Neurocognitive mechanisms of emotional interference in native and foreign languages: evidence from proficient bilinguals.

Currently available data show mixed results as to whether the processing of emotional information has the same characteristics in the native (L1) as in the second language (L2) of bilinguals. We conducted a functional magnetic resonance imaging (fMRI) experiment to shed light on the neurocognitive mechanisms underlying bilinguals' emotional processing in L1 and L2 during an emotional interference task (i.e., the Emotional Stroop Task - EST). Our sample comprised proficient Italian-English bilinguals who learned their L2 during childhood mainly in instructional rather than immersive contexts. In spite of no detectable behavioural effects, we found stronger brain activations for L1 versus L2 emotional words in sectors of the posteromedial cortex involved in attention modulation, episodic memory, and affective processing. While fMRI findings are consistent with the hypothesis of a stronger emotional resonance when processing words in a native language, our overall pattern of results points to the different sensitivity of behavioural and hemodynamic responses to emotional information in the two languages of bilingual speakers.

Development of a prediction model of conversion to Alzheimer's disease in people with mild cognitive impairment: the statistical analysis plan of the INTERCEPTOR project.

BACKGROUND: In recent years, significant efforts have been directed towards the research and development of disease-modifying therapies for dementia. These drugs focus on prodromal (mild cognitive impairment, MCI) and/or early stages of Alzheimer's disease (AD). Literature evidence indicates that a considerable proportion of individuals with MCI do not progress to dementia. Identifying individuals at higher risk of developing dementia is essential for appropriate management, including the prescription of new disease-modifying therapies expected to become available in clinical practice in the near future. METHODS: The ongoing INTERCEPTOR study is a multicenter, longitudinal, interventional, non-therapeutic cohort study designed to enroll 500 individuals with MCI aged 50-85 years. The primary aim is to identify a biomarker or a set of biomarkers able to accurately predict the conversion from MCI to AD dementia within 3 years of follow-up. The biomarkers investigated in this study are neuropsychological tests (mini-mental state examination (MMSE) and delayed free recall), brain glucose metabolism ([18F]FDG-PET), MRI volumetry of the hippocampus, EEG brain connectivity, cerebrospinal fluid (CSF) markers (p-tau, t-tau, Aß1-42, Aß1-42/1-40 ratio, Aß1-42/p-Tau ratio) and APOE genotype. The baseline visit includes a full cognitive and neuropsychological evaluation, as well as the collection of clinical and socio-demographic information. Prognostic models will be developed using Cox regression, incorporating individual characteristics and biomarkers through stepwise selection. Model performance will be evaluated in terms of discrimination and calibration and subjected to internal validation using the bootstrapping procedure. The final model will be visually represented as a nomogram. DISCUSSION: This paper contains a detailed description of the statistical analysis plan to ensure the reproducibility and transparency of the analysis. The prognostic model developed in this study aims to identify the population with MCI at higher risk of developing AD dementia, potentially eligible for drug prescriptions. The nomogram could provide a valuable tool for clinicians for risk stratification and early treatment decisions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03834402. Registered on February 8, 2019.

Coupling motor evoked potentials and brain [18F]FDG-PET in Amyotrophic Lateral Sclerosis: preliminary findings on disease severity.

