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.

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.

Persistent dysfunctions of brain metabolic connectivity in long-covid with cognitive symptoms.

PURPOSE: Our study examines brain metabolic connectivity in SARS-CoV-2 survivors during the acute-subacute and chronic phases, aiming to elucidate the mechanisms underlying the persistence of neurological symptoms in long-COVID patients. METHODS: We perfomed a cross-sectional study including 44 patients (pts) with neurological symptoms who underwent FDG-PET scans, and classified to timing infection as follows: acute (7 pts), subacute (17 pts), long-term (20 pts) phases. Interregional correlation analysis (IRCA) and ROI-based IRCA were applied on FDG-PET data to extract metabolic connectivity in resting state networks (ADMN, PDMN, EXN, ATTN, LIN, ASN) of neuro-COVID pts in acute/subacute and long-term groups compared with healthy controls (HCs). Univariate approach was used to investigate metabolic alterations from the acute to sub-acute and long-term phase. RESULTS: The acute/subacute phase was characterized by hyperconnectivity in EXN and ATTN networks; the same networks showed hypoconnectivity in the chronic phase. EXN and ATTN hypoconnectivity was consistent with clinical findings in long-COVID patients, e.g. altered performances in neuropsychological tests of executive and attention domains. The ASN and LIN presented hyperconnectivity in acute/subacute phase and normalized in long-term phase. The ADMN and PDMN presented a preseverved connectivity. Univariate analysis showed hypometabolism in fronto-insular cortex in acute phase, which reduced in sub-acute phase and disappeared in long-term phase. CONCLUSION: A compensatory EXN and ATTN hyperconnectivity was found in the acute/subacute phase and hypoconnectivity in long-term. Hypoconnectivity and absence of hypometabolism suggest that connectivity derangement in frontal networks could be related to protraction of neurological symptoms in long-term COVID patients.

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.

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.

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.

Sex differences in dementia with Lewy bodies: an imaging study of neurotransmission pathways.

PURPOSE: Dementia with Lewy bodies (DLB) is characterized by a wide clinical and biological heterogeneity, with sex differences reported in both clinical and pathologically confirmed DLB cohorts. No research evidence is available on sex differences regarding molecular neurotransmission. This study aimed to assess whether sex can influence neurotransmitter systems in patients with probable DLB (pDLB). METHODS: We included 123 pDLB patients (male/female: 77/46) and 78 control subjects (male/female: 34/44) for comparison, who underwent 123I-FP-CIT SPECT imaging. We assessed sex differences in the dopaminergic activity of the nigrostriatal and mesolimbic systems using regional-based and voxel-wise analyses of 123I-FP-CIT binding. We tested whether sex-specific binding alterations would also pertain to the serotoninergic and noradrenergic systems by applying spatial correlation analyses. We applied molecular connectivity analyses to assess potential sex differences in the dopaminergic pathways. RESULTS: We found comparable 123I-FP-CIT binding decreases in the striatum for pDLB males and females compared to controls. However, pDLB females showed lower binding in the extrastriatal projections of the nigrostriatal and mesolimbic dopaminergic systems compared to pDLB males. According to the spatial correlation analysis, sex-specific molecular alterations were also associated with serotonergic and noradrenergic systems. Nigrostriatal and mesolimbic systems' connectivity was impaired in both groups, with males showing local alterations and females presenting long-distance disconnections between subcortical and cortical regions. CONCLUSIONS: Sex-specific differences in 123I-FP-CIT binding were found in our cohort, namely, a trend for lower 123I-FP-CIT binding in females, significant in the presence of a pDLB diagnosis. pDLB females showed also different patterns of connectivity compared to males, mostly involving extrastriatal regions. The results suggest the presence of a sex-related regional vulnerability to alpha-synuclein pathology, possibly complicated also by the higher prevalence of Alzheimer's disease co-pathology in females, as previously reported in pDLB populations.

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.

Gender differences in dopaminergic system dysfunction in de novo Parkinson's disease clinical subtypes.

