Metabolic and dopaminergic correlates of intellectual enrichment in de-novo Parkinson's disease patients.

BACKGROUND: Cognitive reserve (CR) is an expression of brain resilience in response to damage. Education, occupational experience and leisure activities are thought to increase CR and have beneficial effects on global cognition and cognitive decline in Parkinson's disease (PD). We aimed to disclose brain metabolic and dopaminergic correlates of CR in de-novo PD patients. METHODS: Sixty-two drug-naïve de-novo PD patients underwent [18F]FDG-PET and DAT-SPECT. CR was quantified through the Cognitive-Reserve-Index questionnaire including total-CR and 3 subscores (educational-CR, occupational-CR, leisure-CR). Specific binding ratios (SBRs) and Z-scores in basal ganglia were obtained with 'BasGan-V2'. Z-scores were used as dependent variables in general linear models to assess the interaction between dopaminergic function and CR. Voxel-based correlation between brain metabolism and CR-scores and between SBR and [18F]FDG-PET was evaluated using SPM12 (P<0.05 FWE-corrected at peak and cluster level considered significant). RESULTS: Dopaminergic deficit in the most affected hemisphere (MAH) putamen was significantly less marked in higher CR patients (Z-score -1.7±0.1 highly-educated versus -2.1±0.1 poorly-educated, P<0.02). Total and leisure-related-CR resulted correlated directly with z-scores of the MAH putamen (P<0.018 and P<0.003) and inversely with brain metabolism in both cerebellar hemispheres (P<0.001). MAH-putamen SBR correlated directly with metabolism in occipital and parietal cortex (P<0.003) and inversely in cerebellar hemispheres (P<0.02). CONCLUSIONS: CR proxies demonstrated to correlate directly with dopaminergic function and inversely with metabolism in cerebellar hemispheres in de-novo PD patients. The present multi-modal approach including both metabolic and dopaminergic correlates of CR allowed to identify possible compensation mechanisms, highlighting a potential role of the cerebellum that deserves further investigation.

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.

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.

Polysomnographic correlates of sleep disturbances in de novo, drug naïve Parkinson's Disease.

BACKGROUND: Sleep disturbances are common non-motor symptoms of Parkinson's Disease (PD). METHODS: The aim of this study was to investigate the polysomnographic correlates of sleep changes, as investigated by the Parkinson's Disease Sleep Scale-2 (PDSS-2), in a cohort of sixty-two consecutive de novo, drug naïve PD patients (71.40 ± 7.84 y/o). RESULTS: PDSS-2 total score showed a direct correlation with stage shifts (p = 0.008). Fragmented sleep showed an inverse correlation with sleep efficiency (p = 0.012). Insomnia symptoms showed an inverse correlation with wake after sleep onset (p = 0.005) and direct correlation with periodic leg movements (p = 0.006) and stage shift indices (p = 0.003). Motor Symptoms showed a direct correlation with Apnoea-Hypopnoea (AHI; p = 0.02) and awakenings indices (p = 0.003). Dream distressing showed a direct correlation with REM without atonia (RWA, p = 0.042) and an inverse correlation with AHI (p = 0.012). Sleep quality showed an inverse correlation with RWA (p = 0.008). CONCLUSION: PDSS-2 features are significantly correlated with polysomnography objective findings, thus further supporting its reliability to investigate sleep disturbances in PD patients.

Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe.

INTRODUCTION: Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS: To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS: With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION: This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond.

Cuneus/precuneus as a central hub for brain functional connectivity of mild cognitive impairment in idiopathic REM sleep behavior patients.