BACKGROUND: The diagnosis of amyotrophic lateral sclerosis (ALS) is primarily clinical, supported by the electromyographic examination to reveal signs of lower motor neuron damage. Identifying reliable markers of upper motor neuron (UMN) involvement is challenging. On this regard, the role of transcranial magnetic stimulation-induced motor-evoked potentials (TMS-MEPs), and its relationship with UMN burden, is still under investigation. OBJECTIVE: To evaluate the ability of TMS-MEPs in delineating the neurophysiological UMN damage, and to determine the relationship between TMS-MEPs and [18F]FDG-PET measures of neural dysfunction. METHODS: We retrospectively selected 13 ALS patients who underwent, during the diagnostic process, the TMS-MEPs and [18F]FDG-PET scans. Demographic and clinical data were collected. For the MEP evaluation, we considered normal MEP, absent MEP, or significantly increased central-motor-conduction-time. For [18F]FDG-PET, we conducted voxel-wise analyses, both at single-subject and group levels, exploring hypometabolism and hypermetabolism patterns in comparison with a large dataset of healthy controls (HC). RESULTS: Based on TMS-MEPs, we identified 4/13 patients with normal MEP in all limbs (GROUP-NO), while 9/13 had an abnormal MEP in at least one limb (GROUP-AB). Despite the [18F]FDG-PET single-subject analysis revealed heterogenous expression of regional hypo- and hyper-metabolism patterns in the patients, the group-level analysis revealed a common hypometabolism, involving the precentral gyrus and the supplementary motor area, the paracentral lobule and the anterior cingulate cortex in the GROUP-AB. Moreover, exclusively for the GROUP-AB compared with HC, a relative hypermetabolism was observed in the right cerebellum, right inferior and middle temporal gyrus. The GROUP-NO showed no specific cluster of hypo- and hyper-metabolism compared to HC. CONCLUSION: This study showed altered brain metabolism only in the ALS group with abnormal MEPs, suggesting an association between the two biomarkers in defining the UMN damage.

Sharing brain imaging data in the Open Science era: how and why?

The sharing of human neuroimaging data has great potential to accelerate the development of imaging biomarkers in neurological and psychiatric disorders; however, major obstacles remain in terms of how and why to share data in the Open Science context. In this Health Policy by the European Cluster for Imaging Biomarkers, we outline the current main opportunities and challenges based on the results of an online survey disseminated among senior scientists in the field. Although the scientific community fully recognises the importance of data sharing, technical, legal, and motivational aspects often prevent active adoption. Therefore, we provide practical advice on how to overcome the technical barriers. We also call for a harmonised application of the General Data Protection Regulation across EU countries. Finally, we suggest the development of a system that makes data count by recognising the generation and sharing of data as a highly valuable contribution to the community.

A deep learning model for generating [18F]FDG PET Images from early-phase [18F]Florbetapir and [18F]Flutemetamol PET images.

INTRODUCTION: Amyloid-ß (Aß) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([18F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunction and disease progression and is complementary for AD diagnosis. Dual-scan acquisitions of amyloid PET allows the possibility to use early-phase amyloid-PET as a biomarker for neurodegeneration, proven to have a good correlation to [18F]FDG PET. The aim of this study was to evaluate the added value of synthesizing the later from the former through deep learning (DL), aiming at reducing the number of PET scans, radiation dose, and discomfort to patients. METHODS: A total of 166 subjects including cognitively unimpaired individuals (N = 72), subjects with mild cognitive impairment (N = 73) and dementia (N = 21) were included in this study. All underwent T1-weighted MRI, dual-phase amyloid PET scans using either Fluorine-18 Florbetapir ([18F]FBP) or Fluorine-18 Flutemetamol ([18F]FMM), and an [18F]FDG PET scan. Two transformer-based DL models called SwinUNETR were trained separately to synthesize the [18F]FDG from early phase [18F]FBP and [18F]FMM (eFBP/eFMM). A clinical similarity score (1: no similarity to 3: similar) was assessed to compare the imaging information obtained by synthesized [18F]FDG as well as eFBP/eFMM to actual [18F]FDG. Quantitative evaluations include region wise correlation and single-subject voxel-wise analyses in comparison with a reference [18F]FDG PET healthy control database. Dice coefficients were calculated to quantify the whole-brain spatial overlap between hypometabolic ([18F]FDG PET) and hypoperfused (eFBP/eFMM) binary maps at the single-subject level as well as between [18F]FDG PET and synthetic [18F]FDG PET hypometabolic binary maps. RESULTS: The clinical evaluation showed that, in comparison to eFBP/eFMM (average of clinical similarity score (CSS) = 1.53), the synthetic [18F]FDG images are quite similar to the actual [18F]FDG images (average of CSS = 2.7) in terms of preserving clinically relevant uptake patterns. The single-subject voxel-wise analyses showed that at the group level, the Dice scores improved by around 13% and 5% when using the DL approach for eFBP and eFMM, respectively. The correlation analysis results indicated a relatively strong correlation between eFBP/eFMM and [18F]FDG (eFBP: slope = 0.77, R2 = 0.61, P-value < 0.0001); eFMM: slope = 0.77, R2 = 0.61, P-value < 0.0001). This correlation improved for synthetic [18F]FDG (synthetic [18F]FDG generated from eFBP (slope = 1.00, R2 = 0.68, P-value < 0.0001), eFMM (slope = 0.93, R2 = 0.72, P-value < 0.0001)). CONCLUSION: We proposed a DL model for generating the [18F]FDG from eFBP/eFMM PET images. This method may be used as an alternative for multiple radiotracer scanning in research and clinical settings allowing to adopt the currently validated [18F]FDG PET normal reference databases for data analysis.

Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response.

Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.

The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes.

OBJECTIVES: Mild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, including brain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up. METHODS: We included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data. RESULTS: The algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline. INTERPRETATION: aMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.

Heterogeneity and overlap in the continuum of linguistic profile of logopenic and semantic variants of primary progressive aphasia: a Profile Analysis based on Multidimensional Scaling study.

BACKGROUND: Primary progressive aphasia (PPA) diagnostic criteria underestimate the complex presentation of semantic (sv) and logopenic (lv) variants, in which symptoms partially overlap, and mixed clinical presentation (mixed-PPA) and heterogenous profile (lvPPA +) are frequent. Conceptualization of similarities and differences of these clinical conditions is still scarce. METHODS: Lexical, semantic, phonological, and working memory errors from nine language tasks of sixty-seven PPA were analyzed using Profile Analysis based on Multidimensional Scaling, which allowed us to create a distributed representation of patients' linguistic performance in a shared space. Patients had been studied with [18F] FDG-PET. Correlations were performed between metabolic and behavioral data. RESULTS: Patients' profiles were distributed across a continuum. All PPA, but two, presented a lexical retrieval impairment, in terms of reduced production of verbs and nouns. svPPA patients occupied a fairly clumped space along the continuum, showing a preponderant semantic deficit, which correlated to fusiform gyrus hypometabolism, while only few presented working memory deficits. Adjacently, lvPPA + presented a semantic impairment combined with phonological deficits, which correlated with metabolism in the anterior fusiform gyrus and posterior middle temporal gyrus. Starting from the shared phonological deficit side, a large portion of the space was occupied by all lvPPA, showing a combination of phonological, lexical, and working memory deficits, with the latter correlating with posterior temporo-parietal hypometabolism. Mixed PPA did not show unique profile, distributing across the space. DISCUSSION: Different clinical PPA entities exist but overlaps are frequent. Identifying shared and unique clinical markers is critical for research and clinical practice. Further research is needed to identify the role of genetic and pathological factors in such distribution, including also higher sample size of less represented groups.

Mapping brain metabolism, connectivity and neurotransmitters topography in early and late onset dementia with lewy bodies.

INTRODUCTION: Early-onset dementia with Lewy bodies (EO-DLB) is associated with rapid cognitive decline and severe neuropsychiatric symptoms at onset. METHODS: Using FDG-PET imaging for 62 patients (21 EO-DLB, 41 LO (late-onset)-DLB), we explored brain hypometabolism, and metabolic connectivity in the whole-brain network and resting-state networks (RSNs). We also evaluated the spatial association between brain hypometabolism and neurotransmitter pathways topography. RESULTS: Direct comparisons between the two clinical subgroups showed that EO-DLB was characterized by a lower metabolism in posterior cingulate/precuneus and occipital cortex. Metabolic connectivity analysis revealed significant alterations in posterior regions in both EO-DLB and LO-DLB. The EO-DLB, however, showed more severe loss of connectivity between occipital and parietal nodes and hyperconnectivity between frontal and cerebellar nodes. Spatial topography association analysis indicated significant correlations between neurotransmitter maps (i.e. acetylcholine, GABA, serotonin, dopamine) and brain hypometabolism in both EO and LO-DLB, with significantly higher metabolic correlation in the presynaptic serotonergic system for EO-DLB, supporting its major dysfunction. CONCLUSIONS: Our study revealed greater brain hypometabolism and loss of connectivity in posterior brain region in EO- than LO-DLB. Serotonergic mapping emerges as a relevant factor for further investigation addressing clinical differences between DLB subtypes.

