Psychological Impact of Predictive Genetic Testing for Inherited Alzheimer Disease and Frontotemporal Dementia: The IT-DIAfN Protocol.

AIM: Our aim was to evaluate the psychological impact of predictive genetic testing in individuals at-risk for inherited dementia who underwent a structured counseling and testing protocol. METHODS: Participants were healthy at-risk relatives from families with at least one affected patient, in whom a disease-associated genetic variant had been ascertained. A comprehensive psychological assessment (personality, anxiety and depression, quality of life, coping strategies, resilience and health-related beliefs) was administered at baseline, at 6 months and 12 months follow-up. RESULTS: Twenty-four participants from 13 families were included. Sixteen participants underwent blood sampling and genetic analysis; 6 resulted to be carriers of pathogenic variants (1 in PSEN1, 1 in PSEN2, 4 in GRN). Carriers showed higher score on the Resilience Scale for Adults (RSA) - social competence, and on Multidimensional Health Locus of Control - internal, than noncarriers (P=0.03 for both). Ten at-risk relatives who completed the follow-up showed improvement in RSA - planned future (P=0.01) with respect to baseline. DISCUSSION: Our case series showed that at-risk individuals undergoing predictive testing showed benefit on personal life and no detrimental impact on a broad range of psychological outcomes. Higher social skills and lower internal health locus of control in carriers may be an early psychological correlate of preclinical dementia.

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.

Neuro-telehealth for fragile patients in a tertiary referral neurological institute during the COVID-19 pandemic in Milan, Lombardy.

BACKGROUND: Lombardy was severely hit by the COVID-19 pandemic since February 2020 and the Health System underwent rapid reorganization. Outpatient clinics were stopped for non-urgent patients: it became a priority to manage hundreds of fragile neurological patients who suddenly had less reference points. In Italy, before the pandemic, Televisits were neither recognized nor priced. METHODS: At the Fondazione IRCCS Istituto Neurologico C. Besta, we reorganized outpatient clinics to deliver Neuro-telemedicine services, including Televisits and Teleneurorehabilitation, since March 2020. A dedicated Working Group prepared the procedure, tested the system, and designed satisfaction questionnaires for adults and children. RESULTS: After a pilot phase, we prepared a procedure for Telemedicine outpatient clinics which was approved by hospital directions. It included prescription, booking, consenting, privacy and data protection, secure connection with patients (Teams Microsoft 365), electronic report preparation and delivery, reporting, and accountability of the services. During the March-September 2020 period, we delivered 3167 Telemedicine services, including 1618 Televisits, to 1694 patients (972 adults, 722 children) with a wide range of chronic neurological disorders. We successfully administered different clinical assessment and scales. Satisfaction among patients and caregivers was very high. CONCLUSIONS: During the dramatic emergency, we were able to take care of more than 1600 patients by organizing Neuro-telehealth in a few weeks, lessening the impact of the pandemic on fragile patients with chronic neurological disorders; this strategy is now stably embedded in our care pathways. In Italy, Telehealth is at present recognized and priced and is becoming a stable pillar of the health system.

Comparison of visual criteria for amyloid-PET reading: could criteria merging reduce inter-rater variability?

BACKGROUND: Three different amyloid tracers labeled with 18-flourine have been introduced into clinical use. The leaflets of tracers indicate different visual criteria for PET reporting. In clinical practice, it is not yet ascertained whether these criteria are equivalent in terms of diagnostic accuracy or if anyone is better than another. We aimed to evaluate the inter and intra-rater variability of visual assessment of 18F-Florbetapir PET/CT images among six independent readers with different clinical experience. METHODS: We analyzed 252 PET/CT scans, visually assessed by each reader three times, applying independently the three different reading criteria proposed. Each reader evaluated the regional uptake specifying for each cortical region a numeric value of grading of positivity in order to assign a final score. At the end of each reading a level of confidence was determined by assigning a score from 0 (negative) to 4 (positive). After first reading, those cases in which the evaluations by two experienced readers did not match (discordant cases) were independently reevaluated merging all the three different visual interpretation criteria. RESULTS: Good agreement was observed for visual interpretation among the six readers' confidence-level using independently the three visual reading criteria: ICC=0.83 (0.80-0.86) for 18F-florbetapir, ICC=0.84 (0.81-0.87) for 18F-florbetaben, and ICC=0.86 (0.83-0.88) for 18F-flutemetamol reading. A good inter-rater agreement was observed for final-score too: ICC=0.74 (0.70-0.78) for 18F-florbetapir; ICC=0.82 (0.79-0.85) for 18F-florbetaben; ICC=0.84 (0.81-0.87) for 18F-flutemetamol. Intra-rater agreement was good for final-score (from 0.76 to 0.90; P<0.001) and confidence-level (Spearman's rho from 0.89 to 1.00; P<0.001). Disagreement between the two experienced readers was observed in 22 of 252 cases (9%). The agreement converged over a second round of independent reading in 12 of 22 cases (54%), by merging all the criteria. CONCLUSIONS: All the criteria proposed are useful to determine the grading of positivity or negativity of amyloid deposition and their merging improves the diagnostic confidence and provides a better agreement.

