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Most patients with idiopathic REM sleep behavior disorder (iRBD) will develop an overt α-synucleinopathy over time, with a rate of phenoconversion of 73.5% after 12 years from diagnosis. Several markers of phenoconversion were identified; however, most studies investigated biomarkers separately, with retrospective study designs, in small cohorts or without standardized data collection methods. The risk FActoRs PREdictive of phenoconversion in idiopathic REM sleep behavior disorder: the Italian STudy (FARPRESTO) is a multicentric longitudinal retrospective and prospective study with a cohort of incident (prospective recruitment) and prevalent (retrospective recruitment) iRBD patients, whose primary aim is to stratify the risk of phenoconversion, through the systematic collection by means of electronic case report forms of different biomarkers. Secondary aims are to (1) describe the sociodemographic and clinical characteristics of patients with iRBD; (2) collect longitudinal data about the development of α-synucleinopathies; (3) monitor the impact of iRBD on quality of life and sleep quality; (4) assess the correlation between phenoconversion, cognitive performance, and loss of normal muscle atony during REM sleep; (5) identify RBD phenotypes through evaluating clinical, biological, neurophysiological, neuropsychological, and imaging biomarkers; and (6) validate vPSG criteria for RBD diagnosis. The FARPRESTO study will collect a large and harmonized dataset, assessing the role of different biomarkers providing a unique opportunity for a holistic, multidimensional, and personalized approach to iRBD, with several possible application and impact at different levels, from basic to clinical research, and from prevention to management. The FARPRESTO has been registered at clinicaltrials.gov (NCT05262543).

Background/Objective: Idiopathic REM sleep behavior disorder (iRBD) often precedes Parkinson's disease (PD) and other alpha-synucleinopathies. The aim of the study is to investigate brain glucose metabolism of patients with RBD and PD by means of a multidimensional scaling approach, using18F-FDG-PET as a biomarker of synaptic function. Methods: Thirty-six iRBD patients (64.1±6.5 y, 32 M), 72 PD patients, and 79 controls (65.6±9.4 y, 53 M) underwent brain 18 F-FDG-PET. PD patients were divided according to the absence (PD, 32 subjects; 68.4±8.5 y, 15 M) or presence (PDRBD, 40 subjects; 71.8±6.6 y, 29 M) of RBD. 18F-FDG-PET scans were used to independently discriminate subjects belonging to four categories: Controls (RBD no, PD no), iRBD (RBD yes, PD no), PD (RBD no, PD yes) and PDRBD (RBD yes, PD yes). Results: The discriminant analysis was moderately accurate in identifying the correct category. This is because the model mostly confounds iRBD and PD, thus the intermediate classes. Indeed, iRBD, PD and PDRBD were progressively located at increasing distance from controls and are ordered along a single dimension (principal coordinate analysis) indicating the presence of a single flux of variation encompassing both RBD and PD conditions. Conclusion: Data-driven approach to brain 18 F-FDG-PET showed only moderate discrimination between iRBD and PD patients, highlighting brain glucose metabolism heterogeneity among such patients. iRBD should be considered as a marker of an ongoing condition that may be picked-up in different stages across patients and thus express different brain imaging features and likely different clinical trajectories.

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

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.

Rationale In Parkinson’s disease (PD), spatial covariance analysis of 18F-FDG PET data has consistently revealed a characteristic PD-related brain pattern (PDRP). By quantifying PDRP expression on a scan-by-scan basis, this technique allows objective assessment of disease activity in individual subjects. We provide a further validation of the PDRP by applying spatial covariance analysis to PD cohorts from the Netherlands (NL), Italy (IT), and Spain (SP). Methods The PDRPNL was previously identified (17 controls, 19 PD) and its expression was determined in 19 healthy controls and 20 PD patients from the Netherlands. The PDRPIT was identified in 20 controls and 20 “de-novo” PD patients from an Italian cohort. A further 24 controls and 18 “de-novo” Italian patients were used for validation. The PDRPSP was identified in 19 controls and 19 PD patients from a Spanish cohort with late-stage PD. Thirty Spanish PD patients were used for validation. Patterns of the three centers were visually compared and then cross-validated. Furthermore, PDRP expression was determined in 8 patients with multiple system atrophy. Results A PDRP could be identified in each cohort. Each PDRP was characterized by relative hypermetabolism in the thalamus, putamen/pallidum, pons, cerebellum, and motor cortex. These changes co-varied with variable degrees of hypometabolism in posterior parietal, occipital, and frontal cortices. Frontal hypometabolism was less pronounced in “de-novo” PD subjects (Italian cohort). Occipital hypometabolism was more pronounced in late-stage PD subjects (Spanish cohort). PDRPIT, PDRPNL, and PDRPSP were significantly expressed in PD patients compared with controls in validation cohorts from the same center (P < 0.0001), and maintained significance on cross-validation (P < 0.005). PDRP expression was absent in MSA.

