descriptive pilot study to assess the reproducibility of network activity and regional glucose metabolism in independent parkinsonian macaques using a clinical positron emission tomography/CT camera. Methods [18F]fluorodeoxyglucose PET scans were acquired longitudinally over 3 months in three drug-naive parkinsonian and three healthy control cynomolgus macaques. Group difference and test–retest stability in network activity and regional glucose metabolism were evaluated graphically, using all brain images from these macaques. Results Comparing the parkinsonian macaques with the controls, network activity was elevated and remained stable over 3 months. Normalized glucose metabolism increased in putamen/globus pallidus and sensorimotor regions but decreased in posterior parietal cortices. Conclusions Parkinsonism-related network activity can be reliably quantified in different macaques with a clinical positron emission tomography/CT scanner and is reproducible over a period typically employed in preclinical intervention studies. This measure can be a useful biomarker of disease process or drug effects in primate models of Parkinson's disease. ©2015 International Parkinson and Movement Disorder Society

Parkinson's disease (PD) is associated with distinct metabolic covariance patterns that relate to the motor and cognitive manifestations of the disorder. It is not known, however, how the expression of these patterns relates to measurements of nigrostriatal dopaminergic activity from the same individuals. To explore these associations, we studied 106 PD subjects who underwent cerebral PET with both 18F-fluorodeoxyglucose (FDG) and 18F-fluoro-L-dopa (FDOPA). Expression values for the PD motor- and cognition-related metabolic patterns (PDRP and PDCP, respectively) were computed for each subject; these measures were correlated with FDOPA uptake on a voxel-by-voxel basis. To explore the relationship between dopaminergic function and local metabolic activity, caudate and putamen FDOPA PET signal was correlated voxel-wise with FDG uptake over the entire brain. PDRP expression correlated with FDOPA uptake in caudate and putamen (P

Electrical stimulation of subthalamic nuclei (STN) is a widely used therapy in Parkinson’s disease (PD). While deep brain stimulation (DBS) of the STN alters the neurophysiological activity in basal ganglia, the therapeutic mechanism has not been established. A positron emission tomography (PET) study of cerebral blood flow (CBF) during speech production in PD subjects treated with STN-DBS found significant increases in global (whole-brain) CBF.1 That study utilized a series of whole-slice regions of interest to obtain global CBF values. The present study examined this effect using a voxel-based principal component analysis (PCA) combined with Fisher’s linear discriminant analysis (FLDA) to classify STN-DBS on versus STN-DBS off whole-brain images. The approach yielded wide-spread CBF changes that classified STN-DBS status with accuracy, sensitivity, and specificity approaching 90%. The PCA component of the analysis supported the observation of a global CBF change during STN-DBS. The FLDA component demonstrated wide-spread multi-focal CBF changes. Further, CBF measurements related to a number of subject characteristics when STN-DBS was off, but not when it was on, suggesting that the normal relationship between CBF and behavior may be disrupted by this form of neuromodulation.

Levodopa (L-dopa) has been at the forefront of antiparkinsonian therapy for a half century. Recent advances in functional brain imaging have contributed substantially to the understanding of the effects of L-dopa and other dopaminergic treatment on the activity of abnormal motor and cognitive brain circuits in Parkinson's disease patients. Progress has also been made in understanding the functional pathology of dyskinesias, a common side effect of l-dopa treatment, at both regional and network levels. Here, we review these studies, focusing mainly on the new mechanistic insights provided by metabolic brain imaging and network analysis.

The differential diagnosis of parkinsonian syndromes can be challenging, particularly in early disease stages. However, prognosis and therapeutic regimes are not alike in Parkinson disease and atypical parkinsonism, and thus a correct diagnosis at the earliest possible stage is desirable. Over the past two decades, magnetic resonance imaging and radiotracer-based imaging techniques have proven to be helpful tools to enhance the accuracy of clinical diagnosis in these disorders. Here, we review recent advances in neuroimaging for the differential diagnosis of parkinsonian syndromes.

To determine whether the Parkinson disease-related covariance pattern (PDRP) expression is abnormally increased in idiopathic REM sleep behavior disorder (RBD) and whether increased baseline activity is associated with greater individual risk of subsequent phenoconversion.For this cohort study, we recruited 2 groups of RBD and control subjects. Cohort 1 comprised 10 subjects with RBD (63.5 ± 9.4 years old) and 10 healthy volunteers (62.7 ± 8.6 years old) who underwent resting-state metabolic brain imaging with (18)F-fluorodeoxyglucose PET. Cohort 2 comprised 17 subjects with RBD (68.9 ± 4.8 years old) and 17 healthy volunteers (66.6 ± 6.0 years old) who underwent resting brain perfusion imaging with ethylcysteinate dimer SPECT. The latter group was followed clinically for 4.6 ± 2.5 years by investigators blinded to the imaging results. PDRP expression was measured in both RBD groups and compared with corresponding control values.PDRP expression was elevated in both groups of subjects with RBD (cohort 1: p0.04; cohort 2: p0.005). Of the 17 subjects with long-term follow-up, 8 were diagnosed with Parkinson disease or dementia with Lewy bodies; the others did not phenoconvert. For individual subjects with RBD, final phenoconversion status was predicted using a logistical regression model based on PDRP expression and subject age at the time of imaging (r(2) = 0.64, p0.0001).Latent network abnormalities in subjects with idiopathic RBD are associated with a greater likelihood of subsequent phenoconversion to a progressive neurodegenerative syndrome.

