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

Electroencephalographic spectro-spatial covariance patterns related to phenoconversion in isolated rapid eye movement sleep behavior disorder and their longitudinal trajectories in α-synucleinopathies

STUDY OBJECTIVES

This study aimed to identify electroencephalographic (EEG) spectro-spatial covariance patterns associated with phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD) patients and explore their longitudinal trajectories within α-synucleinopathies.

METHODS

We assessed 47 participants, including 35 patients with iRBD and 12 healthy controls (HC), through baseline eye-closed resting EEGs. Patients with iRBD underwent follow-up EEG assessments and 18 patients with iRBD converted (12 to Parkinson's disease (PD), 6 to dementia with Lewy bodies [DLB]) during follow-up. We derived EEG spectro-spatial covariance patterns for PD-RBD and DLB-RBD from converters and HC. Correlations with motor and cognitive function, baseline distinctions among iRBD converters and nonconverters, and longitudinal trajectories were examined.

RESULTS

At baseline, converters exhibited higher PD-RBD and DLB-RBD beta2 pattern scores compared to nonconverters (each area under curve [AUC] = 0.7751). The delta and alpha spatial patterns effectively distinguished both PD and DLB converters from HC, with the alpha pattern showing high discriminative power (AUC = 0.9097 for PD-RBD, 0.9306 for DLB-RBD). Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III scores correlated positively with PD-RBD and DLB-RBD delta patterns (Spearman's rho = 0.688, p = 0.00014; rho = 0.539, p = 0.0055, respectively), with age and sex as cofactors. Distinct trajectories emerged during follow-up among PD converters, DLB converters, and iRBD nonconverters.

CONCLUSIONS

Unique EEG spectro-spatial patterns specific to PD-RBD and DLB-RBD offer potential as predictive markers for phenoconversion to α-synucleinopathies in iRBD.

PET-based brain molecular connectivity in neurodegenerative disease

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Spatiotemporal patterns of brain iron-oxygen metabolism in patients with Parkinson's disease

OBJECTIVES

Iron deposition and mitochondrial dysfunction are closely associated with the genesis and progression of Parkinson's disease (PD). This study aims to extract susceptibility and oxygen extraction fraction (OEF) values of deep grey matter (DGM) to explore spatiotemporal progression patterns of brain iron-oxygen metabolism in PD.

METHODS

Ninety-five PD patients and forty healthy controls (HCs) were included. Quantitative susceptibility mapping (QSM) and OEF maps were computed from MRI multi-echo gradient echo data. Analysis of covariance (ANCOVA) was used to compare mean susceptibility and OEF values in DGM between early-stage PD (ESP), advanced-stage PD (ASP) patients and HCs. Then Granger causality analysis on the pseudo-time-series of MRI data was applied to assess the causal effect of early altered nuclei on iron content and oxygen extraction in other DGM nuclei.

RESULTS

The susceptibility values in substantia nigra (SN), red nucleus, and globus pallidus (GP) significantly increased in PD patients compared with HCs, while the iron content in GP did not elevate obviously until the late stage. The mean OEF values for the caudate nucleus, putamen, and dentate nucleus were higher in ESP patients than in ASP patients or/and HCs. We also found that iron accumulation progressively expands from the midbrain to the striatum. These alterations were correlated with clinical features and improved AUC for early PD diagnosis to 0.824.

CONCLUSIONS

Abnormal cerebral iron deposition and tissue oxygen utilization in PD measured by QSM and OEF maps could reflect pathological alterations in neurodegenerative processes and provide valuable indicators for disease identification and management.

CLINICAL RELEVANCE STATEMENT

Noninvasive assessment of cerebral iron-oxygen metabolism may serve as clinical evidence of pathological changes in PD and improve the validity of diagnosis and disease monitoring.

KEY POINTS

• Quantitative susceptibility mapping and oxygen extraction fraction maps indicated the cerebral pathology of abnormal iron accumulation and oxygen metabolism in Parkinson's disease. • Iron deposition is mainly in the midbrain, while altered oxygen metabolism is concentrated in the striatum and cerebellum. • The susceptibility and oxygen extraction fraction values in subcortical nuclei were associated with clinical severity.

Patterns of regional cerebral hypoperfusion in early Parkinson's disease: Clinical implications

INTRODUCTION

This study aimed to investigate whether regional cerebral perfusion patterns on early-phase 18F-FP-CIT PET scans, which is typically coupled to cerebral metabolism, predict the long-term prognosis of Parkinson's disease (PD).

METHODS

We enrolled 397 drug-naïve patients with early-stage PD who underwent dual-phase 18F-FP-CIT PET scans. After quantifying the early-phase 18F-FP-CIT PET images, cluster analysis was performed to delineate the PD subtypes according to the patterns of regional cerebral perfusion. We compared the risk of developing levodopa-induced dyskinesia (LID), wearing-off, freezing of gait (FOG), and dementia between the PD subtypes.

RESULTS

Cluster analysis classified patients into three subtypes: cluster 1 (relatively preserved cortical uptake; n = 175), cluster 2 (decreased uptake in the frontal, parietal, and temporal regions; n = 151), and cluster 3 (decreased uptake in more extensive regions, additionally involving the lateral occipital regions; n = 71). Cluster 1 was characterized by a younger age-of-onset, less severe motor deficits, less severely decreased 18F-FP-CIT binding in the caudate, and better cognitive performance. Cluster 3 was characterized by an older age-of-onset, more severe motor deficits, and poorer cognitive performance. Cluster 2 was intermediate between clusters 1 and 3. Cox regression analyses demonstrated that clusters 2 and 3 had a higher risk for dementia conversion than cluster 1, whereas the risk for developing LID, wearing-off, and FOG did not differ among the clusters.

CONCLUSION

The patterns of regional cerebral perfusion can provide information on long-term prognosis with regards to cognitive, but not motor aspects of patients with early-stage PD.

Investigating the aspect of asymmetry in brain-first versus body-first Parkinson's disease

Parkinson's disease (PD) is characterized by a progressive loss of dopaminergic neurons in the substantia nigra. Recent literature has proposed two subgroups of PD. The "body-first subtype" is associated with a prodrome of isolated REM-sleep Behavior Disorder (iRBD) and a relatively symmetric brain degeneration. The "brain-first subtype" is suggested to have a more asymmetric degeneration and a prodromal stage without RBD. This study aims to investigate the proposed difference in symmetry of the degeneration pattern in the presumed body and brain-first PD subtypes. We analyzed 123I-FP-CIT (DAT SPECT) and 18F-FDG PET brain imaging in three groups of patients (iRBD, n = 20, de novo PD with prodromal RBD, n = 22, and de novo PD without RBD, n = 16) and evaluated dopaminergic and glucose metabolic symmetry. The RBD status of all patients was confirmed with video-polysomnography. The PD groups did not differ from each other with regard to the relative or absolute asymmetry of DAT uptake in the putamen (p = 1.0 and p = 0.4, respectively). The patient groups also did not differ from each other with regard to the symmetry of expression of the PD-related metabolic pattern (PDRP) in each hemisphere. The PD groups had no difference in symmetry considering mean FDG uptake in left and right regions of interest and generally had the same degree of symmetry as controls, while the iRBD patients had nine regions with abnormal left-right differences (p < 0.001). Our findings do not support the asymmetry aspect of the "body-first" versus "brain-first" hypothesis.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

PURPOSE

Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA).