PURPOSE: To investigate brain functional correlates of mild cognitive impairment (MCI) in idiopathic REM sleep behavior disorder (iRBD). METHODS: Thirty-nine consecutive iRBD patients, 17 with (RBD-MCI, 73.6±6.5 years), and 22 without (RBD-NC, 69.6±6.1 years) MCI underwent neuropsychological assessment, 18F-FDG-PET, and 123I-FP-CIT-SPECT as a marker of nigro-striatal dopaminergic function. Forty-two healthy subjects (69.6±8.5 years) were used as control for 18F-FDG-PET analysis. Brain metabolism was compared between the three groups by univariate analysis of variance. Post hoc comparison between RBD-MCI and RBD-NC was performed to investigate the presence of an MCI-related volume of interest (MCI-VOI). Brain functional connectivity was explored by interregional correlation analysis (IRCA), using the whole-brain normalized MCI-VOI uptake as the independent variable. Moreover, the MCI-VOI uptake was correlated with 123I-FP-CIT-SPECT specific-to-non displaceable binding ratios (SBR) and neuropsychological variables. Finally, the MCI-VOI white matter structural connectivity was analyzed by using a MRI-derived human atlas. RESULTS: The MCI-VOI was characterized by a relative hypometabolism involving precuneus and cuneus (height threshold p<0.0001). IRCA (height threshold p<0.0001) revealed a brain functional network involving regions in frontal, temporal, parietal, and occipital lobes, thalamus, caudate, and red nuclei in iRBD patients. In controls, the network was smaller and involved temporal, occipital, cingulate cortex, and cerebellum. Moreover, MCI-VOI metabolism was correlated with verbal memory (p=0.01), executive functions (p=0.0001), and nigro-putaminal SBR (p=0.005). Finally, MCI-VOI was involved in a white matter network including cingulate fasciculus and corpus callosum. CONCLUSION: Our data suggest that cuneus/precuneus is a hub of a large functional network subserving cognitive function in iRBD.

Dopaminergic and Serotonergic Degeneration and Cortical [18 F]Fluorodeoxyglucose Positron Emission Tomography in De Novo Parkinson's Disease.

BACKGROUND: Degeneration of the nigrostriatal dopaminergic (DA) and the raphe-thalamic serotonergic (SE) systems is among the earliest changes observed in Parkinson's disease (PD). The consequences of those changes on brain metabolism, especially regarding their impact on the cortex, are poorly understood. OBJECTIVES: Using multi-tracer molecular imaging, we assessed in a cohort of drug-naive PD patients the association between cortical metabolism and DA and SE system deafferentation of either striatum or thalamus, and we explored whether this association was mediated by either striatum or thalamus metabolism. METHODS: We recruited 96 drug-naive PD patients (aged 71.9 ± 7.5 years) who underwent [123 I]ioflupane single-photon emission computed tomography ([123 I]FP-CIT-SPECT) and brain [18 F]fluorodeoxyglucose positron emission tomography ([18 F]FDG-PET). We used a voxel-wise analysis of [18 F]FDG-PET images to correlate regional metabolism with striatal DA and thalamic SE innervation as assessed using [123 I]FP-CIT-SPECT. RESULTS: We found that [123 I]FP-CIT specific to nondisplaceable binding ratio (SBR) and glucose metabolism positively correlated with one another in the deep gray matter (thalamus: P = 0.001, r = 0.541; caudate P = 0.001, r = 0.331; putamen P = 0.001, r = 0.423). We then observed a direct correlation between temporoparietal metabolism and caudate DA innervation, as well as a direct correlation between prefrontal metabolism and thalamus SE innervation. The effect of caudate [123 I]FP-CIT SBR values on temporoparietal metabolism was mediated by caudate metabolic values (percentage mediated: 89%, P-value = 0.008), and the effect of thalamus [123 I]FP-CIT SBR values on prefrontal metabolism was fully mediated by thalamus metabolic values (P < 0.001). CONCLUSIONS: These data suggest that the impact of deep gray matter monoaminergic deafferentation on cortical function is mediated by striatal and thalamic metabolism in drug-naive PD. © 2021 International Parkinson and Movement Disorder Society.

Rapid eye movement sleep behavior disorder: A proof-of-concept neuroprotection study for prodromal synucleinopathies.