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras.

The therapeutic benefits of bilateral capsulotomy for the treatment of refractory obsessive compulsive disorder (OCD) are probably attributed to interruption of the cortico-striato-thalamo-cortical circuitry. We evaluated resting brain metabolism and treatment response in OCD patients using positron emission tomography (PET) imaging. [18F]-fluoro-deoxy-glucose PET was performed in eight OCD patients precapsulotomy and postcapsulotomy. We determined metabolic differences between preoperative images in patients and those in eight age-matched healthy volunteers, and postoperative changes and clinical correlations in the patients. The OCD patients showed widespread metabolic increases in normalized glucose metabolism in the bilateral orbitofrontal cortex and inferior frontal gyrus, cingulate gyrus, and bilateral pons/cerebellum, and metabolic decreases bilaterally in the precentral and lingual gyri. Bilateral capsulotomy resulted in significant metabolic decreases bilaterally in the prefrontal cortical regions, especially in the dorsal anterior cingulate cortex (ACC) and in the medial dorsal thalamus and caudate nucleus. In contrast, metabolism increased bilaterally in the precentral and lingual gyri. Clinical improvement in patients correlated with metabolic changes in the bilateral dorsal ACC and in the right middle occipital gyrus after capsulotomy. This study underscores the importance of the internal capsule in modulating ventral prefrontal and dorsal anterior cingulate neuronal activity in the neurosurgical management of OCD patients.

Heterozygous glucocerebrosidase (GBA) mutations are the leading genetic risk factor for Parkinson disease, yet imaging correlates, particularly transcranial sonography, have not been extensively described.To determine whether GBA mutation heterozygotes with Parkinson disease demonstrate hyperechogenicity of the substantia nigra, transcranial sonography was performed in Ashkenazi Jewish Parkinson disease subjects, tested for the eight most common Gaucher disease mutations and the LRRK2 G2019S mutation, and in controls. [(18)F]-fluorodeoxyglucose or [(18)F]-fluorodopa positron emission tomography is also reported from a subset of Parkinson disease subjects with heterozygous GBA mutations.Parkinson disease subjects with heterozygous GBA mutations (n = 23) had a greater median maximal area of substantia nigral echogenicity compared to controls (n = 34, aSNmax = 0.30 vs. 0.18, p = 0.007). There was no difference in median maximal area of nigral echogenicity between Parkinson disease groups defined by GBA and LRRK2 genotype: GBA heterozygotes; GBA homozygotes/compound heterozygotes (n = 4, aSNmax = 0.27); subjects without LRRK2 or GBA mutations (n = 32, aSNmax = 0.27); LRRK2 heterozygotes/homozygotes without GBA mutations (n = 27, aSNmax = 0.28); and GBA heterozygotes/LRRK2 heterozygotes (n = 4, aSNmax = 0.32, overall p = 0.63). In secondary analyses among Parkinson disease subjects with GBA mutations, maximal area of nigral echogenicity did not differ based on GBA mutation severity or mutation number. [(18)F]-fluorodeoxyglucose (n = 3) and [(18)F]-fluorodopa (n = 2) positron emission tomography in Parkinson disease subjects with heterozygous GBA mutations was consistent with findings in idiopathic Parkinson disease.Both transcranial sonography and positron emission tomography are abnormal in GBA mutation associated Parkinson disease, similar to other Parkinson disease subjects.

To identify brain regions with metabolic changes in DYT11 myoclonus-dystonia (DYT11-MD) relative to control subjects and to compare metabolic abnormalities in DYT11-MD with those found in other forms of hereditary dystonia and in posthypoxic myoclonus.[(18)F]-fluorodeoxyglucose PET was performed in 6 subjects with DYT11-MD (age 30.5 ± 10.1 years) and in 6 nonmanifesting DYT11 mutation carriers (NM-DYT11; age 59.1 ± 8.9 years) representing the parental generation of the affected individuals. These data were compared to scan data from age-matched healthy control subjects using voxel-based whole brain searches and group differences were considered significant at p0.05 (corrected, statistical parametric mapping). As a secondary analysis, overlapping abnormalities were identified by comparisons to hereditary dystonias (DYT1, DYT6, dopa-responsive dystonia) and to posthypoxic myoclonus.We found significant DYT11 genotype-specific metabolic increases in the inferior pons and in the posterior thalamus as well as reductions in the ventromedial prefrontal cortex. Significant phenotype-related increases were present in the parasagittal cerebellum. This latter abnormality was shared with posthypoxic myoclonus, but not with other forms of dystonia. By contrast, all dystonia cohorts exhibited significant metabolic increases in the superior parietal lobule.The findings are consistent with a subcortical myoclonus generator in DYT11-MD, likely involving the cerebellum. By contrast, subtle increases in the superior parietal cortex relate to the additional presence of dystonic symptoms. Although reduced penetrance in DYT11-MD has been attributed to the maternal imprinting epsilon-sarcoglycan mutations, NM-DYT11 carriers showed significant metabolic abnormalities that are not explained by this genetic model.

