Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit.

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs' motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5-9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units.

COVID-19 vaccine-related Guillain-Barré syndrome in the Liguria region of Italy: A multicenter case series.

BACKGROUND AND PURPOSE: Guillain-Barré-Syndrome (GBS) can follow COVID-19 vaccination, with clinical and paraclinical features still to be precisely assessed. We describe a cohort of patients who developed GBS after vaccination with different types of COVID-19 vaccines. METHODS: Patients with post-COVID-19 vaccination GBS, admitted to the six hospitals that cover the whole Liguria Region, Northwestern Italy, from February 1st to October 30th 2021, were included. Clinical, demographic, and paraclinical data were retrospectively collected. RESULTS: Among the 13 patients with post-COVID-19 vaccination GBS (9 males; mean age, 64 year), 5 were vaccinated with Oxford-AstraZeneca, 7 with Pfizer-BioNTech, and one with Moderna. Mean time between vaccination and GBS onset was 11.5 days. Ten patients developed GBS after the first vaccination dose, 3 after the second dose. Acute inflammatory demyelinating polyradiculoneuropathy (AIDP) was the predominant GBS variant, mainly characterized by sensory involvement. Bilateral seventh cranial nerve involvement followed AstraZeneca vaccination in two cases. Three patients presented treatment-related fluctuations, and 4 mild symptoms that delayed treatments and negatively affected prognosis. Prognosis was poor (GBS-disability score, ≥3) in 5/13 patients, with a disability rate of 3/13. CONCLUSIONS: Our findings confirm that most post-COVID-19 vaccination GBS belong to the AIDP subtype, and occur after the first vaccine dose. Treatment-related fluctuations, and diagnosis-delaying, mild symptoms at onset are clinical features that affect prognosis and deserve particular consideration.

An eleven-year history of Vanishing White Matter Disease in an adult patient with no cognitive decline and EIF2B5 mutations. A case report.

Vanishing White Matter Disease (VWMD) is a rare autosomal recessive leukoencephalopathy . The classical presentation is characterized by a severe cerebellar ataxia, spasticity, neurological deterioration with a chronic progressive course and episodes of acute neurological deterioration after stress conditions.We report a 52-year-old man with VWMD and atypical features who manifested two major events of transient aphasia eleven years apart with complete recovery in 48 hours. No cognitive decline was present. Brain MRI revealed typical aspects of VWMD including diffuse leukoencephalopathy with relative sparing of U-fibers. We identified the presence of c.592G>A (p.Glu198Lys) and c.1360 C>T (p.Pro454Ser) mutations in EIF2B5.

Probing the Role of a Regional Quantitative Assessment of Amyloid PET.

BACKGROUND: In clinical practice, the amy-PET is globally inspected to provide a binary outcome, but the role of a regional assessment has not been fully investigated yet. OBJECTIVE: To deepen the role of regional amyloid burden and its implication on clinical-neuropsychological features. MATERIALS: Amy-PET and a complete neuropsychological assessment (Trail Making Test, Rey Auditory Verbal Learning Test, semantic verbal fluency, Symbol Digit, Stroop, visuoconstruction) were available in 109 patients with clinical suspicion of Alzheimer's disease. By averaging the standardized uptake value ratio and ELBA, a regional quantification was calculated for each scan. Patients were grouped according to their overall amyloid load: correlation maps, based on regional quantification, were calculated and compared. A regression analysis between neuropsychological assessment and the regional amyloid-ß (Aß) load was carried out. RESULTS: Significant differences were observed between the correlation maps of patients at increasing levels of Aß and the overall dataset. The Aß uptake of the subcortical gray matter resulted not related to other brain regions independently of the global Aß level. A significant association of semantic verbal fluency was observed with ratios of cortical and subcortical distribution of Aß which represent a coarse measure of differences in regional distribution of Aß. CONCLUSION: Our observations confirmed the different susceptibility to Aß accumulation among brain regions. The association between cognition and Aß distribution deserves further investigations: it is possibly due to a direct local effect or it represents a proxy marker of a more aggressive disease subtype. Regional Aß assessment represents an available resource on amy-PET scan with possibly clinical and prognostic implications.

Utility of quantitative EEG in early Lewy body disease.