METHODS

FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level.

RESULTS

Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912).

CONCLUSION

Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

99mTc-HMPAO SPECT Perfusion Signatures Associated With Clinical Progression in Patients With Isolated REM Sleep Behavior Disorder

BACKGROUND AND OBJECTIVES

Idiopathic/isolated REM sleep behavior disorder (iRBD) is associated with dementia with Lewy bodies and Parkinson disease. Despite evidence of abnormal cerebral perfusion in iRBD, there is currently no pattern that can predict whether an individual will develop dementia with Lewy bodies or Parkinson disease. The objective was to identify a perfusion signature associated with conversion to dementia with Lewy bodies in iRBD.

METHODS

Patients with iRBD underwent video-polysomnography, neurologic and neuropsychological assessments, and baseline 99mTc-HMPAO SPECT to assess relative cerebral blood flow. Partial least squares correlation was used to identify latent variables that maximized covariance between 27 clinical features and relative gray matter perfusion. Patient-specific scores on the latent variables were used to test the association with conversion to dementia with Lewy bodies compared with that with Parkinson disease. The signature's expression was also assessed in 24 patients with iRBD who underwent a second perfusion scan, 22 healthy controls, and 19 individuals with Parkinson disease.

RESULTS

Of the 137 participants, 93 underwent SPECT processing, namely 52 patients with iRBD (67.9 years, 73% men), 19 patients with Parkinson disease (67.3 years, 37% men), and 22 controls (67.0 years, 73% men). Of the 47 patients with iRBD followed up longitudinally (4.5 years), 12 (26%) developed a manifest synucleinopathy (4 dementia with Lewy bodies and 8 Parkinson disease). Analysis revealed 2 latent variables between relative blood flow and clinical features: the first was associated with a broad set of features that included motor, cognitive, and perceptual variables, age, and sex; the second was mostly associated with cognitive features and RBD duration. When brought back into the patient's space, the expression of the first variable was associated with conversion to a manifest synucleinopathy, whereas the second was associated with conversion to dementia with Lewy bodies. The expression of the patterns changed over time and was associated with worse motor features.

DISCUSSION

This study identified a brain perfusion signature associated with cognitive impairment in iRBD and transition to dementia with Lewy bodies. This signature, which can be derived from individual scans, has the potential to be developed into a biomarker that predicts dementia with Lewy bodies in at-risk individuals.

The remodeling of metabolic brain pattern in patients with extracranial diffuse large B-cell lymphoma

BACKGROUND

Owing to the advances in diagnosis and therapy, survival or remission rates for lymphoma have improved prominently. Apart from the lymphoma- and chemotherapy-related somatic symptom burden, increasing attention has been drawn to the health-related quality of life. The application of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) has been routinely recommended for the staging and response assessment of FDG-avid lymphoma. However, up till now, only a few researches have investigated the brain metabolic impairments in patients with pre-treatment lymphoma. The determination of the lymphoma-related metabolic brain pattern would facilitate exploring the tailored therapeutic regimen to alleviate not only the physiological, but also the psychological symptoms. In this retrospective study, we aimed to establish the diffuse large B-cell lymphoma-related pattern (DLBCLRP) of metabolic brain network and investigate the correlations between DLBCLRP and several indexes of the staging and response assessment.

RESULTS

The established DLBCLRP was characterized by the increased metabolic activity in bilateral cerebellum, brainstem, thalamus, striatum, hippocampus, amygdala, parahippocampal gyrus and right middle temporal gyrus and by the decreased metabolic activity in bilateral occipital lobe, parietal lobe, anterior cingulate gyrus, midcingulate cortex and medial frontal gyrus. Significant difference in the baseline expression of DLBCLRP was found among complete metabolic response (CMR), partial metabolic response (PMR) and progressive metabolic disease (PMD) groups (P < 0.01). DLBCLRP expressions were also significantly or tended to be positively correlated with international prognostic index (IPI) (rs = 0.306, P < 0.05), lg(total metabolic tumor volume, TMTV) (r = 0.298, P < 0.05) and lg(total lesion glycolysis, TLG) (r = 0.233, P = 0.064). Though no significant correlation of DLBCLRP expression was found with Ann Arbor staging or tumor SUVmax (P > 0.05), the post-treatment declines of DLBCLRP expression were significantly positively correlated with Ann Arbor staging (rs = 0.284, P < 0.05) and IPI (rs = 0.297, P < 0.05).

CONCLUSIONS

The proposed DLBCLRP would lay the foundation for further investigating the cerebral dysfunction related to DLBCL itself and/or treatments. Besides, the expression of DLBCLRP was associated with the tumor burden of lymphoma, implying a potential biomarker for prognosis.

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

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

Differential Implications of Cerebral Hypoperfusion and Hyperperfusion in Parkinson's Disease

BACKGROUND

Patients with Parkinson's disease (PD) exhibit widespread brain perfusion changes.

OBJECTIVE

This study investigated whether cerebral regions with hypoperfusion and hyperperfusion have differential effects on motor and cognitive symptoms in PD using early-phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (18 F-FP-CIT) positron emission tomography (PET) scans.

METHODS

We enrolled 394 patients with newly diagnosed PD who underwent dual-phase 18 F-FP-CIT PET scans. Indices reflecting associated changes in regional cerebral hypoperfusion and hyperperfusion on early-phase 18 F-FP-CIT PET scans were calculated as PD[hypo] and PD[hyper] , respectively. The associations of PD[hypo] and PD[hyper] on motor and cognitive symptoms at baseline were assessed using multivariate linear regression. Also, Cox regression and linear mixed models were performed to investigate the effects of baseline PD[hypo] and PD[hyper] on longitudinal outcomes.

RESULTS

There was a weak correlation between PD[hypo] and PD[hyper] (γ = -0.19, P < 0.001). PD[hypo] was associated with baseline Unified Parkinson's Disease Rating Scale Part III scores (β = -1.02, P = 0.045), rapid increases in dopaminergic medications (β = -18.02, P < 0.001), and a higher risk for developing freezing of gait (hazard ratio [HR] = 0.67, P = 0.019), whereas PD[hyper] was not associated. Regarding cognitive function, PD[hypo] was more relevant to the baseline cognitive performance levels of visuospatial, memory, and frontal/executive function than PD[hyper] . However, greater PD[hyper] was associated with future dementia conversion (HR = 1.43, P = 0.004), whereas PD[hypo] was not associated.

CONCLUSIONS

These findings suggest that PD[hypo] and PD[hyper] may differentially affect motor and cognitive functions in patients with PD. © 2023 International Parkinson and Movement Disorder Society.

Validation of the REM behaviour disorder phenoconversion-related pattern in an independent cohort

BACKGROUND

A brain glucose metabolism pattern related to phenoconversion in patients with idiopathic/isolated REM sleep behaviour disorder (iRBDconvRP) was recently identified. However, the validation of the iRBDconvRP in an external, independent group of iRBD patients is needed to verify the reproducibility of such pattern, so to increase its importance in clinical and research settings. The aim of this work was to validate the iRBDconvRP in an independent group of iRBD patients.