Importance Parkinson disease (PD) is heterogeneous in symptom manifestation and rate of progression. Identifying factors that influence disease progression could provide mechanistic insight, improve prognostic accuracy, and elucidate novel therapeutic targets. Objective To determine whether GBA mutations and the E326K polymorphism modify PD symptom progression. Design, Setting, and Participants The entire GBA coding region was screened for mutations and E326K in 740 patients with PD enrolled at 7 sites from the PD Cognitive Genetics Consortium. Detailed longitudinal motor and cognitive assessments were performed with patients in the on state. Main Outcomes and Measures Linear regression was used to test for an association between GBA genotype and motor progression, with the Movement Disorder Society–sponsored version of the Unified Parkinson’s Disease Rating Scale Part III (MDS-UPDRS III) score at the last assessment as the outcome and GBA genotype as the independent variable, with adjustment for levodopa equivalent dose, sex, age, disease duration, MDS-UPDRS III score at the first assessment, duration of follow-up, and site. Similar methods were used to examine the association between genotype and tremor and postural instability and gait difficulty (PIGD) scores. To examine the effect of GBA genotype on cognitive progression, patients were classified into those with conversion to mild cognitive impairment or dementia during the study (progression) and those without progression. The association between GBA genotype and progression status was then tested using logistic regression, adjusting for sex, age, disease duration, duration of follow-up, years of education, and site. Results Of the total sample of 733 patients who underwent successful genotyping, 226 (30.8%) were women and 507 (69.2%) were men (mean [SD] age, 68.1 [8.8] years). The mean (SD) duration of follow-up was 3.0 (1.7) years. GBA mutations (β = 4.65; 95% CI, 1.72-7.58; P = .002), E326K (β = 3.42; 95% CI, 0.66-6.17; P = .02), and GBA variants combined as a single group (β = 4.01; 95% CI, 1.95-6.07; P = 1.5 × 10 −4 ) were associated with a more rapid decline in MDS-UPDRS III score. Combined GBA variants (β = 0.38; 95% CI, 0.23-0.53; P = .01) and E326K (β = 0.64; 95% CI, 0.43-0.86; P = .002) were associated with faster progression in PIGD scores, but not in tremor scores. A significantly higher proportion of E326K carriers (10 of 21 [47.6%]; P = .01) and GBA variant carriers (15 of 39 [38.5%]; P = .04) progressed to mild cognitive impairment or dementia. Conclusions and Relevance GBA variants predict a more rapid progression of cognitive dysfunction and motor symptoms in patients with PD, with a greater effect on PIGD than tremor. Thus, GBA variants influence the heterogeneity in symptom progression observed in PD.

Little is known of the precise relationship between the expression of disease-related metabolic patterns and nigrostriatal dopaminergic dysfunction in parkinsonism. We studied 51 subjects with Parkinson's disease (PD) (18 non-demented, 24 demented, and 9 dementia with Lewy bodies) and 127 with atypical parkinsonian syndromes (47 multiple system atrophy (MSA), 38 progressive supranuclear palsy (PSP), and 42 corticobasal syndrome (CBS)) with 18F-fluorodeoxyglucose PET to quantify the expression of previously validated disease-related patterns for PD, MSA, PSP, and CBS and 18F-fluoropropyl-β-CIT PET to quantify caudate and putamen dopamine transporter (DAT) binding. The patients in each group exhibited significant elevations in the expression of the corresponding disease-related pattern ( p

Item does not contain fulltext Essential tremor (ET) is a common cause of significant disability, but its etiologies and pathogenesis are poorly understood. Research has been hampered by the variable definition of ET and by non-standardized research approaches. The National Institute of Neurological Disorders and Stroke (USA) invited experts in ET and related fields to discuss current knowledge, controversies, and gaps in our understanding of ET and to develop recommendations for future research. Discussion focused on phenomenology and phenotypes, therapies and clinical trials, pathophysiology, pathology, and genetics. Across all areas, the need for collaborative and coordinated research on a multinational level was expressed. Standardized data collection using common data elements for genetic, clinical, neurophysiological, and pathological studies was recommended. Large cohorts of patients should be studied prospectively to collect bio-samples, characterize the natural history of the clinical syndrome including patient-oriented outcomes, investigate potential etiologies of various phenotypes, and identify pathophysiological mechanisms. In particular, cellular and system-level mechanisms of tremor oscillations should be elucidated because they may yield effective therapeutic targets and biomarkers. A neuropathology consortium was recommended to standardize postmortem analysis and further characterize neuropathological observations in the cerebellum and elsewhere. Furthermore, genome-wide association studies on large patient cohorts (>10,000 patients) may allow the identification of common genes contributing to risk, and whole exome or genome sequencing may enable the identification of genetic risk and causal mutations in cohorts and well-characterized families.