BACKGROUND AND PURPOSE: To explore the feasibility of a neuroprotection trial in prodromal synucleinopathy, using idiopathic rapid eye movement sleep behavior disorder (iRBD) as the target population and 123 I-FP-CIT-SPECT as a biomarker of disease progression. METHODS: Consecutive iRBD patients were randomly assigned to a treatment arm receiving selegiline and symptomatic rapid eye movement sleep behavior disorder treatment, or to a control arm receiving symptomatic treatment only. Selegiline was chosen because of a demonstrated neuroprotection effect in animal models. Patients underwent 123 I-FP-CIT-SPECT at baseline and after 30 months on average. The clinical outcome was the emergence of parkinsonism and/or dementia. A repeated-measures general linear model (GLM) was applied using group (control and treatment) as "between" factor, and both time (baseline and follow-up) and regions (123 I-FP-CIT-SPECT putamen and caudate uptake) as the "within" factors, adjusting for age. RESULTS: Thirty iRBD patients completed the study (68.2 ± 6.9 years; 29 males; 21% dropout rate), 13 in the treatment arm, and 17 in the control arm. At follow-up (29.8 ± 9.0 months), three patients in the control arm developed dementia and one parkinsonism, whereas two patients in the treatment arm developed parkinsonism. Both putamen and caudate uptake decreased over time in the control arm. In the treatment arm, only the putamen uptake decreased over time, whereas caudate uptake remained stable. GLM analysis demonstrated an effect of treatment on the 123 I-FP-CIT-SPECT uptake change, with a significant interaction between the effect of group, time, and regions (p = 0.004). CONCLUSIONS: A 30-months neuroprotection study for prodromal synucleinopathy is feasible, using iRBD as the target population and 123 I-FP-CIT-SPECT as a biomarker of disease progression.

18F-FDG PET diagnostic and prognostic patterns do not overlap in Alzheimer's disease (AD) patients at the mild cognitive impairment (MCI) stage.

PURPOSE: We aimed to identify the cortical regions where hypometabolism can predict the speed of conversion to dementia in mild cognitive impairment due to Alzheimer's disease (MCI-AD). METHODS: We selected from the clinical database of our tertiary center memory clinic, eighty-two consecutive MCI-AD that underwent 18F-fluorodeoxyglucose (FDG) PET at baseline during the first diagnostic work-up and were followed up at least until their clinical conversion to AD dementia. The whole group of MCI-AD was compared in SPM8 with a group of age-matched healthy controls (CTR) to verify the presence of AD diagnostic-pattern; then the correlation between conversion time and brain metabolism was assessed to identify the prognostic-pattern. Significance threshold was set at p < 0.05 False-Discovery-Rate (FDR) corrected at peak and at cluster level. Each MCI-AD was then compared with CTR by means of a SPM single-subject analysis and grouped according to presence of AD diagnostic-pattern and prognostic-pattern. Kaplan-Meier-analysis was used to evaluate if diagnostic- and/or prognostic-patterns can predict speed of conversion to dementia. RESULTS: Diagnostic-pattern corresponded to typical posterior hypometabolism (BA 7, 18, 19, 30, 31 and 40) and did not correlate with time to conversion, which was instead correlated with metabolic levels in right middle and inferior temporal gyri as well as in the fusiform gyrus (prognostic-pattern, BA 20, 21 and 38). At Kaplan-Meier analysis, patients with hypometabolism in the prognostic pattern converted to AD-dementia significantly earlier than patients not showing significant hypometabolism in the right middle and inferior temporal cortex (9 versus 19 months; Log rank p < 0.02, Breslow test: p < 0.003, Tarone-Ware test: p < 0.007). CONCLUSION: The present findings support the role of FDG PET as a robust progression biomarker even in a naturalist population of MCI-AD. However, not the AD-typical diagnostic-pattern in posterior regions but the middle and inferior temporal metabolism captures speed of conversion to dementia in MCI-AD since baseline. The highlighted prognostic pattern is a further, independent source of heterogeneity in MCI-AD and affects a primary-endpoint on interventional clinical trials (time of conversion to dementia).

Early identification of MCI converting to AD: a FDG PET study.

PURPOSE: Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not. METHODS: FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy. RESULTS: The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients. CONCLUSION: In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Prediction of cognitive worsening in de novo Parkinson's disease: Clinical use of biomarkers.