METHODS

Forty iRBD patients (70 ± 5.59 years, 19 females) underwent brain [18F]FDG-PET in Seoul National University. Thirteen patients phenoconverted at follow-up (7 Parkinson disease, 5 Dementia with Lewy bodies, 1 Multiple system atrophy; follow-up time 35 ± 20.56 months) and 27 patients were still free from parkinsonism/dementia after 62 ± 29.49 months from baseline. We applied the previously identified iRBDconvRP to validate its phenoconversion prediction power.

RESULTS

The iRBDconvRP significantly discriminated converters from non-converters iRBD patients (p = 0.016; Area under the Curve 0.74, Sensitivity 0.69, Specificity 0.78), and it significantly predicted phenoconversion (Hazard ratio 4.26, C.I.95%: 1.18-15.39).

CONCLUSIONS

The iRBDconvRP confirmed its robustness in predicting phenoconversion in an independent group of iRBD patients, suggesting its potential role as a stratification biomarker for disease-modifying trials.

Parkinson's disease progression: Increasing expression of an invariant common core subnetwork

Notable success has been achieved in the study of neurodegenerative conditions using reduction techniques such as principal component analysis (PCA) and sparse inverse covariance estimation (SICE) in positron emission tomography (PET) data despite their widely differing approach. In a recent study of SICE applied to metabolic scans from Parkinson's disease (PD) patients, we showed that by using PCA to prespecify disease-related partition layers, we were able to optimize maps of functional metabolic connectivity within the relevant networks. Here, we show the potential of SICE, enhanced by disease-specific subnetwork partitions, to identify key regional hubs and their connections, and track their associations in PD patients with increasing disease duration. This approach enabled the identification of a core zone that included elements of the striatum, pons, cerebellar vermis, and parietal cortex and provided a deeper understanding of progressive changes in their connectivity. This subnetwork constituted a robust invariant disease feature that was unrelated to phenotype. Mean expression levels for this subnetwork increased steadily in a group of 70 PD patients spanning a range of symptom durations between 1 and 21 years. The findings were confirmed in a validation sample of 69 patients with up to 32 years of symptoms. The common core elements represent possible targets for disease modification, while their connections to external regions may be better suited for symptomatic treatment.

The effect of Parkin gene S/N 167 polymorphism on resting spontaneous brain functional activity in Parkinson's Disease

BACKGROUND

Genetic susceptibility plays a significant role in Parkinson's disease (PD) development. Carriers of the Parkin S/N167 mutation may have an increased risk of PD and altered spontaneous brain activity.

OBJECTIVE

This study aims to investigate the potential pathogenesis of PD through a comparative analysis of the amplitude of low-frequency fluctuations (ALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) of subjects with Parkin gene S/N 167 polymorphisms, and to examine the association between spontaneous brain activity and clinical scale scores of PD.

METHODS

A total of 69 PD patients and 84 healthy controls (HC) were included in the study. Each subject was genotyped for the Parkin gene S/N 167 polymorphism and underwent rs-fMRI scans. ALFF analysis was employed to evaluate the relationship among genotypes, interactive brain regions, and clinical symptoms in PD.

RESULTS

PD patients exhibited decreased ALFF values in the right anterior lobe and vermis of the cerebellum compared to HC. No significant interaction was found between the gene's main effect and the "group × genotype" effect on brain ALFF values. One-factor ANOVA revealed no significant difference in ALFF values between PD subgroups; however, the ALFF values in the right anterior lobe and vermis of the cerebellum were lower in the PD-G and PD-GA groups compared to the HC-G and HC-GA groups. Spearman correlation analysis demonstrated that ALFF values in the PD-GG and PD-GA groups were negatively associated with UPDRS-III scores in the bilateral lingual gyrus (Lingual R/L).

CONCLUSION

Parkin gene S/N 167 polymorphisms may influence brain functional activity in specific brain regions, and ALFF values are associated with motor symptoms in PD patients.

Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies

BACKGROUND

Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies.

METHODS

We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA).

RESULTS

The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941).

CONCLUSIONS

SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.

Case report: Levodopa-responsive parkinsonism with akinetic mutism after ventriculo-peritoneal shunt

Background

Parkinsonism and akinetic mutism (AM) following ventriculo-peritoneal shunt (VPS) without underdrainage used to be considered rare, but may be underdiagnosed in daily clinical practice. Although the pathophysiology is still unclear, in several case reports, the parkinsonism and AM after VPS shows responsiveness to dopaminergic treatment.

Case presentation

We report a 19-year-old male that presented with severe parkinsonism and AM after VPS. Meanwhile, ¹⁸F-FDG-PET showed a cortical and subcortical hypometabolism. Fortunately, levodopa dramatically improved patient's symptoms and brain hypometabolism. This report provides support for the possibility that dopamine deficiency inhibits brain metabolism, and further elucidates the pathogenesis of parkinsonism and AM.

Conclusion

This report highlights the presentation of a treatable parkinsonism and points out that Levodopa and/or dopamine agonist should be the first choice if the patients develop parkinson-like symptoms after VPS.

Novel insights into Parkin-mediated mitochondrial dysfunction and neuroinflammation in Parkinson's disease

Mutations in PRKN cause the second most common genetic form of Parkinson's disease (PD)-a debilitating movement disorder that is on the rise due to population aging in the industrial world. PRKN codes for an E3 ubiquitin ligase that has been well established as a key regulator of mitophagy. Together with PTEN-induced kinase 1 (PINK1), Parkin controls the lysosomal degradation of depolarized mitochondria. But Parkin's functions go well beyond mitochondrial clearance: the versatile protein is involved in mitochondria-derived vesicle formation, cellular metabolism, calcium homeostasis, mitochondrial DNA maintenance, mitochondrial biogenesis, and apoptosis induction. Moreover, Parkin can act as a modulator of different inflammatory pathways. In the current review, we summarize the latest literature concerning the diverse roles of Parkin in maintaining a healthy mitochondrial pool. Moreover, we discuss how these recent discoveries may translate into personalized therapeutic approaches not only for PRKN-PD patients but also for a subset of idiopathic cases.

Functional brain networks in the evaluation of patients with neurodegenerative disorders

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

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.

Metabolic hormones mediate cognition

Recent biochemical and behavioural evidence indicates that metabolic hormones not only regulate energy intake and nutrient content, but also modulate plasticity and cognition in the central nervous system. Disruptions in metabolic hormone signalling may provide a link between metabolic syndromes like obesity and diabetes, and cognitive impairment. For example, altered metabolic homeostasis in obesity is a strong determinant of the severity of age-related cognitive decline and neurodegenerative disease. Here we review the evidence that eating behaviours and metabolic hormones-particularly ghrelin, leptin, and insulin-are key players in the delicate regulation of neural plasticity and cognition. Caloric restriction and antidiabetic therapies, both of which affect metabolic hormone levels can restore metabolic homeostasis and enhance cognitive function. Thus, metabolic hormone pathways provide a promising target for the treatment of cognitive decline.