INTRODUCTION: The reduction of background activity and the increase of low-frequency powers on electroencephalogram (EEG) correlate with cognitive impairment and have been suggested to be underpinned by cholinergic deficit. We aimed to investigate the ratio between α and θ band power (α/θ ratio), as a synoptic index of quantitative EEG (qEEG) slowing-down, in a peculiar group of patients with mild cognitive impairment (MCI) due to an early-stage Lewy body disease (MCI-LBD), as compared to de novo PD patients without cognitive impairment (PD-MOT), to patients with MCI due to Alzheimer's disease (MCI-AD), and to healthy controls (HC). METHODS: Twelve patients with MCI-LBD (8 males; mean age 74.8 ± 3.6), 11 PD-MOT, 11 MCI-AD and 24 HC subjects undergoing qEEG were matched for gender, age, and education. Following logarithmic transformation, the α/θ ratio was compared among groups and brain regions by repeated measures ANOVA, also exploring group*regions interactions. RESULTS: A significant effect of group (p = 0.0003), regions (p = 0.0001), and group*regions interaction (p = 0.0001) on the α/θ ratio was observed. At post-hoc analysis, α/θ ratio was significantly lower in MCI-LBD (p = 0.001) and in PD-MOT (p = 0.02) compared to HC, and in MCI-LBD than MCI-AD (p = 0.05). No significant differences were found between MCI-AD and HC, as well as between MCI-LBD and PD-MOT. CONCLUSION: The α/θ power ratio as a synoptic index of EEG background slowing-down could be a simple and easy-to-use qEEG index which might indirectly mirror a cholinergic failure, useful to pick-up those MCI patients at higher risk of developing a Lewy-body disease.

Epilepsy in Neurodegenerative Dementias: A Clinical, Epidemiological, and EEG Study.

BACKGROUND: Seizures are common in patients with dementia but precise epidemiologic data of epilepsy in neurodegenerative dementia is lacking. OBJECTIVE: The first aim of the study was to investigate prevalence and clinical characteristics of epilepsy in a large cohort of patients with neurodegenerative dementias. Subsequently, we explored clinical, neuropsychological, and quantitative electroencephalogram (qEEG) data of Alzheimer's disease (AD) patients with epilepsy (AD-EPI) as compared to AD patients without epilepsy (AD-CTR). METHODS: We retrospectively evaluated consecutive patients with a diagnosis of a neurodegenerative dementia and a clinically diagnosed epilepsy that required antiepileptic drugs (AED). All patients underwent baseline comprehensive neuropsychological assessment. A follow-up of at least one year was requested to confirm the dementia diagnosis. In AD patients, qEEG power band analysis was performed. AD-CTR and AD-EPI patients were matched for age, Mini-Mental State Examination score, and gender. RESULTS: Thirty-eight out of 2,054 neurodegenerative dementia patients had epilepsy requiring AED. The prevalence of epilepsy was 1.82% for AD, 1.28% for the behavioral variant of frontotemporal dementia (bvFTD), 2.47% for dementia with Lewy bodies (DLB), and 12% for primary progressive aphasia. Epilepsy were more drug-responsive in AD than in non-AD dementias. Finally, no significant differences were found in neuropsychological and qEEG data between AD-EPI and AD-CTR patients. CONCLUSION: In our cohort, AD, FTD, and DLB dementias have similar prevalence of epilepsy, even if AD patients were more responsive to AED. Moreover, AD-EPI patients did not have significant clinical, neuropsychological qEEG differences compared with AD-CTR patients.

Head-to-Head Comparison among Semi-Quantification Tools of Brain FDG-PET to Aid the Diagnosis of Prodromal Alzheimer's Disease.

BACKGROUND: Several automatic tools have been implemented for semi-quantitative assessment of brain [18]F-FDG-PET. OBJECTIVE: We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls. METHODS: Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [18]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM). RESULTS: The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods. CONCLUSION: The study confirms the good accuracy of [18]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.

Neuroimaging findings and clinical trajectories of Lewy body disease in patients with MCI.