BACKGROUND: Cognitive impairment is a frequent and disabling feature of Parkinson's disease. Identifying the factors able to predict cognitive worsening since the early stage may improve disease management. The objective of this study was to define the best predictors of future cognitive worsening in a group of patients with newly diagnosed PD and to propose cutoff values potentially useful at the individual level. METHODS: Fifty-four consecutive drug-naive patients with de novo PD were prospectively evaluated by clinical and neuropsychological assessment, resting EEG, and 123 I-FP-CIT-SPECT and clinically classified into mainly motor, diffuse/malignant, and intermediate PD subtypes; they were then followed up for an average of 5 years. Cognitive outcome was defined by identifying cognitively stable or worsened patients. RESULTS: Step-wise logistic regression selected the posterior qEEG mean frequency and 123 I-FP-CIT-SPECT uptake at caudate level (P < 0.0001). The posterior qEEG mean frequency (cut point, 8.3 Hz) and the caudate 123 I-FP-CIT-SPECT uptake (cut point, 2.3, specific to nondisplaceable binding ratio) achieved 82% and 80% of accuracy, respectively, in predicting cognitive outcome. Survival analysis showed decreasing expected time to cognitive worsening associated with scores below the established thresholds for qEEG and 123 I-FP-CIT-SPECT and with the presence of a malignant clinical phenotype. CONCLUSIONS: Resting EEG and 123 I-FP-CIT-SPECT are good predictors of future cognitive worsening, in de novo drug-naive PD patients. Wherever available, these biomarkers could add valuable prognostic information to classification into different clinical phenotypes. © 2017 International Parkinson and Movement Disorder Society.

Mapping brain morphological and functional conversion patterns in predementia late-onset bvFTD.

PURPOSE: The diagnosis of behavioural variant frontotemporal dementia (bvFTD) is challenging during the predementia stage when symptoms are subtle and confounding. Morphological and functional neuroimaging can be particularly helpful during this stage but few data are available. METHODS: We retrospectively selected 25 patients with late-onset probable bvFTD. Brain structural MRI and FDG PET were performed during the predementia stage (mean MMSE score 27.1 ± 2.5) on average 2 years before. The findings with the two imaging modalities were compared (SPM8) with those in a group of 20 healthy subjects. The bvFTD patients were divided into two subgroups: those with predominant disinhibition (bvFTD+) and those with apathy (bvFTD-). RESULTS: Hypometabolism exceeded grey matter (GM) density reduction in terms of both extension and statistical significance in all comparisons. In the whole bvFTD group, hypometabolism involved the bilateral medial, inferior and superior lateral frontal cortex, anterior cingulate, left temporal and right parietal cortices and the caudate nuclei. GM density reduction was limited to the right frontal cortex and the left medial temporal lobe. In bvFTD+ patients hypometabolism was found in the bilateral medial and basal frontal cortex, while GM reduction involved the left anterior cingulate and left inferior frontal cortices, and the right insula. In bvFTD- patients, atrophy and mainly hypometabolism involved the lateral frontal cortex and the inferior parietal lobule. CONCLUSION: These findings suggest that hypometabolism is more extensive than, and thus probably precedes, atrophy in predementia late-onset bvFTD, underscoring different topographic involvement in disinhibited and apathetic presentations. If confirmed in a larger series, these results should prompt biomarker operationalization in bvFTD, especially for patient selection in therapeutic clinical trials.

Brain (18)F-DOPA PET and cognition in de novo Parkinson's disease.

