Metabolic pattern analysis of 18F-FDG PET as a marker for Parkinson's disease: a systematic review and meta-analysis

Positron emission tomography molecular imaging for pathological visualization in multiple system atrophy

Multiple system atrophy (MSA) is a complex, heterogeneous neurodegenerative disorder characterized by a multifaceted pathogenesis. Its key pathological hallmark is the abnormal aggregation of α-synuclein, which triggers neuroinflammation, disrupts both dopaminergic and non-dopaminergic systems, and results in metabolic abnormalities in the brain. Positron emission tomography (PET) is a non-invasive technique that enables the visualization, characterization, and quantification of these pathological processes from diverse perspectives using radiolabeled agents. PET imaging of molecular events provides valuable insights into the underlying pathomechanisms of MSA and holds significant promise for the development of imaging biomarkers, which could greatly improve disease assessment and management. In this review, we focused on the pathological mechanisms of MSA, summarized relevant targets and radiopharmaceuticals, and discussed the clinical applications and future perspectives of PET molecular imaging in MSA.

Synaptic Density Reductions in MSA: A Potential Biomarker Identified Through [18F]SynVesT-1 PET Imaging

OBJECTIVE

The objective of this study was to delineate synaptic density alterations in multiple system atrophy (MSA) and explore its potential role as a biomarker for MSA diagnosis and disease severity monitoring using [18F]SynVesT-1 positron emission tomography / computed tomography (PET CT).

METHODS

In this prospective study, 60 patients with MSA (30 patients with MSA-parkinsonian [MSA-P] subtype and 30 patients with MSA-cerebellar [MSA-C] subtype), 30 patients with Parkinson's disease (PD), and 30 age-matched healthy controls (HCs) underwent [18F]SynVesT-1 PET/CT for synaptic density assessment. Visual, voxel, and volumetric region of interest (VOI) analyses were used to elucidate synaptic density patterns in the MSA brain and establish diagnostic criteria. The diagnostic performances of both visual and VOI-based diagnostics were evaluated using receiver operating characteristic (ROC) analysis. Spearman correlation analyses were conducted to investigate the relationship between brain synaptic density and disease severity RESULTS: Patients with MSA displayed extensive reductions in synaptic density throughout the brain, notably affecting both primary VOIs (the cerebellum and putamen) and secondary VOIs including the medulla oblongata, ventral tegmental area, and pons. Notably, patients with MSA-C exhibited a remarkable decrease in cerebellar synaptic density, whereas patients with MSA-P demonstrated significant synaptic loss within the posterior putamen. Compared with patients with PD, the patients with MSA show a more pronounced reduction in synaptic density in infratentorial brain regions. VOI-based diagnosis significantly outperformed visual analysis in diagnosing and differentiating MSA and its subtypes. Synaptic density in primary and multiple secondary VOIs correlated significantly with motor scales in patients with MSA.

INTERPRETATION

Our study identified widespread synaptic density reductions in MSA, particularly in the basal ganglia and infratentorial region, suggesting [18F]SynVesT-1 PET as a potential biomarker for diagnosing and evaluating the disease, and guiding synaptic restoration trials. ANN NEUROL 2025.

The value of PET/CT in the diagnosis and differential diagnosis of Parkinson's disease: a dual-tracer study