Brain Glucose Hypometabolism and Iron Accumulation in Different Brain Regions in Alzheimer's and Parkinson's Diseases

The aim of this study was to examine the relationship between the presence of glucose hypometabolism (GHM) and brain iron accumulation (BIA), two potential pathological mechanisms in neurodegenerative disease, in different regions of the brain in people with late-onset Alzheimer's disease (AD) or Parkinson's disease (PD). Studies that conducted fluorodeoxyglucose positron emission tomography (FDG-PET) to map GHM or quantitative susceptibility mapping-magnetic resonance imaging (QSM-MRI) to map BIA in the brains of patients with AD or PD were reviewed. Regions of the brain where GHM or BIA were reported in each disease were compared. In AD, both GHM and BIA were reported in the hippocampus, temporal, and parietal lobes. GHM alone was reported in the cingulate gyrus, precuneus and occipital lobe. BIA alone was reported in the caudate nucleus, putamen and globus pallidus. In PD, both GHM and BIA were reported in thalamus, globus pallidus, putamen, hippocampus, and temporal and frontal lobes. GHM alone was reported in cingulate gyrus, caudate nucleus, cerebellum, and parietal and occipital lobes. BIA alone was reported in the substantia nigra and red nucleus. GHM and BIA are observed independent of one another in various brain regions in both AD and PD. This suggests that GHM is not always necessary or sufficient to cause BIA and vice versa. Hypothesis-driven FDG-PET and QSM-MRI imaging studies, where both are conducted on individuals with AD or PD, are needed to confirm or disprove the observations presented here about the potential relationship or lack thereof between GHM and BIA in AD and PD.

Cdk5 phosphorylation-induced SIRT2 nuclear translocation promotes the death of dopaminergic neurons in Parkinson's disease

NAD-dependent protein deacetylase Sirtuin 2 (SIRT2), which regulates several cellular pathways by deacetylating multiple substrates, has been extensively studied in the context of Parkinson’s disease (PD). Although several studies based on the MPTP model of PD show that SIRT2 deletion can protect against dopaminergic neuron loss, the precise mechanisms of SIRT2-mediated neuronal death have largely remained unknown. Here, we show that SIRT2 knockout can effectively ameliorate anomalous behavioral phenotypes in transgenic mouse models of PD. Importantly, in both cellular and animal models of PD, it was observed that SIRT2 translocates from the cytoplasm to the nucleus. Further, the nuclear translocation of SIRT2 promotes neuronal death. Moreover, the cyclin-dependent kinase 5 (Cdk5)-mediated phosphorylation of SIRT2 at the Ser331 and Ser335 sites appears to be necessary for such nuclear translocation. Taken together, the results provide insights into the mechanisms involved in the regulation of neuronal death during PD progression via the Cdk5-dependent nuclear–cytoplasmic shuttling of SIRT2.

Alterations of Striatal Subregions in a Prion Protein Gene V180I Mutation Carrier Presented as Frontotemporal Dementia With Parkinsonism

Objective

To explore the roles of striatal subdivisions in the pathogenesis of frontotemporal dementia with parkinsonism (FTDP) in a patient resulting from prion protein gene (PRNP) mutation.

Methods

This patient received clinical interviews and underwent neuropsychological assessments, genetic testing, [18F]-fluorodeoxyglucose positron emission tomography ([18F]-FDG PET)/MRI, and [18F]-dihydrotetrabenazine positron emission tomography ([18F]-DTBZ PET)/CT. Region-of-interest analysis was conducted concerning metabolism, and dopamine transport function between this patient and 12 controls, focusing on the striatum subregions according to the Oxford-GSK-Imanova Striatal Connectivity Atlas.

Results

A 64-year-old man initially presented with symptoms of motor dysfunction and subsequently behavioral and personality changes. FTDP was initially suspected. Sequence analysis disclosed a valine to isoleucine at codon 180 in PRNP. Compared to controls, this patient had a severe reduction (> 2SD) of standard uptake value ratio (SUVR) in the limbic and executive subregions but relative retention of metabolism in rostral motor and caudal motor subregions using [18F]-FDG PET/MRI, and the SUVR decreased significantly across the striatal in [18F]-DTBZ PET/CT, especially in the rostral motor and caudal motor subregions.

Conclusion

The alteration of frontal striatal loops may be involved in cognitive impairment in FTDP, and the development of parkinsonism in FTDP may be primarily due to the involvement of the presynaptic nigrostriatal loops in PRNP V180I mutation.

A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism

Differential diagnosis of parkinsonism early upon symptom onset is often challenging for clinicians and stressful for patients. Several neuroimaging methods have been previously evaluated; however specific routines remain to be established. The aim of this study was to systematically assess the diagnostic accuracy of a previously developed ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) based automated algorithm in the diagnosis of parkinsonian syndromes, including unpublished data from a prospective cohort. A series of 35 patients prospectively recruited in a movement disorder clinic in Stockholm were assessed, followed by systematic literature review and meta-analysis. In our cohort, automated image-based classification method showed excellent sensitivity and specificity for Parkinson Disease (PD) vs. atypical parkinsonian syndromes (APS), in line with the results of the meta-analysis (pooled sensitivity and specificity 0.84; 95% CI 0.79-0.88 and 0.96; 95% CI 0.91 -0.98, respectively). In conclusion, FDG-PET automated analysis has an excellent potential to distinguish between PD and APS early in the disease course and may be a valuable tool in clinical routine as well as in research applications.

Amyotrophic lateral sclerosis with SOD1 mutations shows distinct brain metabolic changes

Purpose

Neuropathological data suggest that ALS with SOD1 mutations (SOD1-ALS) is a distinct form of ALS. We evaluated brain metabolic changes characterizing SOD1-ALS as compared to sporadic ALS (sALS), employing ¹⁸fluorodeoxyglucose-positron-emission tomography (¹⁸F-FDG-PET).

Methods

We included 18 SOD1-ALS patients, 40 healthy controls (HC), and 46 sALS patients without mutations in SOD1, TARDBP, FUS, and C9ORF72, randomly selected from 665 subjects who underwent brain ¹⁸F-FDG-PET at diagnosis between 2008 and 2019 at the ALS Centre of Turin. We excluded patients with frontotemporal dementia. We used the full factorial design in SPM12 to evaluate whether differences among groups exist overall. In case the hypothesis was confirmed, group comparisons were performed through the two-sample t-test model of SPM12. In all the analyses, the height threshold was P < 0.001 (P < 0.05 FWE-corrected at cluster level).

Results

The full factorial design resulted in a significant main effect of groups. We identified a relative hypometabolism in sALS patients compared to SOD1-ALS cases in the right precentral and medial frontal gyrus, right paracentral lobule, and bilateral postcentral gyrus. SOD1 patients showed a relative hypermetabolism as compared to HC in the right precentral gyrus and paracentral lobule. As compared to HC, sALS patients showed relative hypometabolism in frontal, temporal, and occipital cortices.

Conclusion

SOD1-ALS was characterized by a relative hypermetabolism in the motor cortex as compared to sALS and HC. Since promising, targeted, therapeutic strategies are upcoming for SOD1-ALS, our data support the use of PET to study disease pathogenesis and to track its course in clinical trials, in both asymptomatic and symptomatic mutation carriers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05668-7.