Distinctive clinical and imaging trajectories in SWEDD and Parkinson's disease patients.

A proportion of patients clinically diagnosed with Parkinson's disease (PD) can have a 123I-FP-CIT-SPECT scan without evidence of dopaminergic deficit (SWEDD), generating a debate about the underlying biological mechanisms. This study investigated differences in clinical features, 123I-FP-CIT binding, molecular connectivity, as well as clinical and imaging progression between SWEDD and PD patients. We included 36 SWEDD, 49 de novo idiopathic PD, and 49 healthy controls with 123I-FP-CIT-SPECT from the Parkinson's Progression Markers Initiative. Clinical and imaging 2-year follow-ups were available for 27 SWEDD and 40 PD. Regional-based and voxel-wise analysis assessed dopaminergic integrity in dorsal and ventral striatal, as well as extrastriatal regions, at baseline and follow-up. Molecular connectivity analyses evaluated dopaminergic pathways. Spatial correlation analyses tested whether 123I-FP-CIT-binding alterations would also pertain to the serotoninergic system. SWEDD and PD patients showed comparable symptoms at baseline, except for hyposmia, which was more severe for PD. PD showed significantly lower striatal and extrastriatal 123I-FP-CIT-binding compared to SWEDD and controls. SWEDD exhibited lower binding than controls in striatal regions, insula, and olfactory cortex. Both PD and SWEDD showed extensive altered connectivity of dopaminergic pathways, however, with major impairment in the mesocorticolimbic system for SWEDD. Motor symptoms and dopaminergic deficits worsened after 2 years for PD only. The limited dopaminergic impairment and its stability over time observed for SWEDD, as well as the presence of extrastriatal 123I-FP-CIT binding alterations and prevalent mesocorticolimbic connectivity impairment, suggest other mechanisms contributing to SWEDD pathophysiology.

The role of parietal beta-band activity in the resolution of visual crowding.

Visual crowding is the difficulty in identifying an object when surrounded by neighbouring flankers, representing a bottleneck for object perception. Crowding arises not only from the activity of visual areas but also from parietal areas and fronto-parietal network activity. Parietal areas would provide the dorsal-to-ventral guidance for object identification and the fronto-parietal network would modulate the attentional resolution. Several studies highlighted the relevance of beta oscillations (15-25 Hz) in these areas for visual crowding and other connatural visual phenomena. In the present study, we investigated the differential contribution of beta oscillations in the parietal cortex and fronto-parietal network in the resolution of visual crowding. During a crowding task with letter stimuli, high-definition transcranial Alternating Current Stimulation (tACS) in the beta band (18 Hz) was delivered bilaterally on parietal sites, on the right fronto-parietal network, and in a sham regime. Resting-state EEG was recorded before and after stimulation to measure tACS-induced aftereffects. The influence of crowding was reduced only when tACS was delivered bilaterally on parietal sites. In this condition, beta power was reduced after the stimulation. Furthermore, the magnitude of tACS-induced aftereffects varied as a function of individual differences in beta oscillations. Results corroborate the link between parietal beta oscillations and visual crowding, providing fundamental insights on brain rhythms underlying the dorsal-to-ventral guidance in visual perception and suggesting that beta tACS can induce plastic changes in these areas. Remarkably, these findings open new possibilities for neuromodulatory interventions for disorders characterised by abnormal crowding, such as dyslexia.

Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis.

BACKGROUND: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid ß in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING: None.

The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline.

INTRODUCTION: Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. METHODS: We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. RESULTS: Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32). DISCUSSION: Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. HIGHLIGHTS: Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.

FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI.