Parkinson's disease (PD) is characterized by heterogeneity in clinical syndromes, prognosis, and pathophysiology mechanisms. Gender differences in neural anatomy and function are emerging as fundamental determinants of phenotypic variability. Different clinical subtypes, defined as mild motor predominant, intermediate, and diffuse-malignant, have been recently proposed in PD. This study investigated gender influence on clinical features, dopaminergic dysfunction, and connectivity in patients with de novo idiopathic PD stratified according to the clinical criteria for subtypes (i.e., mild motor, intermediate, and diffuse-malignant). We included 286 drug-naïve patients (Males/Females: 189/97, age [mean ± standard deviation]: 61.99 ± 9.67; disease duration: 2.08 ± 2.21) with available [123I]FP-CIT-SPECT and high-resolution T1-weighted MRI from the Parkinson's Progression Markers Initiative. We assessed gender differences for clinical and cognitive features, and dopaminergic presynaptic dysfunction in striatal or extra-striatal regions using molecular analysis of [123I]FP-CIT-bindings. We applied an advanced multivariate analytical approach - partial correlations molecular connectivity analyses - to assess potential gender differences in the vulnerability of the nigrostriatal and mesolimbic dopaminergic pathways. In the mild motor and intermediate subtypes, male patients with idiopathic PD showed poorer cognitive performances than females, who - in contrast - presented more severe anxiety symptoms. The male vulnerability emerged also in the motor system in the same subtypes with motor impairment associated with a lower dopamine binding in the putamen and more severe widespread connectivity alterations in the nigrostriatal dopaminergic pathway in males than in females. In the diffuse-malignant subtype, males showed more severe motor impairments, consistent with a lower dopamine uptake in the putamen than females. On the other hand, a severe dopaminergic depletion in several dopaminergic targets of the mesolimbic pathway, together with extensive altered connectivity in the same system, characterized females with idiopathic PD in all the subtypes. The anxiety level was associated with a lower dopaminergic binding in the amygdala only in females. This study provides evidence on gender differences in idiopathic PD across clinical subtypes, and, remarkably, since the early phase. The clinical correlations with the nigrostriatal or mesolimbic systems in males and females support different vulnerabilities and related disease expressions. Gender differences must be considered in a precision medicine approach to preventing, diagnosing, and treating idiopathic PD.

Lifelong bilingualism and mechanisms of neuroprotection in Alzheimer dementia.

Lifelong bilingualism is associated with delayed dementia onset, suggesting a protective effect on the brain. Here, we aim to study the effects of lifelong bilingualism as a dichotomous and continuous phenomenon, on brain metabolism and connectivity in individuals with Alzheimer's dementia. Ninety-eight patients with Alzheimer's dementia (56 monolinguals; 42 bilinguals) from three centers entered the study. All underwent an [18F]-fluorodeoxyglucose positron emission tomography (PET) imaging session. A language background questionnaire measured the level of language use for conversation and reading. Severity of brain hypometabolism and strength of connectivity of the major neurocognitive networks was compared across monolingual and bilingual individuals, and tested against the frequency of second language life-long usage. Age, years of education, and MMSE score were included in all above mentioned analyses as nuisance covariates. Cerebral hypometabolism was more severe in bilingual compared to monolingual patients; severity of hypometabolism positively correlated with the degree of second language use. The metabolic connectivity analyses showed increased connectivity in the executive, language, and anterior default mode networks in bilingual compared to monolingual patients. The change in neuronal connectivity was stronger in subjects with higher second language use. All effects were most pronounced in the left cerebral hemisphere. The neuroprotective effects of lifelong bilingualism act both against neurodegenerative processes and through the modulation of brain networks connectivity. These findings highlight the relevance of lifelong bilingualism in brain reserve and compensation, supporting bilingual education and social interventions aimed at usage, and maintenance of two or more languages, including dialects, especially crucial in the elderly people.

Time-dependent recovery of brain hypometabolism in neuro-COVID-19 patients.