Metabolic correlates of olfactory dysfunction in COVID-19 and Parkinson's disease (PD) do not overlap

Purpose

Hyposmia is a common feature of COVID-19 and Parkinson’s disease (PD). As parkinsonism has been reported after COVID-19, a link has been hypothesized between SARS-CoV2 infection and PD. We aimed to evaluate brain metabolic correlates of isolated persistent hyposmia after mild-to-moderate COVID-19 and to compare them with metabolic signature of hyposmia in drug-naïve PD patients.

Methods

Forty-four patients who experienced hyposmia after SARS-COV2 infection underwent brain [¹⁸F]-FDG PET in the first 6 months after recovery. Olfaction was assessed by means of the 16-item “Sniffin’ Sticks” test and patients were classified as with or without persistent hyposmia (COVID-hyposmia and COVID-no-hyposmia respectively). Brain [¹⁸F]-FDG PET of post-COVID subgroups were compared in SPM12. COVID-hyposmia patients were also compared with eighty-two drug-naïve PD patients with hyposmia. Multiple regression analysis was used to identify correlations between olfactory test scores and brain metabolism in patients’ subgroups.

Results

COVID-hyposmia patients (n = 21) exhibited significant hypometabolism in the bilateral gyrus rectus and orbitofrontal cortex with respect to COVID-non-hyposmia (n = 23) (p < 0.002) and in middle and superior temporal gyri, medial/middle frontal gyri, and right insula with respect to PD-hyposmia (p < 0.012). With respect to COVID-hyposmia, PD-hyposmia patients showed hypometabolism in inferior/middle occipital gyri and cuneus bilaterally. Olfactory test scores were directly correlated with metabolism in bilateral rectus and medial frontal gyri and in the right middle temporal and anterior cingulate gyri in COVID-hyposmia patients (p < 0.006) and with bilateral cuneus/precuneus and left lateral occipital cortex in PD-hyposmia patients (p < 0.004).

Conclusion

Metabolic signature of persistent hyposmia after COVID-19 encompasses cortical regions involved in olfactory perception and does not overlap metabolic correlates of hyposmia in PD.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

Rapid Eye Movement Sleep Behavior Disorder: Abnormal Cardiac Image and Progressive Abnormal Metabolic Brain Pattern

BACKGROUND

Isolated rapid eye movement sleep behavior disorder (iRBD) is prodromal for α-synucleinopathies.

OBJECTIVE

The aim of this study was to determine whether pathological cardiac [¹²³ I]meta-iodobenzylguanidine scintigraphy ([¹²³ I]MIBG) is associated with progression of [¹⁸ F]fluorodeoxyglucose-positron emission tomography-based Parkinson's disease (PD)-related brain pattern (PDRP) expression in iRBD.

METHODS

Seventeen subjects with iRBD underwent [¹⁸ F]fluorodeoxyglucose-positron emission tomography brain imaging twice ~3.6 years apart. In addition, [¹²³ I]MIBG and [¹²³ I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane single-photon emission computed tomography ([¹²³ I]FP-CIT-SPECT) at baseline were performed. Olfactory, cognitive, and motor functions were tested annually.

RESULTS

Twelve of 17 subjects had pathological [¹²³ I]MIBG. At baseline, 6 of 12 of these expressed the PDRP (suprathreshold PDRP z score). At follow-up, 12 of 17 subjects had suprathreshold PDRP z scores, associated with pathological [¹²³ I]MIBG in 92% and with pathological [¹²³ I]FP-CIT-SPECT in 75%. Subjects with pathological [¹²³ I]MIBG had higher PDRP z score change per year (P = 0.027). Three subjects phenoconverted to PD; all had pathological [¹²³ I]MIBG and [¹²³ I]FP-CIT-SPECT, suprathreshold baseline PDRP z scores, and hyposmia.

CONCLUSIONS

Pathological [¹²³ I]MIBG was associated with progressive and suprathreshold PDRP z scores at follow-up. Abnormal [¹²³ I]MIBG likely identifies iRBD as prodromal PD earlier than pathological [¹²³ I]FP-CIT-SPECT. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

High-resolution pediatric age-specific 18F-FDG PET template: a pilot study in epileptogenic focus localization

Background

PET imaging has been widely used in diagnosis of neurological disorders; however, its application to pediatric population is limited due to lacking pediatric age–specific PET template. This study aims to develop a pediatric age–specific PET template (PAPT) and conduct a pilot study of epileptogenic focus localization in pediatric epilepsy.

Methods

We recruited 130 pediatric patients with epilepsy and 102 age-matched controls who underwent ¹⁸F-FDG PET examination. High-resolution PAPT was developed by an iterative nonlinear registration-averaging optimization approach for two age ranges: 6–10 years (n = 17) and 11–18 years (n = 50), respectively. Spatial normalization to the PAPT was evaluated by registration similarities of 35 validation controls, followed by estimation of potential registration biases. In a pilot study, epileptogenic focus was localized by PAPT-based voxel-wise statistical analysis, compared with multi-disciplinary team (MDT) diagnosis, and validated by follow-up of patients who underwent epilepsy surgery. Furthermore, epileptogenic focus localization results were compared among three templates (PAPT, conventional adult template, and a previously reported pediatric linear template).

Results

Spatial normalization to the PAPT significantly improved registration similarities (P < 0.001), and nearly eliminated regions of potential biases (< 2% of whole brain volume). The PAPT-based epileptogenic focus localization achieved a substantial agreement with MDT diagnosis (Kappa = 0.757), significantly outperforming localization based on the adult template (Kappa = 0.496) and linear template (Kappa = 0.569) (P < 0.05). The PAPT-based localization achieved the highest detection rate (89.2%) and accuracy (80.0%). In postsurgical seizure-free patients (n = 40), the PAPT-based localization also achieved a substantial agreement with resection areas (Kappa = 0.743), and the highest detection rate (95%) and accuracy (80.0%).

Conclusion

The PAPT can significantly improve spatial normalization and epileptogenic focus localization in pediatric epilepsy. Future pediatric neuroimaging studies can also benefit from the unbiased spatial normalization by PAPT.

Trial registration.

NCT04725162: https://clinicaltrials.gov/ct2/show/NCT04725162

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05611-w.

Autoimmune cerebellar hypermetabolism: Report of three cases and literature overview

We report three cases of vermian cerebellar hypermetabolism in patients with autoimmune encephalitis. One of our patients was positive for anti-Ma2 antibodies and one for anti-Zic4 antibodies while the remaining patient did not present any known antibodies. The seronegative patient deteriorated after immune checkpoint inhibitor treatment for a pulmonary adenocarcinoma and improved with immunosuppressive drugs, which is in favour of an underlying autoimmune mechanism. They all presented with subacute neurological symptoms. Brain magnetic resonance imaging was normal except in one patient, where hyperintensities were present on FLAIR sequence around the third ventricle and the cerebral aqueduct. ¹⁸F-FDG brain positron emission tomography with computed tomography (¹⁸F-FDG PET-CT) demonstrated an unusual vermian cerebellar hypermetabolism in the three cases. While cerebellar hypermetabolism on ¹⁸F-FDG PET-CT has been described in various neurological diseases, such vermian - and more broadly cerebellar - hypermetabolism was seldom described in previous studies on autoimmune encephalitis. When differential diagnoses have been ruled out, this pattern may be of interest for the positive diagnosis of autoimmune encephalitis in difficult diagnostic cases.