Elderly patients with mild cognitive impairment (MCI) may develop a Lewy body disease; their neuroimaging features at presentation are largely unknown. We present an intriguing group of 13 patients with MCI preceding (2.9 ± 1.9 years) parkinsonism (MCI-P), and eventually dementia 4.6 ± 1.6 years later (6 patients), whereas 7 patients remained dementia free after 4.7 ± 2.7 years. Neuropsychological tests, dopamine transporter (DAT) single photon emission computed tomography, and 18F-fluorodeoxyglucose positron emission tomography were compared with healthy controls and with cognitively normal patients with Parkinson's disease (PD-MOT). Compared to controls, MCI-P but not PD-MOT showed significant posterior temporo-parieto-occipital hypometabolism. Basal ganglia DAT uptake was similar between MCI-P and PD-MOT. Patients who converted to dementia were older, tended to have higher movement disorder society-unified Parkinson's disease rating scale scores and developed at least another clinical core feature fulfilling the criteria for probable dementia with Lewy bodies (DLB). Concurrent impairment of Corsi span and semantic verbal fluency, or of temporal lobe hypometabolism at baseline and reduced putamen-to-caudate ratio on DAT-SPECT at parkinsonism onset, both predicted (p < 0.001) the evolution to dementia. The constructs of Park cognitive subtype and prodromal Lewy body dementia partially overlap; functional imaging and neuropsychology may help in characterizing the patients and in tracking the risk toward dementia.

Accuracy and generalization capability of an automatic method for the detection of typical brain hypometabolism in prodromal Alzheimer disease.

PURPOSE: The aim of this study was to verify the reliability and generalizability of an automatic tool for the detection of Alzheimer-related hypometabolic pattern based on a Support-Vector-Machine (SVM) model analyzing 18F-fluorodeoxyglucose (FDG) PET data. METHODS: The SVM model processed metabolic data from anatomical volumes of interest also considering interhemispheric asymmetries. It was trained on a homogeneous dataset from a memory clinic center and tested on an independent multicentric dataset drawn from the Alzheimer's Disease Neuroimaging Initiative. Subjects were included in the study and classified based on a diagnosis confirmed after an adequate follow-up time. RESULTS: The accuracy of the discrimination between patients with Alzheimer Disease (AD), in either prodromal or dementia stage, and normal aging subjects was 95.8%, after cross-validation, in the training set. The accuracy of the same model in the testing set was 86.5%. The role of the two datasets was then reversed, and the accuracy was 89.8% in the multicentric training set and 88.0% in the monocentric testing set. The classification rate was also evaluated in different subgroups, including non-converter mild cognitive impairment (MCI) patients, subjects with MCI reverted to normal conditions and subjects with non-confirmed memory concern. The percent of pattern detections increased from 77% in early prodromal AD to 91% in AD dementia, while it was about 10% for healthy controls and non-AD patients. CONCLUSIONS: The present findings show a good level of reproducibility and generalizability of a model for detecting the hypometabolic pattern in AD and confirm the accuracy of FDG-PET in Alzheimer disease.

Metabolic correlates of reserve and resilience in MCI due to Alzheimer's Disease (AD).

BACKGROUND: We explored the presence of both reserve and resilience in late-converter mild cognitive impairment due to Alzheimer's disease (MCI-AD) and in patients with slowly progressing amyloid-positive MCI by assessing the topography and extent of neurodegeneration with respect to both "aggressive" and typically progressing phenotypes and in the whole group of patients with MCI, grounding the stratification on education level. METHODS: We analyzed 94 patients with MCI-AD followed until conversion to dementia and 39 patients with MCI who had brain amyloidosis (AMY+ MCI), all with available baseline 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) results. Using a data-driven approach based on conversion time, patients with MCI-AD were divided into typical AD and late-converter subgroups. Similarly, on the basis of annual rate of Mini Mental State Examination score reduction, AMY+ MCI group was divided, obtaining smoldering (first tertile) and aggressive (third tertile) subgroups. Finally, we divided the whole group (MCI-AD and AMY+ MCI) according to years of schooling, obtaining four subgroups: poorly educated (Low-EDUC; first quartile), patients with average education (Average-EDUC; second quartile), highly educated (High-EDUC; third quartile), and exceptionally educated (Except-EDUC; fourth quartile). FDG-PET of typical AD, late converters, and aggressive and smoldering AMY+ MCI subgroups, as well as education level-based subgroups, were compared with healthy volunteer control subjects (CTR) and within each group using a two-samples t test design (SPM8; p < 0.05 family-wise error-corrected). RESULTS: Late converters were characterized by relatively preserved metabolism in the right middle temporal gyrus (Brodmann area [BA] 21) and in the left orbitofrontal cortex (BA 47) with respect to typical AD. When compared with CTR, the High-EDUC subgroup demonstrated a more extended bilateral hypometabolism in the posterior parietal cortex, posterior cingulate cortex, and precuneus than the Low- and Average-EDUC subgroups expressing the same level of cognitive impairment. The Except-EDUC subgroup showed a cluster of significant hypometabolism including only the left posterior parietal cortex (larger than the Low- and Average-EDUC subgroups but not further extended with respect to the High-EDUC subgroup). CONCLUSIONS: Middle and inferior temporal gyri may represent sites of resilience rather than a hallmark of a more aggressive pattern (when hypometabolic). These findings thus support the existence of a relatively homogeneous AD progression pattern of hypometabolism despite AD heterogeneity and interference of cognitive reserve. In fact, cortical regions whose "metabolic resistance" was associated with slower clinical progression had different localization with respect to the regions affected by education-related reserve.