Background and objective. Idiopathic REM sleep behavior disorder (iRBD) often precedes Parkinson's Disease (PD) and other alpha-synucleinopathies. The aim of the study is to investigate brain glucose metabolism of patients with RBD and PD by means of a multidimensional scaling approach, using18F-FDG-PET as a biomarker of synaptic function. Methods. Thirty-six iRBD patients (64.1±6.5 y, 32 M), 72 PD patients and 79 controls (65.6±9.4 y, 53 M) underwent brain 18F-FDG-PET. PD patients were divided according to the absence (PD, 32 subjects; 68.4±8.5 y, 15 M) or presence (PDRBD, 40 subjects; 71.8±6.6 y, 29 M) of RBD. 18F-FDG-PET scans were used to independently discriminate subjects belonging to four categories: controls (RBD no, PD no), iRBD (RBD yes, PD no), PD (RBD no, PD yes) and PDRBD (RBD yes, PD yes). Results. The discriminant analysis was moderately accurate in identifying the correct category. This is because the model mostly confounds iRBD and PD, thus the intermediate classes. Indeed, iRBD, PD and PDRBD were progressively located at increasing distance from controls and are ordered along a single dimension (principal coordinate analysis) indicating the presence of a single flux of variation encompassing both RBD and PD conditions. Conclusion. Data-driven approach to brain 18F-FDG-PET showed only moderate discrimination between iRBD and PD patients, highlighting brain glucose metabolism heterogeneity among such patients. iRBD should be considered as a marker of an ongoing condition that may be picked-up in different stages across patients and thus express different brain imaging features and likely different clinical trajectories.

Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). FDG-PET is a PET technique employed to obtain a representation of brain metabolic function. In this study we employed 3D CNNs in fluorodeoxyglucose (FDG)-positron emission tomography (PET)brain images with the purpose of discriminating patients diagnosed with Parkinson's disease (PD) from controls. We employed Scaled Subprofile Modeling using Principal Component Analysis as a preprocessing step to focus on specific brain regions and limit the number of voxels that are used as input for the CNNs, thereby increasing the signal-to-noise ratio in our data. We performed hyper-parameter optimization on three CNN architectures to estimate the classification accuracy of the networks on new data. The best performance that we obtained was accuracy=0.86, and area under the receiver operating characteristiccurve (AUC)= 0.94 on the test set. We believe that, with larger datasets, PD patients could be reliably distinguished from controls by FDG-PET scans alone and that this technique could be applied to more clinically challenging tasks, like the differential diagnosis of neurological disorders with similar symptoms, such as PD, Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA).

Rationale: Idiopathic REM sleep behavior disorder (iRBD) is considered a prodromal stage of Parkinson's disease (PD) and other Lewy-body disorders. Spatial covariance analysis of [18F]-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG-PET) data has disclosed a specific brain pattern of altered glucose metabolism in PD. In this study, we identify the metabolic pattern underlying iRBD and compare it to the known PD pattern. To understand the relevance of the iRBD pattern to disease progression, we study the expression of the iRBD pattern in de novo PD patients.Methods:The iRBD-related pattern was identified in18F-FDG-PET scans of 21 patients with polysomnographically-confirmed iRBD and 19 controls using spatial covariance analysis. Expression of the iRBD-related pattern was subsequently computed in18F-FDG-PET scans of 44 controls and 38 de novo, treatment-naïve PD patients. Of these 38 PD patients, 24 had probable RBD according to the Mayo Sleep Questionnaire. Neuropsychological evaluation showed mild cognitive impairment in 20 PD patients (PD-MCI), of whom sixteen also had concomitant RBD and roughly half (11/20) had bilateral motor symptoms.Results:The iRBD-related pattern was characterized by relative hypermetabolism in cerebellum, brainstem, thalamus, sensorimotor cortex, and hippocampus, and by relative hypometabolism in middle cingulate, temporal, occipital and parietal cortices. This topography partially overlapped with the PD-related pattern (PDRP). The iRBD-related pattern was significantly expressed in PD patients compared to controls (P