Positron emission tomography/computed tomography (PET/CT) is a molecular imaging method commonly used to diagnose and differentiate Parkinson's disease (PD). This study aimed to evaluate the performance of PET/CT with 11C-2β-Carbomethoxy-3β-(4-fluorophenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose (18F-FDG) tracers in the differential diagnosis between PD, multiple system atrophy parkinsonian type (MSA-P), progressive supranuclear palsy (PSP) and vascular parkinsonism (VP) using the data of 220 patients with clinical PD-like symptoms. Of the 220 enrolled patients, 166 (PD, n = 80; MSA-P, n = 54; PSP, n = 15; VP, n = 17) completed the motor, cognitive and PET/CT assessment and were included in this study. 11C-CFT and 18F-FDG PET/CT images were analyzed using the SNBPI toolbox and CortexID Suite software. The uptake values of 11C-CFT and 18F-FDG PET/CT were compared among the groups after controlling for covariates using generalized linear models. Receiver operating characteristic (ROC) curves were generated to estimate the diagnostic values. Patients with PSP showed the most significant reduction on 11C-CFT PET/CT, while patients with PD and MSA-P showed similar reductions, and patients with VP did not show any significant reduction in 11C-CFT uptake. The areas under the curve (AUCs) for 11C-CFT PET/CT for distinguishing PD from VP, PSP, and MSA-P were 0.902, 0.830, and 0.580, respectively, and 0.728 for distinguishing advanced-stage PD from PSP. On 18F-FDG PET/CT, the AUCs for distinguishing PD from PSP and MSA-P were 0.968 and 0.963, respectively. These results suggest that 11C-CFT and 18F-FDG PET/CT complement each other in improving the accuracy in differential diagnosis of PD.

Differences in Topography of Individual Amyloid Brain Networks by Amyloid PET Images in Healthy Control, Mild Cognitive Impairment, and Alzheimer's Disease

Amyloid plaques, implicated in Alzheimer's disease, exhibit a spatial propagation pattern through interconnected brain regions, suggesting network-driven dissemination. This study utilizes PET imaging to investigate these brain connections and introduces an innovative method for analyzing the amyloid network. A modified version of a previously established method is applied to explore distinctive patterns of connectivity alterations across cognitive performance domains. PET images illustrate differences in amyloid accumulation, complemented by quantitative network indices. The normal control group shows minimal amyloid accumulation and preserved network connectivity. The MCI group displays intermediate amyloid deposits and partial similarity to normal controls and AD patients, reflecting the evolving nature of cognitive decline. Alzheimer's disease patients exhibit high amyloid levels and pronounced disruptions in network connectivity, which are reflected in low levels of global efficiency (Eg) and local efficiency (Eloc). It is mostly in the temporal lobe where connectivity alterations are found, particularly in regions related to memory and cognition. Network connectivity alterations, combined with amyloid PET imaging, show potential as discriminative markers for different cognitive states. Dataset-specific variations must be considered when interpreting connectivity patterns. The variability in MCI and AD overlap emphasizes the heterogeneity in cognitive decline progression, suggesting personalized approaches for neurodegenerative disorders. This study contributes to understanding the evolving network characteristics associated with normal cognition, MCI, and AD, offering valuable insights for developing diagnostic and prognostic markers.

Dysfunction of motor cortices in Parkinson's disease

The cerebral cortex has long been thought to be involved in the pathophysiology of motor symptoms of Parkinson's disease. The impaired cortical function is believed to be a direct and immediate effect of pathologically patterned basal ganglia output, mediated to the cerebral cortex by way of the ventral motor thalamus. However, recent studies in humans with Parkinson's disease and in animal models of the disease have provided strong evidence suggesting that the involvement of the cerebral cortex is much broader than merely serving as a passive conduit for subcortical disturbances. In the present review, we discuss Parkinson's disease-related changes in frontal cortical motor regions, focusing on neuropathology, plasticity, changes in neurotransmission, and altered network interactions. We will also examine recent studies exploring the cortical circuits as potential targets for neuromodulation to treat Parkinson's disease.

Cerebellar blood perfusion is a diagnostic, but not a prognostic, marker for parkinsonian-dominant type multiple system atrophy

INTRODUCTION

Multiple system atrophy (MSA) is clinically characterized by various neurological symptoms. According to the diagnostic criteria, MSA is classified into parkinsonian-dominant type (MSA-P) or cerebellar ataxia-dominant type (MSA-C) based on the predominant signs displayed. Recently, N-isopropyl-p-[123I] iodoamphetamine (123I-IMP) single-photon emission computed tomography (SPECT), a radiological examination evaluating brain perfusion, has been successful in detecting cerebellar hypoperfusion in MSA-P patients, demonstrating its utility in the early detection of cerebellar dysfunction. In this study, we further explored whether this cerebellar hypoperfusion impacts the clinical features of MSA-P, whether it is observable in patients without cerebellar symptoms, and, most importantly, whether it influences the prognosis of MSA-P.

