Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.

A real-world comparison among third-generation antiseizure medications: Results from the COMPARE study.

OBJECTIVE: There are few comparative data on the third-generation antiseizure medications (ASMs). We aimed to assess and compare the effectiveness of brivaracetam (BRV), eslicarbazepine acetate (ESL), lacosamide (LCM), and perampanel (PER) in people with epilepsy (PWE). Efficacy and tolerability were compared as secondary objectives. METHODS: This multicenter, retrospective study collected data from 22 Italian neurology/epilepsy centers. All adult PWE who started add-on treatment with one of the studied ASMs between January 2018 and October 2021 were included. Retention rate was established as effectiveness measure and described using Kaplan-Meier curves and the best fitting survival model. The responder status and the occurrence of adverse events (AEs) were used to evaluate efficacy and safety, respectively. The odds of AEs and drug efficacy were estimated by two multilevel logistic models. RESULTS: A total of 960 patients (52.92% females, median age = 43 years) met the inclusion criteria. They mainly suffered from structural epilepsy (52.29%) with monthly (46.2%) focal seizures (69.58%). Compared with LCM, all the studied ASMs had a higher dropout risk, statistically significant in the BRV levetiracetam (LEV)-naïve (hazard ratio [HR] = 1.97, 95% confidence interval [CI] = 1.17-3.29) and PER groups (HR = 1.64, 95% CI = 1.06-2.55). Women were at higher risk of discontinuing ESL (HR = 5.33, 95% CI = 1.71-16.61), as well as PER-treated patients with unknown epilepsy etiology versus those with structural etiology (HR = 1.74, 95% CI = 1.05-2.88). BRV with prior LEV therapy showed lower odds of efficacy (odds ratio [OR] = .08, 95% CI = .01-.48) versus LCM, whereas a higher efficacy was observed in women treated with BRV and LEV-naïve (OR = 10.32, 95% CI = 1.55-68.78) versus men. PER (OR = 6.93, 95% CI = 3.32-14.44) and BRV in LEV-naïve patients (OR = 6.80, 95% CI = 2.64-17.52) had a higher chance of AEs than LCM. SIGNIFICANCE: Comparative evidence from real-world studies may help clinicians to tailor treatments according to patients' demographic and clinical characteristics.

Rapid eye movement sleep and epilepsy: exploring interactions and therapeutic prospects.

While research interest in the relationship between sleep and epilepsy is growing, it primarily centres on the effects of non-rapid eye movement (NREM) sleep in favouring seizures. Nonetheless, a noteworthy aspect is the observation that, in the lives of patients with epilepsy, REM sleep represents the moment with the least epileptic activity and the lowest probability of having a seizure. Studies demonstrate a suppressive effect of phasic REM sleep on interictal epileptiform discharges, potentially offering insights into epilepsy localisation and management. Furthermore, epilepsy impacts REM sleep, with successful treatment correlating with improved REM sleep quality. Novel therapeutic strategies aim to harness REM's anti-epileptic effects, including pharmacological approaches targeting orexinergic systems and neuromodulation techniques promoting cortical desynchronisation. These findings underscore the intricate relationship between REM sleep and epilepsy, highlighting avenues for further research and therapeutic innovation in epilepsy management.

Progression of clinical markers in prodromal Parkinson's disease and dementia with Lewy bodies: a multicentre study.