The assessment of the degree of order of brainmetabolism bymeans of a statisticalmechanistic approach applied to FDG-PET, allowed us to characterize healthy subjects as well as patients with mild cognitive impairment and Alzheimer's Disease (AD). The intensity signals from 24 volumes of interest were submitted to principal component analysis (PCA) giving rise to a major first principal component whose eigenvalue was a reliable cumulative index of order. This index linearly decreased from 77 to 44% going from normal aging to AD patients with intermediate conditions between these values (r =0.96, p b 0.001). Bootstrap analysis confirmed the statistical significance of the results. The progressive detachment of different brain regions from the first component was assessed, allowing for a purely data driven reconstruction of already known maximally affected areas. Wedemonstrated for the first time the reliability of a single global index of order in discriminating groups of cognitively impaired patients with different clinical outcome. The second relevant finding was the identification of clusters of regions relevant to AD pathology progressively separating fromthe first principal component through different stages of cognitive impairment, including patients cognitively impaired but not converted to AD. This paved the way to the quantitative assessment of the functional networking status in individual patients.

STUDY OBJECTIVE: Rigidity is a muscle hypertonia typical of Parkinson disease (PD), whereas rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by abnormally increased muscle tone during REM sleep (REM sleep without atonia) and enacting dream behaviors. Because movements are not bradykinetic during RBD in patients with PD, we investigated whether the background, wake postural rigidity is attenuated during REM sleep without atonia, in absence of movement. METHODS: The amplitude of levator menti (postural muscle) electromyographic activity during relaxed evening wakefulness (considered as reference) and sleep (N2, N3, atonic REM sleep, and quiet REM sleep without atonia) was measured in 20 patients with PD (with and without RBD), 10 patients with idiopathic RBD patients and 10 healthy subjects. RESULTS: The chin tone amplitude progressively decreased from wake to N2, N3, and atonic REM sleep in the four groups, but the highest amplitude was observed in PD patients with RBD during atonic REM sleep. Furthermore, chin muscle tone amplitude did not attenuate from wake to REM sleep without atonia in patients with both PD and RBD but dramatically attenuated (by 40% on average) in patients with idiopathic RBD. CONCLUSIONS: The high amplitude of chin muscle tone in PD with RBD (but not in idiopathic RBD) during REM sleep with and without atonia suggests that both PD-related hypertonia and RBD-related enhanced muscle tone coexist during REM sleep, together affecting chin muscle tone. Consequently, some rapid RBD movements likely start against a rigid postural tone.

Cognitive impairment in Parkinson's disease (PD) and atypical parkinsonian syndromes is gaining increased clinical significance. The neurochemical and neuropathological basis in the various parkinsonian forms and even in an individual patient are not fully elucidated yet and could be heterogeneous. Loss of dopaminergic, cholinergic and noradrenergic innervation has been suggested to be the underlying neurochemical deficits for cognitive impairment and dementia in PD, but the onset of cognitive impairment and the progression to dementia may not share the same underlying neurochemical basis. Similarly, pathological evidence is also heterogeneous, ranging from subcortical pathology, limbic or cortical Lewy body type degeneration, and Alzheimer's type pathology that can be found even in the same patient with PD dementia (PDD). Typically, the prototype of early cognitive deficit in PD is a dysexecutive syndrome, but other cognitive domains are more involved when dementia develops, mainly including visuospatial, language and memory dysfunction. Functional radionuclide neuroimaging, by means of single-photon emission computed tomography and positron emission tomography, are contributing to characterize the topographic cortical pattern of cognitive impairment, as well as to define the underlying neurochemical deficit. Lastly, the advent of amyloid PET may help clarifying the meaning of amyloid load in diffuse Lewy body disease and PDD. Knowing the neurochemical and pathophysiological substrate of cognitive deficit in patients with PD or other degenerative Parkinsonisms may help the clinician in understanding the clinical condition of an individual patient in order to plan pharmacological and non-pharmacological intervention. The introduction of acetylcholinesterase inhibitors for therapy of PDD is an example of information integration between clinical-neuropsychological and pathophysiological-neurochemical aspects obtained also with the key contribution of functional neuroimaging.