METHODS

We conducted a retrospective analysis of 88 MSA patients who were admitted to our department for the last fifteen years. Clinical data were collected, and cerebellar perfusion was examined using 123I-IMP SPECT. This analysis includes the application of the three-dimensional stereotactic surface projection (3D-SSP) technique and Z-score.

RESULTS

Cerebellar perfusion decreased in MSA-P patients without cerebellar ataxia, compared to healthy individuals (p = 0.0017). The Receiver Operating Characteristic (ROC) curve demonstrated a moderate ability to distinguish MSA-P patients without cerebellar ataxia (MSA-Pp) from healthy controls (AUC = 0.6832). Among MSA-Pp, those exhibiting cerebellar hypoperfusion showed relatively improved neurological prognosis, although the difference was not statistically significant when compared to those with normal cerebellar perfusion.

CONCLUSION

Assessing cerebellar perfusion through IMP-SPECT proves valuable in detecting subclinical cerebellar dysfunction in MSA-Pp. Importantly, cerebellar hypoperfusion does not correlate with a poorer neurological prognosis.

Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis

Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.

[18F]FDG PET in conditions associated with hyperkinetic movement disorders and ataxia: a systematic review

PURPOSE

To give a comprehensive literature overview of alterations in regional cerebral glucose metabolism, measured using [18F]FDG PET, in conditions associated with hyperkinetic movement disorders and ataxia. In addition, correlations between glucose metabolism and clinical variables as well as the effect of treatment on glucose metabolism are discussed.

METHODS

A systematic literature search was performed according to PRISMA guidelines. Studies concerning tremors, tics, dystonia, ataxia, chorea, myoclonus, functional movement disorders, or mixed movement disorders due to autoimmune or metabolic aetiologies were eligible for inclusion. A PubMed search was performed up to November 2021.

RESULTS

Of 1240 studies retrieved in the original search, 104 articles were included. Most articles concerned patients with chorea (n = 27), followed by ataxia (n = 25), dystonia (n = 20), tremor (n = 8), metabolic disease (n = 7), myoclonus (n = 6), tics (n = 6), and autoimmune disorders (n = 5). No papers on functional movement disorders were included. Altered glucose metabolism was detected in various brain regions in all movement disorders, with dystonia-related hypermetabolism of the lentiform nuclei and both hyper- and hypometabolism of the cerebellum; pronounced cerebellar hypometabolism in ataxia; and striatal hypometabolism in chorea (dominated by Huntington disease). Correlations between clinical characteristics and glucose metabolism were often described. [18F]FDG PET-showed normalization of metabolic alterations after treatment in tremors, ataxia, and chorea.

CONCLUSION

In all conditions with hyperkinetic movement disorders, hypo- or hypermetabolism was found in multiple, partly overlapping brain regions, and clinical characteristics often correlated with glucose metabolism. For some movement disorders, [18F]FDG PET metabolic changes reflected the effect of treatment.

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.

Multiple system atrophy

Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.

Glia Imaging Differentiates Multiple System Atrophy from Parkinson's Disease: A Positron Emission Tomography Study with [11 C]PBR28 and Machine Learning Analysis

BACKGROUND

The clinical diagnosis of multiple system atrophy (MSA) is challenged by overlapping features with Parkinson's disease (PD) and late-onset ataxias. Additional biomarkers are needed to confirm MSA and to advance the understanding of pathophysiology. Positron emission tomography (PET) imaging of the translocator protein (TSPO), expressed by glia cells, has shown elevations in MSA.

OBJECTIVE

In this multicenter PET study, we assess the performance of TSPO imaging as a diagnostic marker for MSA.