Spinocerebellar ataxia 17: full phenotype in a 41 CAG/CAA repeats carrier.

BACKGROUND: Spinocerebellar ataxia 17 (SCA17) is one of the most heterogeneous forms of autosomal dominant cerebellar ataxias with a large clinical spectrum which can mimic other movement disorders such as Huntington disease (HD), dystonia and parkinsonism. SCA17 is caused by an expansion of CAG/CAA repeat in the Tata binding protein (TBP) gene. Normal alleles contain 25 to 40 CAG/CAA repeats, alleles with 50 or greater CAG/CAA repeats are pathological with full penetrance. Alleles with 43 to 49 CAG/CAA repeats were also reported and their penetrance is estimated between 50 and 80%. Recently few symptomatic individuals having 41 and 42 repeats were reported but it is still unclear whether CAG/CAA repeats of 41 or 42 are low penetrance disease-causing alleles. Thus, phenotypic variability like the disease course in subject with SCA17 locus restricted expansions remains to be fully understood. CASE PRESENTATION: The patients was a 63-year-old woman who, at 54 years, showed personality changes and increased frequency of falls. At 55 years of age neuropsychological tests showed executive attention and visuospatial deficit. At the age of 59 the patient developed dysarthria and a progressive cognitive deficit. The neurological examination showed moderate gait ataxia, dysdiadochokinesia and dysmetria, dysphagia, dysarthria and abnormal saccadic pursuit, severe axial asynergy during postural changes, choreiform dyskinesias. Molecular analysis of the TBP gene demonstrated an allele with 41 repeat suggesting that 41 CAG/CCG TBP repeats could be an allele associated with the full clinical spectrum of SCA17. CONCLUSIONS: The described case with the other similar cases described in the literature suggests that 41 CAG/CAA trinucleotides should be considered as critical threshold in SCA17. We suggest that SCA17 diagnosis should be suspected in patients presenting with movement disorders associated with other neurodegenerative signs and symptoms.

Clinical utility and research frontiers of neuroimaging in movement disorders.

Neuroimaging in Parkinson's disease (PD) and other primary Parkinsonian disorders has been increasingly used in the routine clinical work in the last years. The paradigm has changed from an "exclusionary" use, i.e., to rule out causes of secondary Parkinsonism, to an "inclusionary" one, i.e., finding image and network characteristics allowing to identify a specific disease. This is allowed by analyses spanning from the commonly used visual analysis to the most sophisticated postprocessing leading to the identification of covariance patterns both in morphological and functional neuroimaging. However, paralleling the advancement in covariance and connectivity analyses, the issues of standardization and harmonization of data acquisition, and image reconstruction and postprocessing among centers are emerging in the scientific community. Also, the building of scientific evidence still suffers from the lack of large, formal studies and relies on relatively small cohort studies from one or few centers. Joint actions to face these issues are now ongoing in Europe, supported by specific programs, such as the Joint Programming on Neurodegenerative Diseases (JPND). In the present review, some of the most recent and relevant achievements in the field of diffusion tensor magnetic resonance imaging (MRI), functional MRI, fludeoxyglucose-positron-emission tomography, dopamine transporter single-photon emission computed tomography and non-dopaminergic imaging in PD and primary Parkinsonisms are reported.