Subtle cognitive impairment can be detected in early Parkinson's disease (PD). In a consecutive series of de novo, drug-naive PD patients, we applied stepwise regression analysis to assess which clinical, neuropsychological, and functional neuroimaging (dopamine transporter [DAT] and perfusion single photon emission computed tomography [SPECT]) characteristics at baseline was predictive of cognitive decline during an average follow-up time of about 4 years. Decline both in executive (R(2) = 0.54; p = 0.0001) and visuospatial (R(2) = 0.56; p = 0.0001) functions was predicted by the couple of Unified Parkinson's Disease Rating Scale (UPDRS)-III score and caudate dopamine transporter (DAT) uptake in the less affected hemisphere (LAH). Verbal memory and language decline was predicted instead by caudate DAT uptake and brain perfusion in a posterior parieto-temporal area of the less affected hemisphere (R(2) = 0.42; p = 0.0005). No significant effect was shown for age, baseline neuropsychological scores, and levodopa equivalent dose at follow-up. The combined use of clinical structured examination and brain functional assessment by means of dual single photon emission computed tomography imaging appears as a powerful approach to predict cognitive decline in de novo PD patients.

PURPOSE: Subtle cognitive impairment is recognized in the first stages of Parkinson's disease (PD), including executive, memory and visuospatial dysfunction, but its pathophysiological basis is still debated. METHODS: Twenty-six consecutive, drug-naïve, de novo PD patients underwent an extended neuropsychological battery, dopamine transporter (DAT) and brain perfusion single photon emission computed tomography (SPECT). We previously reported that nigrocaudate impairment correlates with executive functions, and nigroputaminal impairment with visuospatial abilities. Here perfusion SPECT was first compared between the PD group and age-matched controls (CTR). Then, perfusion SPECT was correlated with both DAT SPECT and four neuropsychological factors by means of voxel-based analysis (SPM8) with a height threshold of p

To unveil cognitive-nigrostriatal correlations in Parkinson's disease (PD), 30 de novo, drug-naïve PD patients and 15 patients with essential tremor (Controls, CTR) underwent a neuropsychological (NPS) battery and brain SPECT with [I-123]Ioflupane, as a biomarker of nigrostriatal function. Automatic extraction of uptake at caudate and putamen level was conducted through the BasGan software, also allowing partial volume effect correction. Because of the multicollinearity among neuropsychological tests and among SPECT variables, factor analysis was applied to 16 neuropsychological scores; moreover, the four SPECT variables were merged into a mean SPECT value (mSPECT). Factor analysis identified four NPS factors: a dys-executive (NPS-EX), a visuospatial (NPS-VS), a verbal memory (NPS-VM), and a "mixed" (NPD-MIX) factor. In PD group, there were inverse correlations between UPDRS-III score and both NPS-VS (P < 0.01) and mSPECT (P < 0.05), and a direct correlation between mSPECT and NPS-EX (P < 0.05). Post hoc analysis showed a direct correlation between NPS-EX and caudate uptake in both hemispheres (P < 0.05). Moreover, inverse correlations were found between UPDRS-III and, respectively, putamen uptake in the less affected hemisphere (P < 0.01), and putamen and caudate uptake in the more affected hemisphere (P < 0.05). In CTR, no correlation was found between mSPECT and either NPS or GDS values. Nigro-caudate function affects executive capabilities in PD but not in CTR, which appears to be unrelated to the disease motor severity at its onset. Instead, PD motor severity is related to nigro-putaminal impairment and visuospatial dysfunction. The role of these data as predictive features of cognitive decline and eventually dementia remains to be established in longitudinal studies.