METHODS

We analyzed [¹¹ C]PBR28 binding to TSPO using imaging data of 66 patients with MSA and 24 patients with PD. Group comparisons were based on regional analysis of parametric images. The diagnostic readout included visual reading of PET images against clinical diagnosis and machine learning analyses. Sensitivity, specificity, and receiver operating curves were used to discriminate MSA from PD and cerebellar from parkinsonian variant MSA.

RESULTS

We observed a conspicuous pattern of elevated regional [¹¹ C]PBR28 binding to TSPO in MSA as compared with PD, with "hotspots" in the lentiform nucleus and cerebellar white matter. Visual reading discriminated MSA from PD with 100% specificity and 83% sensitivity. The machine learning approach improved sensitivity to 96%. We identified MSA subtype-specific TSPO binding patterns.

CONCLUSIONS

We found a pattern of significantly increased regional glial TSPO binding in patients with MSA. Intriguingly, our data are in line with severe neuroinflammation in MSA. Glia imaging may have potential to support clinical MSA diagnosis and patient stratification in clinical trials on novel drug therapies for an α-synucleinopathy that remains strikingly incurable. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Abnormal structural connectivity in progressive supranuclear palsy-Richardson syndrome

OBJECTIVES

Progressive supranuclear palsy-Richardson syndrome (PSP-RS) is characterized by symmetrical parkinsonism with postural instability and frontal dysfunction. This study aims to use the whole brain structural connectome (SC) to gain insights into the underlying disconnectivity which may be implicated in the clinical features of PSP-RS.

METHODS

Sixteen patients of PSP-RS and 12 healthy controls were recruited. Disease severity was quantified using PSP rating scale (PSPRS), and mini-mental scale was applied to evaluate cognition. Thirty-two direction diffusion MRIs were acquired and used to compute the structural connectome of the whole brain using deterministic fiber tracking. Group analyses were performed at the edge-wise, nodal, and global levels. Age and gender were used as nuisance covariates for all the subsequent analyses, and FDR correction was applied.

RESULTS

Network-based statistics revealed a 34-edge network with significantly abnormal edge-wise connectivity in the patient group. Of these, 25 edges were cortical connections, of which 68% were frontal connections. Abnormal deep gray matter connections were predominantly comprised of connections between structures of the basal ganglia. The characteristic path length of the SC was lower in PSP-RS, and nodal analysis revealed abnormal degree, strength, local efficiency, betweenness centrality, and participation coefficient in several nodes.

CONCLUSIONS

Significant alterations in the structural connectivity of the whole brain connectome were observed in PSP-RS. The higher degree of abnormality observed in nodes belonging to the frontal lobe and basal ganglia substantiates the predominant frontal dysfunction and parkinsonism observed in PSP-RS. The findings of this study support the concept that PSP-RS may be a network-based disorder.

Brain Molecular Connectivity in Neurodegenerative Conditions

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

Importance of Fluorine in Benzazole Compounds

Fluorine-containing heterocycles continue to receive considerable attention due to their unique properties. In medicinal chemistry, the incorporation of fluorine in small molecules imparts a significant enhancement their biological activities compared to non-fluorinated molecules. In this short review, we will highlight the importance of incorporating fluorine as a basic appendage in benzothiazole and benzimidazole skeletons. The chemistry and pharmacological activities of heterocycles containing fluorine during the past years are compiled and discussed.

Can Autonomic Testing and Imaging Contribute to the Early Diagnosis of Multiple System Atrophy? A Systematic Review and Recommendations by the Movement Disorder Society Multiple System Atrophy Study Group

Background

In the current consensus diagnostic criteria, the diagnosis of probable multiple system atrophy (MSA) is based solely on clinical findings, whereas neuroimaging findings are listed as aid for the diagnosis of possible MSA. There are overlapping phenotypes between MSA-parkinsonian type and Parkinson's disease, progressive supranuclear palsy, and dementia with Lewy bodies, and between MSA-cerebellar type and sporadic adult-onset ataxia resulting in a significant diagnostic delay and misdiagnosis of MSA during life.