PURPOSE: We evaluated brain metabolic dysfunctions and associations with neurological and biological parameters in acute, subacute and chronic COVID-19 phases to provide deeper insights into the pathophysiology of the disease. METHODS: Twenty-six patients with neurological symptoms (neuro-COVID-19) and [18F]FDG-PET were included. Seven patients were acute (< 1 month (m) after onset), 12 subacute (4 ≥ 1-m, 4 ≥ 2-m and 4 ≥ 3-m) and 7 with neuro-post-COVID-19 (3 ≥ 5-m and 4 ≥ 7-9-m). One patient was evaluated longitudinally (acute and 5-m). Brain hypo- and hypermetabolism were analysed at single-subject and group levels. Correlations between severity/extent of brain hypo- and hypermetabolism and biological (oxygen saturation and C-reactive protein) and clinical variables (global cognition and Body Mass Index) were assessed. RESULTS: The "fronto-insular cortex" emerged as the hypometabolic hallmark of neuro-COVID-19. Acute patients showed the most severe hypometabolism affecting several cortical regions. Three-m and 5-m patients showed a progressive reduction of hypometabolism, with limited frontal clusters. After 7-9 months, no brain hypometabolism was detected. The patient evaluated longitudinally showed a diffuse brain hypometabolism in the acute phase, almost recovered after 5 months. Brain hypometabolism correlated with cognitive dysfunction, low blood saturation and high inflammatory status. Hypermetabolism in the brainstem, cerebellum, hippocampus and amygdala persisted over time and correlated with inflammation status. CONCLUSION: Synergistic effects of systemic virus-mediated inflammation and transient hypoxia yield a dysfunction of the fronto-insular cortex, a signature of CNS involvement in neuro-COVID-19. This brain dysfunction is likely to be transient and almost reversible. The long-lasting brain hypermetabolism seems to reflect persistent inflammation processes.

Clinical and Dopamine Transporter Imaging Trajectories in a Cohort of Parkinson's Disease Patients with GBA Mutations.

BACKGROUND: Glucosylceramidase (GBA) mutations are considered the most common genetic risk factors for developing Parkinson's disease (PD). OBJECTIVES: We aimed to assess, at different time points, the integrity of brain striatal and extra-striatal dopamine pathways and clinical phenotype of a group of PD subjects bearing heterozygous GBA mutations (GBA-PD), compared with a group of idiopathic PD patients (iPD) stratified by age at disease onset. A longitudinal approach was adopted to evaluate the progression over time for clinical and 123 I-FP-CIT SPECT imaging features. METHODS: We considered 46 GBA-PD patients and 339 iPD patients, subdivided into two groups according to age at PD onset (n = 58 < 50 years and n = 281 > 50 years). We measured differences in the occurrence/severity/progression of motor and non-motor features, 123 I-FP-CIT standard uptake value ratios (SUVr) in striatal and extra-striatal regions, and global cognitive deterioration over time in a subset of 168 cases with available follow-up. RESULTS: At baseline, the GBA-PD cohort showed more severe motor and cognitive deficits than the early-iPD cohort. The 123 I-FP-CIT SUVr reduction in the striatal and the extra-striatal regions was more marked in the GBA-PD than the early- and late-iPD cohorts. Both GBA-PD and late-iPD patients had a significant annual deterioration in their global cognitive performance, while the early-iPD group showed global cognitive stability over time. At follow-up, the iPD cohorts became similar to the GBA-PD group in 123 I-FP-CIT SUVr reduction. CONCLUSION: These new findings support the hypothesis of a biological role of GBA mutations in accelerating the early neurodegenerative processes in PD, leading to the malignant clinical phenotype. © 2021 International Parkinson and Movement Disorder Society.

Emotion Recognition Deficits in the Differential Diagnosis of Amnestic Mild Cognitive Impairment: A Cognitive Marker for the Limbic-Predominant Phenotype.