The neurodegenerative synucleinopathies, including Parkinson's disease and dementia with Lewy bodies, are characterized by a typically lengthy prodromal period of progressive subclinical motor and non-motor manifestations. Among these, idiopathic REM sleep behaviour disorder is a powerful early predictor of eventual phenoconversion, and therefore represents a critical opportunity to intervene with neuroprotective therapy. To inform the design of randomized trials, it is essential to study the natural progression of clinical markers during the prodromal stages of disease in order to establish optimal clinical end points. In this study, we combined prospective follow-up data from 28 centres of the International REM Sleep Behavior Disorder Study Group representing 12 countries. Polysomnogram-confirmed REM sleep behaviour disorder subjects were assessed for prodromal Parkinson's disease using the Movement Disorder Society criteria and underwent periodic structured sleep, motor, cognitive, autonomic and olfactory testing. We used linear mixed-effect modelling to estimate annual rates of clinical marker progression stratified by disease subtype, including prodromal Parkinson's disease and prodromal dementia with Lewy bodies. In addition, we calculated sample size requirements to demonstrate slowing of progression under different anticipated treatment effects. Overall, 1160 subjects were followed over an average of 3.3 ± 2.2 years. Among clinical variables assessed continuously, motor variables tended to progress faster and required the lowest sample sizes, ranging from 151 to 560 per group (at 50% drug efficacy and 2-year follow-up). By contrast, cognitive, olfactory and autonomic variables showed modest progression with higher variability, resulting in high sample sizes. The most efficient design was a time-to-event analysis using combined milestones of motor and cognitive decline, estimating 117 per group at 50% drug efficacy and 2-year trial duration. Finally, while phenoconverters showed overall greater progression than non-converters in motor, olfactory, cognitive and certain autonomic markers, the only robust difference in progression between Parkinson's disease and dementia with Lewy bodies phenoconverters was in cognitive testing. This large multicentre study demonstrates the evolution of motor and non-motor manifestations in prodromal synucleinopathy. These findings provide optimized clinical end points and sample size estimates to inform future neuroprotective trials.

Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to Alzheimer's disease.

Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.

Automatic quantification of REM sleep without atonia reliably identifies patients with REM sleep behavior disorder: a possible screening tool?

BACKGROUND: REM Sleep Behavior Disorder (RBD) is characterized by absence of physiological muscle atonia during REM sleep (REM sleep without atonia, RWA). Nigro-striatal dopaminergic impairment is a feature of Parkinson disease (PD) and can be identified in prodromal stages as well, such as idiopathic RBD (iRBD). Aims of this study are to explore the efficacy of an automatic RWA quantification in identifying RBD patients and the correlation between RWA and nigro-striatal dopaminergic function. METHODS: Forty-five iRBD, 46 PD with RBD, 24 PD without RBD patients and 11 healthy controls were enrolled in the Genoa Center (group A) and 25 patients with iRBD (group B) were enrolled in the Danish Center. Group A underwent brain [123I]FP-CIT-SPECT and group B underwent brain [18F]PE2I-PET as measures of nigro-striatal dopaminergic function. Chin muscle activity was recorded in all subjects and analyzed by applying a published automatic algorithm. Correlations between RWA and nigro-striatal dopaminergic function were explored. RESULTS: The automatic quantification of RWA significantly differentiated RBD from non-RBD subjects (AUC = 0.86), although with lower accuracy compared with conventional visual scoring (AUC = 0.99). No significant correlation was found between RWA and nigro-striatal dopaminergic function. CONCLUSION: The automatic quantification of RWA is a reliable tool to identify subjects with RBD and may be used as a first-line screening tool, but without correlations with nigro-striatal dopaminergic functioning.

Prodromal dementia with Lewy bodies in REM sleep behavior disorder: A multicenter study.

INTRODUCTION: Isolated/idiopathic rapid eye movement sleep behavior disorder (iRBD) is a powerful early predictor of dementia with Lewy bodies (DLB) and Parkinson's disease (PD). This provides an opportunity to directly observe the evolution of prodromal DLB and to identify which cognitive variables are the strongest predictors of evolving dementia. METHODS: IRBD participants (n = 754) from 10 centers of the International RBD Study Group underwent annual neuropsychological assessment. Competing risk regression analysis determined optimal predictors of dementia. Linear mixed-effect models determined the annual progression of neuropsychological testing. RESULTS: Reduced attention and executive function, particularly performance on the Trail Making Test Part B, were the strongest identifiers of early DLB. In phenoconverters, the onset of cognitive decline began up to 10 years prior to phenoconversion. Changes in verbal memory best differentiated between DLB and PD subtypes. DISCUSSION: In iRBD, attention and executive dysfunction strongly predict dementia and begin declining several years prior to phenoconversion. HIGHLIGHTS: Cognitive decline in iRBD begins up to 10 years prior to phenoconversion. Attention and executive dysfunction are the strongest predictors of dementia in iRBD. Decline in episodic memory best distinguished dementia-first from parkinsonism-first phenoconversion.