Circuit imaging biomarkers in preclinical and prodromal Parkinson's disease

Parkinson's disease (PD) commences several years before the onset of motor features. Pathophysiological understanding of the pre-clinical or early prodromal stages of PD are essential for the development of new therapeutic strategies. Two categories of patients are ideal to study the early disease stages. Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents a well-known prodromal stage of PD in which pathology is presumed to have reached the lower brainstem. The majority of patients with iRBD will develop manifest PD within years to decades. Another category encompasses non-manifest mutation carriers, i.e. subjects without symptoms, but with a known mutation or genetic variant which gives an increased risk of developing PD. The speed of progression from preclinical or prodromal to full clinical stages varies among patients and cannot be reliably predicted on the individual level. Clinical trials will require inclusion of patients with a predictable conversion within a limited time window. Biomarkers are necessary that can confirm pre-motor PD status and can provide information regarding lead time and speed of progression. Neuroimaging changes occur early in the disease process and may provide such a biomarker. Studies have focused on radiotracer imaging of the dopaminergic nigrostriatal system, which can be assessed with dopamine transporter (DAT) single photon emission computed tomography (SPECT). Loss of DAT binding represents an effect of irreversible structural damage to the nigrostriatal system. This marker can be used to monitor disease progression and identify individuals at specific risk for phenoconversion. However, it is known that changes in neuronal activity precede structural changes. Functional neuro-imaging techniques, such as ¹⁸F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography (¹⁸F-FDG PET) and functional magnetic resonance imaging (fMRI), can be used to model the effects of disease on brain networks when combined with advanced analytical methods. Because these changes occur early in the disease process, functional imaging studies are of particular interest in prodromal PD diagnosis. In addition, fMRI and ¹⁸F-FDG PET may be able to predict a specific future phenotype in prodromal cohorts, which is not possible with DAT SPECT. The goal of the current review is to discuss the network-level brain changes in pre-motor PD.

Implication of metabolic and dopamine transporter PET in dementia with Lewy bodies

To evaluate the implication of ¹⁸F-fluorodeoxyglucose (FDG)- and dopamine transporter (DAT)-positron emission tomography (PET) in the diagnosis and clinical symptoms of dementia with Lewy bodies (DLB), 55 DLB patients and 49 controls underwent neuropsychological evaluation and FDG-, DAT-, and ¹⁸F-Florbetaben (FBB) PET. DAT- and FDG-uptake and FDG/DAT ratio were measured in the anterior and posterior striatum. The first principal component (PC1) of FDG subject residual profiles was identified for each subject. Receiver operating characteristic curve analyses for the diagnosis of DLB were performed using FDG- and DAT-PET biomarkers as predictors, and general linear models for motor severity and cognitive scores were performed adding FBB standardized uptake value ratio as a predictor. Increased metabolism in the bilateral putamen, vermis, and somato-motor cortices, which characterized PC1, was observed in the DLB group, compared to the control group. A combination of posterior putamen FDG/DAT ratio and PC1 showed the highest diagnostic accuracy (91.8% sensitivity and 96.4% specificity), which was significantly greater than that obtained by DAT uptake alone. Striatal DAT uptake and PC1 independently contributed to motor severity and language, memory, frontal/executive, and general cognitive dysfunction in DLB patients, while only PC1 contributed to attention and visuospatial dysfunction.

Emerging role of metabolomics in protein conformational disorders

Introduction: Metabolomics focuses on interactions among different metabolites associated with various cellular functions in cells, tissues, and organs. In recent years, metabolomics has emerged as a powerful tool to identify perturbed metabolites, pathways influenced by the environment, for protein conformational diseases (PCDs) and also offers wide clinical application.Area Covered: This review provides a brief overview of recent advances in metabolomics as applied to identify metabolic variations in PCDs, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, prion disease, and cardiac amyloidosis. The 'PubMed' and 'Google Scholar' database search methods have been used to screen the published reports with key search terms: metabolomics, biomarkers, and protein conformational disorders.Expert opinion: Metabolomics is the large-scale study of metabolites and is deemed to overwhelm other omics. It plays a crucial role in finding variations in diseases due to protein conformational changes. However, many PCDs are yet to be identified. Metabolomics is still an emerging field; there is a need for new high-resolution analytical techniques and more studies need to be carried out to generate new information.

Dopaminergic and Serotonergic Degeneration and Cortical [18 F]Fluorodeoxyglucose Positron Emission Tomography in De Novo Parkinson's Disease

BACKGROUND

Degeneration of the nigrostriatal dopaminergic (DA) and the raphe-thalamic serotonergic (SE) systems is among the earliest changes observed in Parkinson's disease (PD). The consequences of those changes on brain metabolism, especially regarding their impact on the cortex, are poorly understood.

OBJECTIVES

Using multi-tracer molecular imaging, we assessed in a cohort of drug-naive PD patients the association between cortical metabolism and DA and SE system deafferentation of either striatum or thalamus, and we explored whether this association was mediated by either striatum or thalamus metabolism.

METHODS

We recruited 96 drug-naive PD patients (aged 71.9 ± 7.5 years) who underwent [¹²³ I]ioflupane single-photon emission computed tomography ([¹²³ I]FP-CIT-SPECT) and brain [¹⁸ F]fluorodeoxyglucose positron emission tomography ([¹⁸ F]FDG-PET). We used a voxel-wise analysis of [¹⁸ F]FDG-PET images to correlate regional metabolism with striatal DA and thalamic SE innervation as assessed using [¹²³ I]FP-CIT-SPECT.

RESULTS

We found that [¹²³ I]FP-CIT specific to nondisplaceable binding ratio (SBR) and glucose metabolism positively correlated with one another in the deep gray matter (thalamus: P = 0.001, r = 0.541; caudate P = 0.001, r = 0.331; putamen P = 0.001, r = 0.423). We then observed a direct correlation between temporoparietal metabolism and caudate DA innervation, as well as a direct correlation between prefrontal metabolism and thalamus SE innervation. The effect of caudate [¹²³ I]FP-CIT SBR values on temporoparietal metabolism was mediated by caudate metabolic values (percentage mediated: 89%, P-value = 0.008), and the effect of thalamus [¹²³ I]FP-CIT SBR values on prefrontal metabolism was fully mediated by thalamus metabolic values (P < 0.001).

CONCLUSIONS

These data suggest that the impact of deep gray matter monoaminergic deafferentation on cortical function is mediated by striatal and thalamic metabolism in drug-naive PD. © 2021 International Parkinson and Movement Disorder Society.

Parkinson Disease-Related Brain Metabolic Patterns and Neurodegeneration in Isolated REM Sleep Behavior Disorder

OBJECTIVE

To elucidate the role of Parkinson disease (PD)-related brain metabolic patterns as a biomarker in isolated REM sleep behavior disorder (iRBD) for future disease conversion.