PURPOSE: The role of mesocortical dopaminergic pathways in the cognitive function of patients with early Parkinson's disease (PD) needs to be further clarified. METHODS: The study groups comprised 15 drug-naive patients with de novo PD and 10 patients with essential tremor (controls) who underwent (18)F-DOPA PET (static acquisition, normalization on mean cerebellar counts) and an extended neuropsychological test battery. Factor analysis with varimax rotation was applied to the neuropsychological test scores, to yield five factors from 16 original scores, which explained 82 % of the total variance. Correlations between cognitive factors and (18)F-DOPA uptake were assessed with SPM8, taking age and gender as nuisance variables. RESULTS: (18)F-DOPA uptake was significantly lower in PD patients than in controls in the bilateral striatum, mainly in the more affected (right) hemisphere, and in a small right temporal region. Significant positive correlations were found only in PD patients between the executive factor and (18)F-DOPA uptake in the bilateral anterior cingulate cortex (ACC) and the middle frontal gyrus, between the verbal fluency factor and (18)F-DOPA uptake in left BA 46 and the bilateral striatum, and between the visuospatial factor and (18)F-DOPA uptake in the left ACC and bilateral striatum. No correlations were found between (18)F-DOPA uptake and either the verbal memory factor or the abstraction-working memory factor. CONCLUSION: These data clarify the role of the mesocortical dopaminergic pathways in cognitive function in early PD, highlighting the medial frontal lobe, anterior cingulate, and left BA 46 as the main sites of cortical correlation with executive and language functions.

Cognitive impairment assessment through handwriting (COGITAT) score: a novel tool that predicts cognitive state from handwriting for forensic and clinical applications.

Introduction: Handwriting deteriorates proportionally to the writer's cognitive state. Such knowledge is of special importance in the case of a contested will, where dementia of the testator is claimed, but medical records are often insufficient to decide what the testator's cognitive state really was. By contrast, if the will is handwritten, handwriting analysis allows us to gauge the testator's cognitive state at the precise moment when he/she was writing the will. However, quantitative methods are needed to precisely evaluate whether the writer's cognitive state was normal or not. We aim to provide a test that quantifies handwriting deterioration to gauge a writer's cognitive state. Methods: We consecutively enrolled patients who came for the evaluation of cognitive impairment at the Outpatient Clinic for Cognitive Impairment of the Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Sciences (DINOGMI) of the University of Genoa, Italy. Additionally, we enrolled their caregivers. We asked them to write a short text by hand, and we administered the Mini Mental State Examination (MMSE). Then, we investigated which handwriting parameters correlated with cognitive state as gauged by the MMSE. Results: Our study found that a single score, which we called the COGnitive Impairment Through hAndwriTing (COGITAT) score, reliably allows us to predict the writer's cognitive state. Conclusion: The COGITAT score may be a valuable tool to gage the cognitive state of the author of a manuscript. This score may be especially useful in contested handwritten wills, where clinical examination of the writer is precluded.

Tracking the progression of Alzheimer's disease: Insights from metabolic patterns of SOMI stages.

BACKGROUND: SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients. METHODS: One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated. RESULTS: Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05). DISCUSSION: SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline. CONCLUSION: Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration.

Limbic Network Derangement Mediates Unawareness of Apathy in Mild Cognitive Impairment due to Alzheimer's Disease: Clues from [18F]FDG PET Voxel-Wise Analysis.

Background: Discrepancy between caregiver and patient assessments of apathy in mild cognitive impairment (MCI) is considered an index of apathy unawareness, independently predicting progression to AD dementia. However, its neural underpinning are uninvestigated. Objective: To explore the [18F]FDG PET-based metabolic correlates of apathy unawareness measured through the discrepancy between caregiver and patient self-report, in patients diagnosed with MCI. Methods: We retrospectively studied 28 patients with an intermediate or high likelihood of MCI-AD, progressed to dementia over an average of two years, whose degree of apathy was evaluated by means of the Apathy Evaluation Scale (AES) for both patients (PT-AES) and caregivers (CG-AES). Voxel-based analysis at baseline was used to obtain distinct volumes of interest (VOIs) correlated with PT-AES, CG-AES, or their absolute difference (DISCR-AES). The resulting DISCR-AES VOI count densities were used as covariates in an inter-regional correlation analysis (IRCA) in MCI-AD patients and a group of matched healthy controls (HC). Results: DISCR-AES negatively correlated with metabolism in bilateral parahippocampal gyrus, posterior cingulate cortex, and thalamus, PT-AES score with frontal and anterior cingulate areas, while there was no significant correlation between CG-AES and brain metabolism. IRCA revealed that MCI-AD patients exhibited reduced metabolic/functional correlations of the DISCR-AES VOI with the right cingulate gyrus and its anterior projections compared to HC. Conclusions: Apathy unawareness entails early disruption of the limbic circuitry rather than the classical frontal-subcortical pathways typically associated with apathy. This reaffirms apathy unawareness as an early and independent measure in MCI-AD, marked by distinct pathophysiological alterations.