Different z-score cut-offs for striatal binding ratio (SBR) of DaT SPECT are needed to support the diagnosis of Parkinson's Disease (PD) and dementia with Lewy bodies (DLB).

PURPOSE: A cut-off of -2 z-score for striatal or putaminal SBR has been to date arbitrarily used to define an abnormal DaT SPECT in patients with suspected neurodegenerative parkinsonism. We aimed to experimentally identify the most accurate z-score cut-offs for SBR of striatal and substriatal regions to independently discriminate PD and DLB, with respect to essential tremor (ET) and Alzheimer's disease (AD) respectively. METHODS: Two-hundred twenty-five patients undergoing DaT SPECT were enrolled (seventy-five de novo PD, eighty ET, fifty DLB, and twenty AD). Semiquantification was computed by means of Datquant® software which returns measures of striatal SBR and z-scores with respect to 118 healthy volunteers belonging to the Parkinson's Progression Markers Initiative (PPMI). ROC analysis was used to identify most accurate cut-offs for z-score for striatum and substriatal regions (clinical diagnosis at follow-up as gold standard). RESULTS: Posterior putamen of the most affected hemisphere (MAH) with a z-score cut-off of - 1.27 demonstrated the highest accuracy to differentiate between PD and ET (sensitivity 0.97, specificity 0.94). The whole putamen (z-score cut-off - 0.96) was the most accurate parameter to support the diagnosis of DLB (sensitivity 0.74, specificity 0.95). Putamen to caudate ratio was accurate to detect PD (especially in early stages) while not DLB patients. CONCLUSION: We experimentally demonstrated that different substriatal regions and cut-offs for z-score of SBR should be considered to support the diagnosis of either PD or DLB. The identified less conservative cut-offs showed higher sensitivity without a measurable reduction in specificity with respect to the arbitrary - 2 z-score.

Derivation and Validation of a Phenoconversion-Related Pattern in Idiopathic Rapid Eye Movement Behavior Disorder.

BACKGROUND: Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents the prodromal stage of α-synucleinopathies. Reliable biomarkers are needed to predict phenoconversion. OBJECTIVE: The aim was to derive and validate a brain glucose metabolism pattern related to phenoconversion in iRBD (iRBDconvRP) using spatial covariance analysis (Scaled Subprofile Model and Principal Component Analysis [SSM-PCA]). METHODS: Seventy-six consecutive iRBD patients (70 ± 6 years, 15 women) were enrolled in two centers and prospectively evaluated to assess phenoconversion (30 converters, 73 ± 6 years, 14 Parkinson's disease and 16 dementia with Lewy bodies, follow-up time: 21 ± 14 months; 46 nonconverters, 69 ± 6 years, follow-up time: 33 ± 19 months). All patients underwent [18 F]FDG-PET (18 F-fluorodeoxyglucose positron emitting tomography) to investigate brain glucose metabolism at baseline. SSM-PCA was applied to obtain the iRBDconvRP; nonconverter patients were considered as the reference group. Survival analysis and Cox regression were applied to explore prediction power. RESULTS: First, we derived and validated two distinct center-specific iRBDconvRP that were comparable and significantly able to predict phenoconversion. Then, SSM-PCA was applied to the whole set, identifying the iRBDconvRP. The iRBDconvRP included positive voxel weights in cerebellum; brainstem; anterior cingulate cortex; lentiform nucleus; and middle, mesial temporal, and postcentral areas. Negative voxel weights were found in posterior cingulate, precuneus, middle frontal gyrus, and parietal areas. Receiver operating characteristic analysis showed an area under the curve of 0.85 (sensitivity: 87%, specificity: 72%), discriminating converters from nonconverters. The iRBDconvRP significantly predicted phenoconversion (hazard ratio: 7.42, 95% confidence interval: 2.6-21.4). CONCLUSIONS: We derived and validated an iRBDconvRP to efficiently discriminate converter from nonconverter iRBD patients. [18 F]FDG-PET pattern analysis has potential as a phenoconversion biomarker in iRBD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neuropsychological evaluation of phenoconversion risk in REM sleep behaviour disorder: A scoping review.

