for a scientific commentary on this article. Parkinson's disease is a neurodegenerative disorder characterized by nigrostriatal dopamine depletion. Previous studies measuring spontaneous brain activity using resting state functional magnetic resonance imaging have reported abnormal changes in broadly distributed whole-brain networks. Although resting state functional connectivity, estimating temporal correlations between brain regions, is measured with the assumption that intrinsic fluctuations throughout the scan are stable, dynamic changes of functional connectivity have recently been suggested to reflect aspects of functional capacity of neural systems, and thus may serve as biomarkers of disease. The present work is the first study to investigate the dynamic functional connectivity in patients with Parkinson's disease, with a focus on the temporal properties of functional connectivity states as well as the variability of network topological organization using resting state functional magnetic resonance imaging. Thirty-one Parkinson's disease patients and 23 healthy controls were studied using group spatial independent component analysis, a sliding windows approach, and graph-theory methods. The dynamic functional connectivity analyses suggested two discrete connectivity configurations: a more frequent, sparsely connected within-network state (State I) and a less frequent, more strongly interconnected between-network state (State II). In patients with Parkinson's disease, the occurrence of the sparsely connected State I dropped by 12.62%, while the expression of the more strongly interconnected State II increased by the same amount. This was consistent with the altered temporal properties of the dynamic functional connectivity characterized by a shortening of the dwell time of State I and by a proportional increase of the dwell time pattern in State II. These changes are suggestive of a reduction in functional segregation among networks and are correlated with the clinical severity of Parkinson's disease symptoms. Additionally, there was a higher variability in the network global efficiency, suggesting an abnormal global integration of the brain networks. The altered functional segregation and abnormal global integration in brain networks confirmed the vulnerability of functional connectivity networks in Parkinson's disease.

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BackgroundNeuroinflammatory processes including activated microglia have been reported to play an important role in Parkinson’s disease (PD). Increased expression of translocator protein (TSPO) has been observed after brain injury and inflammation in neurodegenerative diseases. Positron emission tomography (PET) radioligand targeting TSPO allows for the quantification of neuroinflammation in vivo.MethodsBased on the genotype of the rs6791 polymorphism in the TSPO gene, we included 25 mixed-affinity binders (MABs) (14 PD patients and 11 age-matched healthy controls (HC)) and 27 high-affinity binders (HABs) (16 PD patients and 11 age-matched HC) to assess regional differences in the second-generation radioligand [18F]-FEPPA between PD patients and HC. FEPPA total distribution volume (V T) values in cortical as well as subcortical brain regions were derived from a two-tissue compartment model with arterial plasma as an input function.ResultsOur results revealed a significant main effect of genotype on [18F]-FEPPA V T in every brain region, but no main effect of disease or disease × genotype interaction in any brain region. The overall percentage difference of the mean FEPPA V T between HC-MABs and HC-HABs was 32.6% (SD = 2.09) and for PD-MABs and PD-HABs was 43.1% (SD = 1.21).ConclusionsFuture investigations are needed to determine the significance of [18F]-FEPPA as a biomarker of neuroinflammation as well as the importance of the rs6971 polymorphism and its clinical consequence in PD.

We now propose this test battery as the basis of laboratory-supported criteria for the diagnosis of functional tremor, and we encourage its use in clinical and research practice.