Cerebrospinal fluid NPTX2 changes and relationship with regional brain metabolism metrics across mild cognitive impairment due to Alzheimer's disease.

BACKGROUND: Neuronal pentraxin-2 (NPTX2), crucial for synaptic functioning, declines in cerebrospinal fluid (CSF) as cognition deteriorates. The variations of CSF NPTX2 across mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and its association with brain metabolism remain elusive, albeit relevant for patient stratification and pathophysiological insights. METHODS: We retrospectively analyzed 49 MCI-AD patients grouped by time until dementia (EMCI, n = 34 progressing within 2 years; LMCI, n = 15 progressing later/stable at follow-up). We analyzed demographic variables, cognitive status (MMSE score), and CSF NPTX2 levels using a commercial ELISA assay in EMCI, LMCI, and a control group of age-/sex-matched individuals with other non-dementing disorders (OND). Using [18F]FDG PET scans for voxel-based analysis, we explored correlations between regional brain metabolism metrics and CSF NPTX2 levels in MCI-AD patients, accounting for age. RESULTS: Baseline and follow-up MMSE scores were lower in LMCI than EMCI (p value = 0.006 and p < 0.001). EMCI exhibited significantly higher CSF NPTX2 values than both LMCI (p = 0.028) and OND (p = 0.006). We found a significant positive correlation between NPTX2 values and metabolism of bilateral precuneus in MCI-AD patients (p < 0.005 at voxel level, p < 0.05 with family-wise error correction at the cluster level). CONCLUSIONS: Higher CSF NPTX2 in EMCI compared to controls and LMCI suggests compensatory synaptic responses to initial AD pathology. Disease progression sees these mechanisms overwhelmed, lowering CSF NPTX2 approaching dementia. Positive CSF NPTX2 correlation with precuneus glucose metabolism links to AD-related metabolic changes across MCI course. These findings posit CSF NPTX2 as a promising biomarker for both AD staging and progression risk stratification.

Medical Information Extraction With NLP-Powered QABots: A Real-World Scenario.

The advent of computerized medical recording systems in healthcare facilities has made data retrieval tasks easier, compared to manual recording. Nevertheless, the potential of the information contained within medical records remains largely untapped, mostly due to the time and effort required to extract data from unstructured documents. Natural Language Processing (NLP) represents a promising solution to this challenge, as it enables the use of automated text-mining tools for clinical practitioners. In this work, we present the architecture of the Virtual Dementia Institute (IVD), a consortium of sixteen Italian hospitals, using the NLP Extraction and Management Tool (NEMT), a (semi-) automated end-to-end pipeline that extracts relevant information from clinical documents and stores it in a centralized REDCap database. After defining a common Case Report Form (CRF) across the IVD hospitals, we implemented NEMT, the core of which is a Question Answering Bot (QABot) based on a modern NLP model. This QABot is fine-tuned on thousands of examples from IVD centers. Detailed descriptions of the process to define a common minimum dataset, Inter-Annotator Agreement calculated on clinical documents, and NEMT results are provided. The best QABot performance show an Exact Match score (EM) of 78.1%, a F1-score of 84.7%, a Lenient Accuracy (LAcc) of 0.834, and a Mean Reciprocal Rank (MRR) of 0.810. EM and F1 scores outperform the same metrics obtained with ChatGPTv3.5 (68.9% and 52.5%, respectively). With NEMT the IVD has been able to populate a database that will contain data from thousands of Italian patients, all screened with the same procedure. NEMT represents an efficient tool that paves the way for medical information extraction and exploitation for new research studies.