METHODS

This is a prospective cohort study consisting of 30 patients with iRBD, 25 patients with de novo PD with a premorbid history of RBD, 21 patients with longstanding PD on stable treatment, and 24 healthy controls. The iRBD group was longitudinally followed up. All participants underwent ¹⁸F-fluorodeoxyglucose (FDG) PET and were evaluated with olfaction, cognition, and the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) at baseline. From FDG-PET scans, we derived metabolic patterns from the longstanding PD group (PD-RP) and de novo PD group with RBD (dnPDRBD-RP). Subsequently, we calculated the PD-RP and dnPDRBD-RP scores in patients with iRBD. We validated the metabolic patterns in each PD group and separate iRBD cohort (n = 14).

RESULTS

The 2 patterns significantly correlated with each other and were spatially overlapping yet distinct. The MDS-UPDRS motor scores significantly correlated with PD-RP (p = 0.013) but not with dnPDRBD-RP (p = 0.076). In contrast, dnPDRBD-RP correlated with olfaction in butanol threshold test (p = 0.018) in patients with iRBD, but PD-RP did not (p = 0.21). High dnPDRBD-RP in patients with iRBD predicted future phenoconversion with all cutoff ranges from 1.5 to 3 SD of the control value, whereas predictability of PD-RP was only significant in a partial range of cutoff.

CONCLUSION

The dnPDRBD-RP is an efficient neuroimaging biomarker that reflects prodromal features of PD and predicts phenoconversion in iRBD that can be applied individually.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that a de novo PD pattern on FDG-PET predicts future conversion to neurodegenerative disease in patients with iRBD.

Astrocyte-Neuron Metabolic Crosstalk in Neurodegeneration: A Mitochondrial Perspective

Converging evidence made clear that declining brain energetics contribute to aging and are implicated in the initiation and progression of neurodegenerative disorders such as Alzheimer's and Parkinson's disease. Indeed, both pathologies involve instances of hypometabolism of glucose and oxygen in the brain causing mitochondrial dysfunction, energetic failure and oxidative stress. Importantly, recent evidence suggests that astrocytes, which play a key role in supporting neuronal function and metabolism, might contribute to the development of neurodegenerative diseases. Therefore, exploring how the neuro-supportive role of astrocytes may be impaired in the context of these disorders has great therapeutic potential. In the following, we will discuss some of the so far identified features underlining the astrocyte-neuron metabolic crosstalk. Thereby, special focus will be given to the role of mitochondria. Furthermore, we will report on recent advancements concerning iPSC-derived models used to unravel the metabolic contribution of astrocytes to neuronal demise. Finally, we discuss how mitochondrial dysfunction in astrocytes could contribute to inflammatory signaling in neurodegenerative diseases.

Co-registration Analysis of Fluorodopa and Fluorodeoxyglucose Positron Emission Tomography for Differentiating Multiple System Atrophy Parkinsonism Type From Parkinson's Disease

It is difficult to differentiate between Parkinson's disease and multiple system atrophy parkinsonian subtype (MSA-P) because of the overlap of their signs and symptoms. Enormous efforts have been made to develop positron emission tomography (PET) imaging to differentiate these diseases. This study aimed to investigate the co-registration analysis of ¹⁸F-fluorodopa and ¹⁸F-flurodeoxyglucose PET images to visualize the difference between Parkinson's disease and MSA-P. We enrolled 29 Parkinson's disease patients, 28 MSA-P patients, and 10 healthy controls, who underwent both ¹⁸F-fluorodopa and ¹⁸F-flurodeoxyglucose PET scans. Patients with Parkinson's disease and MSA-P exhibited reduced bilateral striatal ¹⁸F-fluorodopa uptake (p < 0.05, vs. healthy controls). Both regional specific uptake ratio analysis and statistical parametric mapping analysis of ¹⁸F-flurodeoxyglucose PET revealed hypometabolism in the bilateral putamen of MSA-P patients and hypermetabolism in the bilateral putamen of Parkinson's disease patients. There was a significant positive correlation between ¹⁸F-flurodeoxyglucose uptake and ¹⁸F-fluorodopa uptake in the contralateral posterior putamen of MSA-P patients (rs = 0.558, p = 0.002). Both ¹⁸F-flurodeoxyglucose and ¹⁸F-fluorodopa PET images showed that the striatum was rabbit-shaped in the healthy control group segmentation analysis. A defective rabbit-shaped striatum was observed in the ¹⁸F-fluorodopa PET image of patients with Parkinson's disease and MSA-P. In the segmentation analysis of ¹⁸F-flurodeoxyglucose PET image, an intact rabbit-shaped striatum was observed in Parkinson's disease patients, whereas a defective rabbit-shaped striatum was observed in MSA-P patients. These findings suggest that there were significant differences in the co-registration analysis of ¹⁸F-flurodeoxyglucose and ¹⁸F-fluorodopa PET images, which could be used in the individual analysis to differentiate Parkinson's disease from MSA-P.

Longitudinal Changes in Isolated Rapid Eye Movement Sleep Behavior Disorder-Related Metabolic Pattern Expression

BACKGROUND

It remains unclear whether and how the isolated rapid eye movement (REM) sleep behavior disorder (iRBD)-related metabolic pattern (RBDRP) changes with disease progression in iRBD.

OBJECTIVE

To examine longitudinal changes in RBDRP expression in iRBD patients and to explore trajectories of relative metabolic activities of individual brain regions constituting RBDRP.

METHODS

In this cohort study, 25 iRBD patients (mean age [±standard deviation], 69.2 ± 5.3 years; 12 [48%] patients were men) and 24 age-matched healthy controls were included. The patients underwent at least two ¹⁸ F-fluorodeoxyglucose positron emission tomography scans at baseline and at the 2-year and/or 4-year follow-ups. We measured the RBDRP expression of the patients and controls which was validated by reproduction in a separate iRBD cohort (n = 13).

RESULTS

At baseline, the RBDRP expression discriminated iRBD patients from healthy controls. However, the RBDRP expression z scores tended to decrease over time in the patients, especially with longer follow-ups, and this tendency was observed even in patients with high-risk of phenoconversion. Furthermore, the degree of RBDRP expression at baseline did not predict the disease conversion. The RBDRP breakdown was mainly provoked by the attenuation of relative hypermetabolism in the frontal cortex including premotor areas and relative hypometabolism in the occipital cortex. The putaminal metabolic activity increased steadily with the disease progression.

CONCLUSIONS

The RBDRP expression in iRBD patients was altered significantly over time. Some of the brain metabolic changes seem to represent attempted functional compensation against ongoing neurodegeneration. The RBDRP expression measurement at one time point may not be a reliable biomarker for predicting disease conversion. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neuroimaging evaluation of deep brain stimulation in the treatment of representative neurodegenerative and neuropsychiatric disorders

Brain stimulation technology has become a viable modality of reversible interventions in the effective treatment of many neurological and psychiatric disorders. It is aimed to restore brain dysfunction by the targeted delivery of specific electronic signal within or outside the brain to modulate neural activity on local and circuit levels. Development of therapeutic approaches with brain stimulation goes in tandem with the use of neuroimaging methodology in every step of the way. Indeed, multimodality neuroimaging tools have played important roles in target identification, neurosurgical planning, placement of stimulators and post-operative confirmation. They have also been indispensable in pre-treatment screen to identify potential responders and in post-treatment to assess the modulation of brain circuitry in relation to clinical outcome measures. Studies in patients to date have elucidated novel neurobiological mechanisms underlying the neuropathogenesis, action of stimulations, brain responses and therapeutic efficacy. In this article, we review some applications of deep brain stimulation for the treatment of several diseases in the field of neurology and psychiatry. We highlight how the synergistic combination of brain stimulation and neuroimaging technology is posed to accelerate the development of symptomatic therapies and bring revolutionary advances in the domain of bioelectronic medicine.