INTRODUCTION: Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition. METHODS: We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression. RESULTS: Three subtypes emerged: hippocampal sparing-cortical hypometabolism, associated with younger age and the highest level of Alzheimer's disease (AD)-CSF pathology; hippocampal/cortical hypometabolism, associated with a high percentage of APOE ε3/ε4 or ε4/ε4 carriers; medial-temporal hypometabolism, characterized by older age, the lowest AD-CSF pathology, the most severe hippocampal atrophy, and a benign course. Within the whole cohort, the severity of temporo-parietal hypometabolism, correlated with AD-CSF pathology and marked the rate of progression of cognitive decline. DISCUSSION: FDG-PET can distinguish clinically comparable aMCI at single-subject level with different risk of progression to AD dementia or stability. The obtained results can be useful for the optimization of pharmacological trials and automated-classification models. HIGHLIGHTS: Algorithm based on FDG-PET hypometabolism demonstrates distinct subtypes across aMCI; Three different subtypes show heterogeneous biological profiles and risk of progression; The cortical hypometabolism is associated with AD pathology and cognitive decline; MTL hypometabolism is associated with the lowest conversion rate and CSF-AD pathology.

Atypical brain FDG-PET patterns increase the risk of long-term cognitive and motor progression in Parkinson's disease.

INTRODUCTION: Brain hypometabolism patterns have been previously associated with cognitive decline in Parkinson's disease (PD). Our aim is to evaluate the impact of single-subject fluorodeoxyglucose (FDG)-PET brain hypometabolism on long-term cognitive and motor outcomes in PD. METHODS: Forty-nine non-demented PD patients with baseline brain FDG-PET data underwent an extensive clinical follow-up for 8 years. The ability of FDG-PET to predict long-term cognitive and motor progression was evaluated using Cox regression and mixed ANCOVA models. RESULTS: Participants were classified according to FDG-PET pattern in PD with typical (n = 26) and atypical cortical metabolism (n = 23). Patients with atypical brain hypometabolic patterns showed higher incidence of dementia (60% vs 3%; HR = 18.3), hallucinations (56% vs 7%, HR = 7.3) and faster motor decline compared to typical pattern group. CONCLUSION: This study argues for specific patterns of FDG-PET cortical hypometabolism in PD as a prognostic marker for long term cognitive and motor outcomes at single-subject level.

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

BACKGROUND: Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies. METHODS: We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA). RESULTS: The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941). CONCLUSIONS: SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.

Occipital hypometabolism is a risk factor for conversion to Parkinson's disease in isolated REM sleep behaviour disorder.

PURPOSE: Isolated REM sleep behaviour disorder (iRBD) patients are at high risk of developing clinical syndromes of the α-synuclein spectrum. Progression markers are needed to determine the neurodegenerative changes and to predict their conversion. Brain imaging with 18F-FDG PET in iRBD is promising, but longitudinal studies are scarce. We investigated the regional brain changes in iRBD over time, related to phenoconversion. METHODS: Twenty iRBD patients underwent two consecutive 18F-FDG PET brain scans and clinical assessments (3.7 ± 0.6 years apart). Seventeen patients also underwent 123I-MIBG and 123I-FP-CIT SPECT scans at baseline. Four subjects phenoconverted to Parkinson's disease (PD) during follow-up. 18F-FDG PET scans were compared to controls with a voxel-wise single-subject procedure. The relationship between regional brain changes in metabolism and PD-related pattern scores (PDRP) was investigated. RESULTS: Individual hypometabolism t-maps revealed three scenarios: (1) normal 18F-FDG PET scans at baseline and follow-up (N = 10); (2) normal scans at baseline but occipital or occipito-parietal hypometabolism at follow-up (N = 4); (3) occipital hypometabolism at baseline and follow-up (N = 6). All patients in the last group had pathological 123I-MIBG and 123I-FP-CIT SPECT. iRBD converters (N = 4) showed occipital hypometabolism at baseline (third scenario). At the group level, hypometabolism in the frontal and occipito-parietal regions and hypermetabolism in the cerebellum and limbic regions were progressive over time. PDRP z-scores increased over time (0.54 ± 0.36 per year). PDRP expression was driven by occipital hypometabolism and cerebellar hypermetabolism. CONCLUSIONS: Our results suggest that occipital hypometabolism at baseline in iRBD implies a short-term conversion to PD. This might help in stratification strategies for disease-modifying trials.

Comparing two picture naming tasks in primary progressive aphasia: Insights from behavioural and neural results.