OBJECTIVE: Late-onset amnestic mild cognitive impairment (aMCI) with long disease course and slow progression has been recently recognized as a possible phenotypical expression of a limbic-predominant neurodegenerative disorder. Basic emotion recognition ability crucially depending on temporo-limbic integrity is supposed to be impaired in this group of MCI subjects presenting a selective vulnerability of medio-temporal and limbic regions. However, no study specifically investigated this issue. METHODS: Hereby, we enrolled 30 aMCI with a biomarker-based diagnosis of Alzheimer's disease (i.e., aMCI-AD, n = 16) or a biomarker evidence of selective medio-temporal and limbic degeneration (aMCI-mTLD, n = 14). Ekman-60 Faces Test (Ek-60F) was administered to each subject, comparing the performance with that of 20 healthy controls (HCs). RESULTS: aMCI-mTLD subjects showed significantly lower Ek-60F global scores compared to HC (p = 0.001), whose performance was comparable to aMCI-AD. Fear (p = 0.02), surprise (p = 0.005), and anger (p = 0.01) recognition deficits characterized the aMCI-mTLD performance. Fear recognition scores were significantly lower in aMCI-mTLD compared to aMCI-AD (p = 0.04), while no differences were found in other emotions. CONCLUSIONS: Impaired social cognition, suggested by defective performance in emotion recognition tasks, may be a useful cognitive marker to detect limbic-predominant aMCI subjects among the heterogeneous aMCI population.

Accuracy of the clinical diagnosis of dementia with Lewy bodies (DLB) among the Italian Dementia Centers: a study by the Italian DLB study group (DLB-SINdem).

INTRODUCTION: Dementia with Lewy bodies (DLB) may represent a diagnostic challenge, since its clinical picture overlaps with other dementia. Two toolkits have been developed to aid the clinician to diagnose DLB: the Lewy Body Composite Risk Score (LBCRS) and the Assessment Toolkit for DLB (AT-DLB). We aim to evaluate the reliability of these two questionnaires, and their ability to enhance the interpretation of the international consensus diagnostic criteria. METHODS: LBCRS and AT-DLB were distributed to 135 Italian Neurological Centers for Cognitive Decline and Dementia (CDCDs), with the indication to administer them to all patients with dementia referred within the subsequent 3 months. We asked to subsequently apply consensus criteria for DLB diagnosis, to validate the diagnostic accuracy of the two toolkits. RESULTS: A total of 23 Centers joined the study; 1854 patients were enrolled. We found a prevalence of possible or probable DLB of 13% each (26% total), according to the consensus criteria. LBCRS toolkit showed good reliability, with a Cronbach alpha of 0.77, stable even after removing variables from the construct. AT-DLB toolkit Cronbach alpha was 0.52 and, after the subtraction of the "cognitive fluctuation" criterion, was only 0.31. Accuracy, sensitivity, and specificity were higher for LBCRS vs. AT-DLB. However, when simultaneously considered in the logistic models, AT-DLB showed a better performance (p < 0.001). Overall, the concordance between LBCRS positive and AT-DLB possible/probable was of 78.02% CONCLUSIONS: In a clinical setting, the LBCRS and AT-DLB questionnaires have good accuracy for DLB diagnosis.

Evaluation of a 2D UNet-Based Attenuation Correction Methodology for PET/MR Brain Studies.

Deep learning (DL) strategies applied to magnetic resonance (MR) images in positron emission tomography (PET)/MR can provide synthetic attenuation correction (AC) maps, and consequently PET images, more accurate than segmentation or atlas-registration strategies. As first objective, we aim to investigate the best MR image to be used and the best point of the AC pipeline to insert the synthetic map in. Sixteen patients underwent a 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) and a PET/MR brain study in the same day. PET/CT images were reconstructed with attenuation maps obtained: (1) from CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with a 2D UNet trained on MR image/attenuation map pairs. As for MR, T1-weighted and Zero Time Echo (ZTE) images were considered; as for attenuation maps, CTs and 511 keV low-resolution attenuation maps were assessed. As second objective, we assessed the ability of DL strategies to provide proper AC maps in presence of cranial anatomy alterations due to surgery. Three 11C-methionine (METH) PET/MR studies were considered. PET images were reconstructed with attenuation maps obtained: (1) from diagnostic coregistered CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with 2D UNets trained on the sixteen FDG anatomically normal patients. Only UNets taking ZTE images in input were considered. FDG and METH PET images were quantitatively evaluated. As for anatomically normal FDG patients, UNet AC models generally provide an uptake estimate with lower bias than atlas-based or segmentation-based methods. The intersubject average bias on images corrected with UNet AC maps is always smaller than 1.5%, except for AC maps generated on too coarse grids. The intersubject bias variability is the lowest (always lower than 2%) for UNet AC maps coming from ZTE images, larger for other methods. UNet models working on MR ZTE images and generating synthetic CT or 511 keV low-resolution attenuation maps therefore provide the best results in terms of both accuracy and variability. As for METH anatomically altered patients, DL properly reconstructs anatomical alterations. Quantitative results on PET images confirm those found on anatomically normal FDG patients.

Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps.

PURPOSE: An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. METHODS: Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. RESULTS: Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. CONCLUSIONS: The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Biomarker-based stability in limbic-predominant amnestic mild cognitive impairment.

BACKGROUND: The amnestic presentation of mild cognitive impairment (aMCI) represents the most common prodromal stage of Alzheimer's disease (AD) dementia. There is, however, some evidence of aMCI with typical amnestic syndrome but showing long-term clinical stability. The ability to predict stability or progression to dementia in the aMCI condition is important, particularly for the selection of candidates in clinical trials. We aimed to establish the role of in vivo biomarkers, as assessed by cerebrospinal fluid (CSF) measures and [18 F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging, in predicting prognosis in a large aMCI cohort. METHODS: We conducted a retrospective study, including 142 aMCI subjects who had a long follow-up (4-19 years), baseline CSF data and [18 F]FDG-PET scans individually assessed by validated voxel-based procedures, classifying subjects into either limbic-predominant or AD-like hypometabolism patterns. RESULTS: The two aMCI cohorts were clinically comparable at baseline. At follow-up, the aMCI group with a limbic-predominant [18 F]FDG-PET pattern showed clinical stability over a very long follow-up (8.20 ± 3.30 years), no decline in Mini-Mental State Examination score, and only 7% conversion to dementia. Conversely, the aMCI group with an AD-like [18 F]FDG-PET pattern had a high rate of dementia progression (86%) over a shorter follow-up (6.47 ± 2.07 years). Individual [18 F]FDG-PET hypometabolism patterns predicted stability or conversion with high accuracy (area under the curve = 0.89), sensitivity (0.90) and specificity (0.89). In the limbic-predominant aMCI cohort, CSF biomarkers showed large variability and no prognostic value. CONCLUSIONS: In a large series of clinically comparable subjects with aMCI at baseline, the specific [18 F]FDG-PET limbic-predominant hypometabolism pattern was associated with clinical stability, making progression to AD very unlikely. The identification of a biomarker-based benign course in aMCI subjects has important implications for prognosis and in planning clinical trials.

White matter deficits correlate with visual motion perception impairments in dyslexic carriers of the DCDC2 genetic risk variant.

Motion perception deficits in dyslexia show a large intersubjective variability, partly reflecting genetic factors influencing brain architecture development. In previous work, we have demonstrated that dyslexic carriers of a mutation of the DCDC2 gene have a very strong impairment in motion perception. In the present study, we investigated structural white matter alterations associated with the poor motion perception in a cohort of twenty dyslexics with a subgroup carrying the DCDC2 gene deletion (DCDC2d+) and a subgroup without the risk variant (DCDC2d-). We observed significant deficits in motion contrast sensitivity and in motion direction discrimination accuracy at high contrast, stronger in the DCDC2d+ group. Both motion perception impairments correlated significantly with the fractional anisotropy in posterior ventral and dorsal tracts, including early visual pathways both along the optic radiation and in proximity of occipital cortex, MT and VWFA. However, the DCDC2d+ group showed stronger correlations between FA and motion perception impairments than the DCDC2d- group in early visual white matter bundles, including the optic radiations, and in ventral pathways located in the left inferior temporal cortex. Our results suggest that the DCDC2d+ group experiences higher vulnerability in visual motion processing even at early stages of visual analysis, which might represent a specific feature associated with the genotype and provide further neurobiological support to the visual-motion deficit account of dyslexia in a specific subpopulation.