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The recent application of graph theory to brain networks promises to shed light on complex diseases such as Parkinson’s disease (PD). This study aimed to investigate functional changes in sensorimotor and cognitive networks in Parkinsonian patients, with a focus on inter- and intra-connectivity organization in the disease-associated nodal and hub regions using the graph theoretical analyses. Resting-state functional MRI data of a total of 65 participants, including 23 healthy controls (HCs) and 42 patients, were investigated in 120 nodes for local efficiency, betweenness centrality, and degree. Hub regions were identified in the HC and patient groups. We found nodal and hub changes in patients compared with HCs, including the right pre-supplementary motor area (SMA), left anterior insula, bilateral mid-insula, bilateral dorsolateral prefrontal cortex (DLPFC), and right caudate nucleus. In general, nodal regions within the sensorimotor network (i.e., right pre-SMA and right mid-insula) displayed weakened connectivity, with the former node associated with more severe bradykinesia, and impaired integration with default mode network regions. The left mid-insula also lost its hub properties in patients. Within the executive networks, the left anterior insular cortex lost its hub properties in patients, while a new hub region was identified in the right caudate nucleus, paralleled by an increased level of inter- and intra-connectivity in the bilateral DLPFC possibly representing compensatory mechanisms. These findings highlight the diffuse changes in nodal organization and regional hub disruption accounting for the distributed abnormalities across brain networks and the clinical manifestations of PD.

PurposeThe input function (IF) is a core element in the quantification of Translocator protein 18 kDa with positron emission tomography (PET), as no suitable reference region with negligible binding has been identified. Arterial blood sampling is indeed needed to create the IF (ASIF). In the present manuscript we study individualization of a population based input function (PBIF) with a single arterial manual sample to estimate total distribution volume (VT) for [18F]FEPPA and to replicate previously published clinical studies in which the ASIF was used.MethodsThe data of 3 previous [18F]FEPPA studies (39 of healthy controls (HC), 16 patients with Parkinson’s disease (PD) and 18 with Alzheimer’s disease (AD)) was reanalyzed with the new approach. PBIF was used with the Logan graphical analysis (GA) neglecting the vascular contribution to estimate VT. Time of linearization of the GA was determined with the maximum error criteria. The optimal calibration of the PBIF was determined based on the area under the curve (AUC) of the IF and the agreement range of VT between methods. The shape of the IF between groups was studied while taking into account genotyping of the polymorphism (rs6971).ResultsPBIF scaled with a single value of activity due to unmetabolized radioligand in arterial plasma, calculated as the average of a sample taken at 60 min and a sample taken at 90 min post-injection, yielded a good interval of agreement between methods and optimized the area under the curve of IF. In HC, gray matter VTs estimated by PBIF highly correlated with those using the standard method (r2 = 0.82, p = 0.0001). Bland-Altman plots revealed PBIF slightly underestimates (~1 mL/cm3) VT calculated by ASIF (including a vascular contribution). It was verified that the AUC of the ASIF were independent of genotype and disease (HC, PD, and AD). Previous clinical results were replicated using PBIF but with lower statistical power.ConclusionA single arterial blood sample taken 75 minute post-injection contains enough information to individualize the IF in the groups of subjects studied; however, the higher variability produced requires an increase in sample size to reach the same effect size.

Progressive supranuclear palsy is a rare form of atypical Parkinsonism that differs neuropathologically from other parkinsonian disorders. While many parkinsonian disorders such as Parkinson's disease, Lewy body dementia, and multiple system atrophy are classified as synucleinopathies, progressive supranuclear palsy is coined a tauopathy due to the aggregation of pathological tau in the brain. [F]AV-1451 (also known as [F]-T807) is a positron emission tomography radiotracer that binds to paired helical filaments of tau in Alzheimer's disease. We investigated whether [F]AV-1451 could be used as biomarker for the diagnosis and disease progression monitoring in progressive supranuclear palsy. Six progressive supranuclear palsy, six Parkinson's disease, and 10 age-matched healthy controls were recruited. An anatomical MRI and a 90-min PET scan, using [F]AV-1451, were acquired from all participants. The standardized uptake value ratio from 60 to 90 min post-injection was calculated in each region of interest, using the cerebellar cortex as a reference region. No significant differences in standardized uptake value ratios were detected in our progressive supranuclear palsy group compared to the two control groups. [F]AV-1451 may bind selectivity to the paired helical filaments in Alzheimer's disease, which differ from the straight conformation of tau filaments in progressive supranuclear palsy.