The objective of this study was to assess the role of cognitive evaluation in the prediction of phenoconversion in polysomnography-confirmed idiopathic or isolated rapid eye movement sleep behaviour disorder, through a scoping review focussing on a longitudinal comprehensive neuropsychological assessment of patients with idiopathic REM sleep behaviour disorder. A literature search (2006-2022) yielded 1034 records, and 20 were selected for analysis. The sample included 899 patients from eight different cohorts and five countries. We extracted data on clinical evolution, mild cognitive impairment diagnosis, neuropsychological tests used, and classification of cognitive domains. Tests, cognitive domains, and mild cognitive impairment definitions were heterogeneous across the studies, precluding a meta-analysis. Ten studies (50%) evaluated the presence of mild cognitive impairment; 14 studies (70%) grouped neuropsychological tests into between three (6 studies, 21.4%) and seven (1 study, 7.1%) cognitive domains. The most frequently used tests were semantic fluency, Stroop colour word test, trail making test A and B, digit span, Rey auditory verbal learning test, and Rey-Osterrieth figure. All except digit span showed a role in predicting phenoconversion. The authors did not consistently assign tests to specific cognitive domains. In conclusion, we discuss methodological differences between the studies and highlight the need for a standardised framework for neuropsychological data acquisition and presentation, based on a multilevel approach covering test selection, domain assignment, and mild cognitive impairment diagnostic criteria.

Clinical and dopaminergic imaging characteristics of the FARPRESTO cohort of trial-ready idiopathic rapid eye movement sleep behavior patients.

INTRODUCTION: Idiopathic/isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is considered the prodromal stage of alpha-synucleinopathies. Thus, iRBD patients are the ideal target for disease-modifying therapy. The risk FActoRs PREdictive of phenoconversion in iRBD Italian STudy (FARPRESTO) is an ongoing Italian database aimed at identifying risk factors of phenoconversion, and eventually to ease clinical trial enrollment of well-characterized subjects. METHODS: Polysomnography-confirmed iRBD patients were retrospectively and prospectively enrolled. Baseline harmonized clinical and nigrostriatal functioning data were collected at baseline. Nigrostriatal functioning was evaluated by dopamine transporter-single-photon emission computed tomography (DaT-SPECT) and categorized with visual semi-quantification. Longitudinal data were evaluated to assess phenoconversion. Cox regressions were applied to calculate hazard ratios. RESULTS: 365 patients were enrolled, and 289 patients with follow-up (age 67.7 ± 7.3 years, 237 males, mean follow-up 40 ± 37 months) were included in this study. At follow-up, 97 iRBD patients (33.6%) phenoconverted to an overt synucleinopathy. Older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression, and visual semi-quantification of nigrostriatal functioning predicted phenoconversion. The remaining 268 patients are in follow-up within the FARPRESTO project. CONCLUSIONS: Clinical data (older age, motor and cognitive impairment, constipation, urinary and sexual dysfunction, depression) predicted phenoconversion in this multicenter, longitudinal, observational study. A standardized visual approach for semi-quantification of DaT-SPECT is proposed as a practical risk factor for phenoconversion in iRBD patients. Of note, non-converted and newly diagnosed iRBD patients, who represent a trial-ready cohort for upcoming disease-modification trials, are currently being enrolled and followed in the FARPRESTO study. New data are expected to allow better risk characterization.