Objectives

In light of an ongoing effort to revise the current consensus criteria for MSA, the Movement Disorders Society Multiple System Atrophy Study Group performed a systematic review of original articles published before August 2019.

Methods

We included articles that studied at least 10 patients with MSA as well as participants with another disorder or control group for comparison purposes. MSA was defined by neuropathological confirmation, or as clinically probable, or clinically probable plus possible according to consensus diagnostic criteria.

Results

We discuss the pitfalls and benefits of each diagnostic test and provide specific recommendations on how to evaluate patients in whom MSA is suspected.

Conclusions

This systematic review of relevant studies indicates that imaging and autonomic function tests significantly contribute to increasing the accuracy of a diagnosis of MSA.

Regional SUV quantification in hybrid PET/MR, a comparison of two atlas-based automatic brain segmentation methods

BACKGROUND

Quantitative analysis of brain positron-emission tomography (PET) depends on structural segmentation, which can be time-consuming and operator-dependent when performed manually. Previous automatic segmentation usually registered subjects' images onto an atlas template (defined as RSIAT here) for group analysis, which changed the individuals' images and probably affected regional PET segmentation. In contrast, we could register atlas template to subjects' images (RATSI), which created an individual atlas template and may be more accurate for PET segmentation. We segmented two representative brain areas in twenty Parkinson disease (PD) and eight multiple system atrophy (MSA) patients performed in hybrid positron-emission tomography/magnetic resonance imaging (PET/MR). The segmentation accuracy was evaluated using the Dice coefficient (DC) and Hausdorff distance (HD), and the standardized uptake value (SUV) measurements of these two automatic segmentation methods were compared, using manual segmentation as a reference.

RESULTS

The DC of RATSI increased, and the HD decreased significantly (P < 0.05) compared with the RSIAT in PD, while the results of one-way analysis of variance (ANOVA) found no significant differences in the SUVmean and SUVmax among the two automatic and the manual segmentation methods. Further, RATSI was used to compare regional differences in cerebral metabolism pattern between PD and MSA patients. The SUVmean in the segmented cerebellar gray matter for the MSA group was significantly lower compared with the PD group (P < 0.05), which is consistent with previous reports.

CONCLUSION

The RATSI was more accurate for the caudate nucleus and putamen automatic segmentation and can be used for regional PET analysis in hybrid PET/MR.

[123I]FP-CIT SPECT in Clinically Uncertain Parkinsonism Predicts Survival: A Data-Driven Analysis

BACKGROUND

Dopamine transporter SPECT is an established method to investigate nigrostriatal integrity in case of clinically uncertain parkinsonism.

OBJECTIVE

The present study explores whether a data-driven analysis of [123I]FP-CIT SPECT is able to stratify patients according to mortality after SPECT.

METHODS

Patients from our clinical registry were included if they had received [123I]FP-CIT SPECT between 10/2008 and 06/2016 for diagnosis of parkinsonism and if their vital status could be determined in 07/2017. Specific binding ratios (SBR) of the whole striatum, its asymmetry (asymmetry index, AI; absolute value), and the rostrocaudal gradient of striatal binding (C/pP: caudate SBR divided by posterior putamen SBR) were used as input for hierarchical clustering of patients. We tested differences in survival between these groups (adjusted for age) with a Cox proportional hazards model.

RESULTS

Data from 518 patients were analyzed. Median follow-up duration was 3.3 years [95% C.I. 3.1 to 3.7]. Three subgroups identified by hierarchical clustering were characterized by relatively low striatal SBR, high AI, and low C/pP (group 1), low striatal SBR, high AI, and high C/pP (group 2), and high striatal SBR, low AI, and low C/pP (group 3). Mortality was significantly higher in group 1 compared to each of the other two groups (p = 0.029 and p = 0.003, respectively).

CONCLUSION

Data-driven analysis of [123I]FP-CIT SPECT identified a subgroup of patients with significantly increased mortality during follow-up. This suggests that [123I]-FP-CIT SPECT might not only serve as a diagnostic tool to verify nigrostriatal degeneration but also provide valuable prognostic information.