Brain metabolic signatures across the Alzheimer's disease spectrum.

PURPOSE: Given the challenges posed by the clinical diagnosis of atypical Alzheimer's disease (AD) variants and the limited imaging evidence available in the prodromal phases of atypical AD, we assessed brain hypometabolism patterns at the single-subject level in the AD variants spectrum. Specifically, we tested the accuracy of [18F]FDG-PET brain hypometabolism, as a biomarker of neurodegeneration, in supporting the differential diagnosis of atypical AD variants in individuals with dementia and mild cognitive impairment (MCI). METHODS: We retrospectively collected N = 67 patients with a diagnosis of typical AD and AD variants according to the IWG-2 criteria (22 typical-AD, 15 frontal variant-AD, 14 logopenic variant-AD and 16 posterior variant-AD). Further, we included N = 11 MCI subjects, who subsequently received a clinical diagnosis of atypical AD dementia at follow-up (21 ± 11 months). We assessed brain hypometabolism patterns at group- and single-subject level, using W-score maps, measuring their accuracy in supporting differential diagnosis. In addition, the regional prevalence of cerebral hypometabolism was computed to identify the most vulnerable core regions. RESULTS: W-score maps pointed at distinct, specific patterns of hypometabolism in typical and atypical AD variants, confirmed by the assessment of core hypometabolism regions, showing that each variant was characterized by specific regional vulnerabilities, namely in occipital, left-sided, or frontal brain regions. ROC curves allowed discrimination among AD variants and also non-AD dementia (i.e., dementia with Lewy bodies and behavioral variant of frontotemporal dementia), with high sensitivity and specificity. Notably, we provide preliminary evidence that, even in AD prodromal phases, these specific [18F]FDG-PET patterns are already detectable and predictive of clinical progression to atypical AD variants at follow-up. CONCLUSIONS: The AD variant-specific patterns of brain hypometabolism, highly consistent at single-subject level and already evident in the prodromal stages, represent relevant markers of disease neurodegeneration, with highly supportive diagnostic and prognostic role.

CSF p-tau/Aß42 ratio and brain FDG-PET may reliably detect MCI "imminent" converters to AD.

PURPOSE: To know whether mild cognitive impairment (MCI) patients will develop Alzheimer's disease (AD) dementia in very short time or remain stable is of crucial importance, also considering new experimental drugs usually tested within very short time frames. Here we combined cerebrospinal fluid (CSF) AD biomarkers and a neurodegeneration marker such as brain FDG-PET to define an objective algorithm, suitable not only to reliably detect MCI converters to AD dementia but also to predict timing of conversion. METHODS: We included 77 consecutive MCI patients with neurological/neuropsychological assessment, brain 18F-FDG-PET and CSF analysis available at diagnosis and a neuropsychological/neurological evaluation every 6 months for a medium- to a long-term follow-up (at least 2 and up to 8 years). Binomial logistic regression models and Kaplan-Meier survival analyses were performed to determine the best biomarker (or combination of biomarkers) in detecting MCI converters to AD dementia and then, among the converters, those who converted in short time frames. RESULTS: Thirty-five out of 77 MCI patients (45%) converted to AD dementia, with an average conversion time since MCI diagnosis of 26.07 months. CSF p-tau/Aß42 was the most accurate predictor of conversion from MCI to AD dementia (82.9% sensitivity; 90% specificity). CSF p-tau/Aß42 and FDG-PET-positive MCIs converted to AD dementia significantly earlier than the CSF-positive-only MCIs (median conversion time, 17.1 vs 31.3 months). CONCLUSIONS: CSF p-tau/Aß42 ratio and brain FDG-PET may predict both occurrence and timing of MCI conversion to full-blown AD dementia. MCI patients with both biomarkers suggestive for AD will likely develop an AD dementia shortly, thus representing the ideal target for any new experimental drug requiring short periods to be tested for.