Resting State Alpha Electroencephalographic Rhythms Are Affected by Sex in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment: A Retrospective and Exploratory Study.

In the present retrospective and exploratory study, we tested the hypothesis that sex may affect cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer's disease and mild cognitive impairment (ADMCI). Datasets in 69 ADMCI and 57 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands and fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into matched females and males. The sex factor affected the magnitude of rsEEG source activities in the Nold seniors. Compared with the males, the females were characterized by greater alpha source activities in all cortical regions. Similarly, the parietal, temporal, and occipital alpha source activities were greater in the ADMCI-females than the males. Notably, the present sex effects did not depend on core genetic (APOE4), neuropathological (Aß42/phospho-tau ratio in the cerebrospinal fluid), structural neurodegenerative and cerebrovascular (MRI) variables characterizing sporadic AD-related processes in ADMCI seniors. These results suggest the sex factor may significantly affect neurophysiological brain neural oscillatory synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms to regulate cortical arousal during quiet vigilance.

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.

Evaluation of iron overload in nigrosome 1 via quantitative susceptibility mapping as a progression biomarker in prodromal stages of synucleinopathies.

Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies, such as Parkinson's disease (PD), which are characterized by the loss of dopaminergic neurons in substantia nigra, associated with abnormal iron load. The assessment of presymptomatic biomarkers predicting the onset of neurodegenerative disorders is critical for monitoring early signs, screening patients for neuroprotective clinical trials and understanding the causal relationship between iron accumulation processes and disease development. Here, we used Quantitative Susceptibility Mapping (QSM) and 7T MRI to quantify iron deposition in Nigrosome 1 (N1) in early PD (ePD) patients, iRBD patients and healthy controls and investigated group differences and correlation with disease progression. We evaluated the radiological appearance of N1 and analyzed its iron content in 35 ePD, 30 iRBD patients and 14 healthy controls via T2*-weighted sequences and susceptibility (χ) maps. N1 regions of interest (ROIs) were manually drawn on control subjects and warped onto a study-specific template to obtain probabilistic N1 ROIs. For each subject the N1 with the highest mean χ was considered for statistical analysis. The appearance of N1 was rated pathological in 45% of iRBD patients. ePD patients showed increased N1 χ compared to iRBD patients and HC but no correlation with disease duration, indicating that iron load remains stable during the early stages of disease progression. Although no difference was reported in iron content between iRBD and HC, N1 χ in the iRBD group increases as the disease evolves. QSM can reveal temporal changes in N1 iron content and its quantification may represent a valuable presymptomatic biomarker to assess neurodegeneration in the prodromal stages of PD.

Transfreq: A Python package for computing the theta-to-alpha transition frequency from resting state electroencephalographic data.

A classic approach to estimate individual theta-to-alpha transition frequency (TF) requires two electroencephalographic (EEG) recordings, one acquired in a resting state condition and one showing alpha desynchronisation due, for example, to task execution. This translates into long recording sessions that may be cumbersome in studies involving patients. Moreover, an incomplete desynchronisation of the alpha rhythm may compromise TF estimates. Here we present transfreq, a publicly available Python library that allows TF computation from resting state data by clustering the spectral profiles associated to the EEG channels based on their content in alpha and theta bands. A detailed overview of transfreq core algorithm and software architecture is provided. Its effectiveness and robustness across different experimental setups are demonstrated on a publicly available EEG data set and on in-house recordings, including scenarios where the classic approach fails to estimate TF. We conclude with a proof of concept of the predictive power of transfreq TF as a clinical marker. Specifically, we present a scenario where transfreq TF shows a stronger correlation with the mini mental state examination score than other widely used EEG features, including individual alpha peak and median/mean frequency. The documentation of transfreq and the codes for reproducing the analysis of the article with the open-source data set are available online at https://elisabettavallarino.github.io/transfreq/. Motivated by the results showed in this article, we believe our method will provide a robust tool for discovering markers of neurodegenerative diseases.