Picture naming tests are widely used to evaluate language impairments in neurodegenerative diseases, especially in Primary Progressive Aphasia (PPA). The available tests differ for many factors affecting the performance, e.g. format of stimuli and their psycholinguistic properties. We aim to identify the most appropriate naming test to be used on PPA according to the clinical and research demands. We investigated the behavioural characteristics, i.e. proportion of correct responses and error type, and their neural correlates in two Italian naming tests, CaGi naming (CaGi) and naming subtest of the Screening for Aphasia in NeuroDegeneration battery (SAND), administered to 52 PPA patients who underwent an FDG-PET scan. We analysed the effectiveness of the tests in distinguishing PPA versus controls and among PPA variants, considering the psycholinguistic variables affecting performance. We explored the brain metabolic correlates of behavioural performance in the tests. SAND, differently from CaGi, has time limits for the response and its items are less frequent and acquired later. SAND and CaGi differed in terms of number of correct responses and error profile, suggesting a higher difficulty to name SAND items compared to CaGi. Semantic errors predominated in CaGi, while anomic and semantic errors were equally frequent in SAND. Both tests distinguished PPA from controls, but SAND outperformed CaGi in discriminating among PPA variants. FDG-PET imaging revealed a shared metabolic involvement of temporal areas associated with lexico-semantic processing, encompassing anterior fusiform, temporal pole, and extending to posterior fusiform in sv-PPA. Concluding, a picture naming test with response time limit and items which are less frequent and acquired later in life, as SAND, may be effective at highlighting subtle distinctions between PPA variants, improving the diagnosis. Conversely, a naming test without time limit for the response, as CaGi, may be useful for a better characterization of the nature of the naming impairment at the behavioural level, eliciting more naming errors than anomia, possibly helping in the development of rehabilitation protocols.

Neurobiological Dysfunctional Substrates for the Self-Medication Hypothesis in Adult Individuals with Attention-Deficit Hyperactivity Disorder and Cocaine Use Disorder: A Fluorine-18-Fluorodeoxyglucose Positron Emission Tomography Study.

Objectives: Attention-deficit hyperactivity disorder (ADHD) in adulthood shows high co-occurrence rates with cocaine use disorder (CoUD). The self-medication hypothesis (SMH) provides a theoretical explanation for this comorbidity. This study investigates the neurobiological mechanisms that could support SMH in adult patients with attention-deficit hyperactivity disorder with cocaine use disorder (ADHD-CoUD). Materials and Methods: We included 19 ADHD-CoUD patients (84.2% male; age: 32.11 years [7.18]) and 16 CoUD patients (68.7% male; age: 36.63 years [8.12]). All subjects underwent a fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG PET) brain scan. We tested brain metabolism differences between ADHD-CoUD and CoUD patients using voxel-based and regions of interest (ROIs)-based analyses. The correlation between dependence/abstinence duration and regional brain metabolism was also assessed in the two groups. Lastly, we investigated the integrity of brain metabolic connectivity of mesocorticolimbic and nigrostriatal dopaminergic systems, and large-scale brain networks involved in ADHD and addictions. Results: The voxel-wise and ROIs-based approaches showed that ADHD-CoUD patients had a lower metabolism in the thalamus and increased metabolism in the amygdala and parahippocampus, bilaterally, than CoUD subjects and healthy controls (HCs). Metabolism in the thalamus negatively correlated with years of dependence in ADHD-CoUD patients. Moreover, connectivity analyses revealed that ADHD-CoUD patients had a more preserved metabolic connectivity than CoUD patients in the dopaminergic networks and large-scale networks involved in self-regulation mechanisms of attention and behaviors (i.e., anterior default mode network [ADMN], executive network [ECN], and anterior salience network [aSAN]). Conclusions: We demonstrated distinct neuropathological substrates underlying substance-use behaviors in ADHD-CoUD and CoUD patients. Furthermore, we provided neurobiological evidence in support of SMH, demonstrating that ADHD-CoUD patients might experience short-term advantages of cocaine assumption (i.e., compensation of dopaminergic deficiency and related cognitive-behavioral deficits).