Dynamic 18F-FPCIT PET: Quantification of Parkinson's disease metabolic networks and nigrostriatal dopaminergic dysfunction in a single imaging session

Previous multi-center imaging studies with 18F-FDG PET have established the presence of Parkinson's disease motor- and cognition-related metabolic patterns termed PDRP and PDCP in patients with this disorder. Given that in PD cerebral perfusion and glucose metabolism are typically coupled in the absence of medication, we determined whether subject expression of these disease networks can be quantified in early-phase images from dynamic 18F-FPCIT PET scans acquired to assess striatal dopamine transporter (DAT) binding. Methods: We studied a cohort of early-stage PD patients and age-matched healthy control subjects who underwent 18F-FPCIT at baseline; scans were repeated 4 years later in a smaller subset of patients. The early 18F-FPCIT frames, which reflect cerebral perfusion, were used to compute PDRP and PDCP expression (subject scores) in each subject, and compared to analogous measures computed based on 18F-FDG PET scan when additionally available. The late 18F-FPCIT frames were used to measure caudate and putamen DAT binding in the same individuals. Results: PDRP subject scores from early-phase 18F-FPCIT and 18F-FDG scans were elevated and striatal DAT binding reduced in PD versus healthy subjects. The PDRP scores from 18F-FPCIT correlated with clinical motor ratings, disease duration, and with corresponding measures from 18F-FDG PET. In addition to correlating with disease duration and analogous 18F-FDG PET values, PDCP scores correlated with DAT binding in the caudate/anterior putamen. PDRP and PDCP subject scores using either method rose over 4 years whereas striatal DAT binding declined over the same time period. Conclusion: Early-phase images obtained with 18F-FPCIT PET can provide an alternative to 18F-FDG PET for PD network quantification. This technique therefore allows PDRP/PDCP expression and caudate/putamen DAT binding to be evaluated with a single tracer in one scanning session.

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.

Spectral guided sparse inverse covariance estimation of metabolic networks in Parkinson's disease

In neurodegenerative disorders, a clearer understanding of the underlying aberrant networks facilitates the search for effective therapeutic targets and potential cures. [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging data of brain metabolism reflects the distribution of glucose consumption known to be directly related to neural activity. In FDG PET resting-state metabolic data, characteristic disease-related patterns have been identified in group analysis of various neurodegenerative conditions using principal component analysis of multivariate spatial covariance. Notably, among several parkinsonian syndromes, the identified Parkinson’s disease-related pattern (PDRP) has been repeatedly validated as an imaging biomarker of PD in independent groups worldwide. Although the primary nodal associations of this network are known, its connectivity is not fully understood. Here, we describe a novel approach to elucidate functional principal component (PC) network connections by performing graph theoretical sparse network derivation directly within the disease relevant PC partition layer of the whole brain data rather than by searching for associations retrospectively in whole brain sparse representations. Using sparse inverse covariance estimation of each overlapping PC partition layer separately, a single coherent network is detected for each layer in contrast to more spatially modular segmentation in whole brain data analysis. Using this approach, the major nodal hubs of the PD disease network are identified and their characteristic functional pathways are clearly distinguished within the basal ganglia, midbrain and parietal areas. Network associations are further clarified using Laplacian spectral analysis of the adjacency matrices. In addition, the innate discriminative capacity of the eigenvector centrality of the graph derived networks in differentiating PD versus healthy external data provides evidence of their validity.

Deep brain stimulation of the internal globus pallidus does not affect the limbic circuit in patients with Parkinson's disease: a PET study

INTRODUCTION

Internal globus pallidus (GPi) deep brain stimulation (DBS) is a safe and effective alternative treatment in Parkinson's disease (PD) for patients with cognitive impairment. However, no study has yet investigated metabolic changes within a large series of patients undergoing GPi stimulation.

OBJECTIVE

We assessed motor, cognitive and psychiatric changes, as well as modifications in brain glucose metabolism measured with FDG-PET, before and after bilateral GPi-DBS.

METHODS

In the same week, 32 patients with PD underwent a motor, cognitive and psychiatric assessment and a resting-state FDG-PET scan, 4 months before and 4 months after GPi-DBS surgery. For the voxelwise metabolic change assessment, the p value was controlled for multiple comparisons using the family wise error rate.

RESULTS

After GPi-DBS surgery, patients showed a significant overall improvement in motor status. No cognitive or psychiatric changes were observed after surgery. Nor were any clusters with significantly relative metabolic changes found in the limbic circuit after surgery. Clusters with significantly relative metabolic changes were observed in the left and right Brodmann area (BA) 6, the right BA 9, the right and left BA 39 and the left BA 17.

CONCLUSION

The present study confirmed that GPi-DBS is an effective treatment in patients with advanced PD, owing to metabolic changes in the areas involved in motor execution. The absence of relative metabolic decrease in the limbic circuit and the few changes affecting the associative circuit could explain why GPi-DBS is cognitively safe.

Multicenter Validation of Metabolic Abnormalities Related to PSP According to the MDS-PSP Criteria

It remains unclear whether the supportive imaging features described in the diagnostic criteria for progressive supranuclear palsy (PSP) are suitable for the full clinical spectrum. The aim of the current study was to define and cross-validate the pattern of glucose metabolism in the brain associated with a diagnosis of different PSP variants. A retrospective multicenter cohort study performed on 73 PSP patients who were referred for a fluorodeoxyglucose positron emission tomography PET scan: PSP-Richardson's syndrome, n = 47; PSP-parkinsonian variant, n = 18; and progressive gait freezing, n = 8. In addition, we included 55 healthy controls and 58 Parkinson's disease (PD) patients. Scans were normalized by global mean activity. We analyzed the regional differences in metabolism between the groups. Moreover, we applied a multivariate analysis to obtain a PSP-related pattern that was cross-validated in independent populations at the individual level. Group analysis showed relative hypometabolism in the midbrain, basal ganglia, thalamus, and frontoinsular cortices and hypermetabolism in the cerebellum and sensorimotor cortices in PSP patients compared with healthy controls and PD patients, the latter with more severe involvement in the basal ganglia and occipital cortices. The PSP-related pattern obtained confirmed the regions described above. At the individual level, the PSP-related pattern showed optimal diagnostic accuracy to distinguish between PSP and healthy controls (sensitivity, 80.4%; specificity, 96.9%) and between PSP and PD (sensitivity, 80.4%; specificity, 90.7%). Moreover, PSP-Richardson's syndrome and PSP-parkinsonian variant patients showed significantly more PSP-related pattern expression than PD patients and healthy controls. The glucose metabolism assessed by fluorodeoxyglucose PET is a useful and reproducible supportive diagnostic tool for PSP-Richardson's syndrome and PSP-parkinsonian variant. © 2020 International Parkinson and Movement Disorder Society.