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.

Added value of semiquantitative analysis of brain FDG-PET for the differentiation between MCI-Lewy bodies and MCI due to Alzheimer's disease.

PURPOSE: FDG-PET is an established supportive biomarker in dementia with Lewy bodies (DLB), but its diagnostic accuracy is unknown at the mild cognitive impairment (MCI-LB) stage when the typical metabolic pattern may be difficultly recognized at the individual level. Semiquantitative analysis of scans could enhance accuracy especially in less skilled readers, but its added role with respect to visual assessment in MCI-LB is still unknown. METHODS: We assessed the diagnostic accuracy of visual assessment of FDG-PET by six expert readers, blind to diagnosis, in discriminating two matched groups of patients (40 with prodromal AD (MCI-AD) and 39 with MCI-LB), both confirmed by in vivo biomarkers. Readers were provided in a stepwise fashion with (i) maps obtained by the univariate single-subject voxel-based analysis (VBA) with respect to a control group of 40 age- and sex-matched healthy subjects, and (ii) individual odds ratio (OR) plots obtained by the volumetric regions of interest (VROI) semiquantitative analysis of the two main hypometabolic clusters deriving from the comparison of MCI-AD and MCI-LB groups in the two directions, respectively. RESULTS: Mean diagnostic accuracy of visual assessment was 76.8 ± 5.0% and did not significantly benefit from adding the univariate VBA map reading (77.4 ± 8.3%) whereas VROI-derived OR plot reading significantly increased both accuracy (89.7 ± 2.3%) and inter-rater reliability (ICC 0.97 [0.96-0.98]), regardless of the readers' expertise. CONCLUSION: Conventional visual reading of FDG-PET is moderately accurate in distinguishing between MCI-LB and MCI-AD, and is not significantly improved by univariate single-subject VBA but by a VROI analysis built on macro-regions, allowing for high accuracy independent of reader skills.

Stratification Tools for Disease-Modifying Trials in Prodromal Synucleinopathy.

BACKGROUND: Dopamine transporter single photon-emission computed tomography (DAT-SPECT) is the strongest risk factor for phenoconversion in patients with idiopathic rapid eye movement (REM)-sleep behavior disorder (iRBD). However, it might be used as a second-line stratification tool in clinical trials, because it is expensive and mini-invasive. OBJECTIVE: Aim of the study is to investigate whether other cost-effective and non-invasive biomarkers may be proposed as first-line stratification tools. METHODS: Forty-seven consecutive iRBD patients (68.53 ± 7.16 years, 40 males) underwent baseline clinical and neuropsychological assessment, olfaction test, resting electroencephalogram (EEG), and DAT-SPECT. All patients underwent 6 month-based clinical follow-up to investigate the emergence of parkinsonism and/or dementia. Survival analysis and Cox regression were used to estimate conversion risk. RESULTS: Seventeen patients developed an overt synucleinopathy (eight Parkinsonism and nine dementia) 32.8 ± 22 months after diagnosis. The strongest risk factors were putamen specific to non-displaceable binding ratio (SBR) (hazard ratio [HR], 7.3), attention/working memory cognitive function (NPS-AT/WM) (HR, 5.9), EEG occipital mean frequency (HR, 2.7) and clinical motor assessment (HR, 2.3). On multivariate Cox-regression analysis, only putamen SBR and NPS-AT/WM significantly contributed to the model (HR, 6.2, 95% confidence interval [CI], 1.9-19.8). At post-hoc analysis, the trail-making test B (TMT-B) was the single most efficient first-line stratification tool that allowed to reduce the number of eligible subjects to 76.6% (sensitivity 1, specificity 0.37). Combining TMT-B and DAT-SPECT further reduced the sample to 66% (sensitivity 0.88, specificity 0.47). CONCLUSION: The TMT-B seems to be a cost-effective and efficient first-line screening tool, to be used to select patients that deserve DAT-SPECT as second-line screening tool for disease-modifying clinical trials. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Dopaminergic imaging and clinical predictors for phenoconversion of REM sleep behaviour disorder.

This is an international multicentre study aimed at evaluating the combined value of dopaminergic neuroimaging and clinical features in predicting future phenoconversion of idiopathic REM sleep behaviour (iRBD) subjects to overt synucleinopathy. Nine centres sent 123I-FP-CIT-SPECT data of 344 iRBD patients and 256 controls for centralized analysis. 123I-FP-CIT-SPECT images were semiquantified using DaTQUANTTM, obtaining putamen and caudate specific to non-displaceable binding ratios (SBRs). The following clinical variables were also analysed: (i) Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale, motor section score; (ii) Mini-Mental State Examination score; (iii) constipation; and (iv) hyposmia. Kaplan-Meier survival analysis was performed to estimate conversion risk. Hazard ratios for each variable were calculated with Cox regression. A generalized logistic regression model was applied to identify the best combination of risk factors. Bayesian classifier was used to identify the baseline features predicting phenoconversion to parkinsonism or dementia. After quality check of the data, 263 iRBD patients (67.6 ± 7.3 years, 229 males) and 243 control subjects (67.2 ± 10.1 years, 110 males) were analysed. Fifty-two (20%) patients developed a synucleinopathy after average follow-up of 2 years. The best combination of risk factors was putamen dopaminergic dysfunction of the most affected hemisphere on imaging, defined as the lower value between either putamina (P < 0.000001), constipation, (P < 0.000001) and age over 70 years (P = 0.0002). Combined features obtained from the generalized logistic regression achieved a hazard ratio of 5.71 (95% confidence interval 2.85-11.43). Bayesian classifier suggested that patients with higher Mini-Mental State Examination score and lower caudate SBR asymmetry were more likely to develop parkinsonism, while patients with the opposite pattern were more likely to develop dementia. This study shows that iRBD patients older than 70 with constipation and reduced nigro-putaminal dopaminergic function are at high risk of short-term phenoconversion to an overt synucleinopathy, providing an effective stratification approach for future neuroprotective trials. Moreover, we provide cut-off values for the significant predictors of phenoconversion to be used in single subjects.

Abnormalities of Cortical Sources of Resting State Alpha Electroencephalographic Rhythms are Related to Education Attainment in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment.

In normal old (Nold) and Alzheimer's disease (AD) persons, a high cognitive reserve (CR) makes them more resistant and resilient to brain neuropathology and neurodegeneration. Here, we tested whether these effects may affect neurophysiological oscillatory mechanisms generating dominant resting state electroencephalographic (rsEEG) alpha rhythms in Nold and patients with mild cognitive impairment (MCI) due to AD (ADMCI). Data in 60 Nold and 70 ADMCI participants, stratified in higher (Edu+) and lower (Edu-) educational attainment subgroups, were available in an Italian-Turkish archive. The subgroups were matched for age, gender, and education. RsEEG cortical sources were estimated by eLORETA freeware. As compared to the Nold-Edu- subgroup, the Nold-Edu+ subgroup showed greater alpha source activations topographically widespread. On the contrary, in relation to the ADMCI-Edu- subgroup, the ADMCI-Edu+ subgroup displayed lower alpha source activations topographically widespread. Furthermore, the 2 ADMCI subgroups had matched cerebrospinal AD diagnostic biomarkers, brain gray-white matter measures, and neuropsychological scores. The current findings suggest that a high CR may be related to changes in rsEEG alpha rhythms in Nold and ADMCI persons. These changes may underlie neuroprotective effects in Nold seniors and subtend functional compensatory mechanisms unrelated to brain structure alterations in ADMCI patients.