Quantitative appraisal of the Amyloid Imaging Taskforce appropriate use criteria for amyloid-PET.

INTRODUCTION: We test the hypothesis that amyloid-positron emission tomography prescriptions, considered appropriate based on the Amyloid Imaging Taskforce (AIT) criteria, lead to greater clinical utility than AIT-inappropriate prescriptions. METHODS: We compared the clinical utility between patients who underwent amyloid-positron emission tomography appropriately or inappropriately and among the subgroups of patients defined by the AIT criteria. Finally, we performed logistic regressions to identify variables associated with clinical utility. RESULTS: We identified 171 AIT-appropriate and 67 AIT-inappropriate patients. AIT-appropriate and AIT-inappropriate cases did not differ in any outcomes of clinical utility (P > .05). Subgroup analysis denoted both expected and unexpected results. The logistic regressions outlined the primary role of clinical picture and clinical or neuropsychological profile in identifying patients benefitting from amyloid-positron emission tomography. DISCUSSION: Contrary to our hypothesis, also AIT-inappropriate prescriptions were associated with clinical utility. Clinical or neuropsychological variables, not taken into account by the AIT criteria, may help further refine criteria for appropriateness.

(123) I-2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl) nortropane single photon emission computed tomography and (123) I-metaiodobenzylguanidine myocardial scintigraphy in differentiating dementia with lewy bodies from other dementias: A comparative study.

OBJECTIVE: To compare the diagnostic value of striatal (123) I-2ß-carbomethoxy-3ß-(4-iodophenyl)-N-(3-fluoropropyl) nortropane ((123) I-FP-CIT) single photon emission computed tomography (SPECT) and (123) I-metaiodobenzylguanidine ((123) I-MIBG) myocardial scintigraphy in differentiating dementia with Lewy bodies (DLB) from other dementia types. METHODS: This prospective longitudinal study included 30 patients with a clinical diagnosis of DLB and 29 patients with non-DLB dementia (Alzheimer disease, n = 16; behavioral variant frontotemporal dementia, n = 13). All patients underwent (123) I-FP-CIT SPECT and (123) I-MIBG myocardial scintigraphy within a few weeks of clinical diagnosis. All diagnoses at each center were agreed upon by the local clinician and an independent expert, both unaware of imaging data, and re-evaluated after 12 months. Each image was visually classified as either normal or abnormal by 3 independent nuclear physicians blinded to patients' clinical data. RESULTS: Overall, sensitivity and specificity to DLB were respectively 93% and 100% for (123) I-MIBG myocardial scintigraphy, and 90% and 76% for (123) I-FP-CIT SPECT. Lower specificity of striatal compared to myocardial imaging was due to decreased (123) I-FP-CIT uptake in 7 non-DLB subjects (3 with concomitant parkinsonism) who had normal (123) I-MIBG myocardial uptake. Notably, in our non-DLB group, myocardial imaging gave no false-positive readings even in those subjects (n = 7) with concurrent medical illnesses (diabetes and/or heart disease) supposed to potentially interfere with (123) I-MIBG uptake. INTERPRETATION: (123) I-FP-CIT SPECT and (123) I-MIBG myocardial scintigraphy have similar sensitivity for detecting DLB, but the latter appears to be more specific for excluding non-DLB dementias, especially when parkinsonism is the only "core feature" exhibited by the patient. Our data also indicate that the potential confounding effects of diabetes and heart disease on (123) I-MIBG myocardial scintigraphy results might have been overestimated. Ann Neurol 2016;80:368-378.

Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage.

Three sets of research criteria are available for diagnosis of Alzheimer's disease in subjects with mild cognitive impairment: the International Working Group-1, International Working Group-2, and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage according to these criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and available biomarkers to classify subjects as prodromal Alzheimer's disease according to International Working Group-1 and International Working Group-2 criteria and in the high Alzheimer's disease likelihood group, conflicting biomarker groups (isolated amyloid pathology or suspected non-Alzheimer pathophysiology), and low Alzheimer's disease likelihood group according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures were the proportion of subjects with Alzheimer's disease at the mild cognitive impairment stage and progression to Alzheimer's disease-type dementia. We performed survival analyses using Cox proportional hazards models. According to the International Working Group-1 criteria, 850 (53%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 50% compared to 21% for subjects without prodromal Alzheimer's disease. According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 61% compared to 22% for subjects without prodromal Alzheimer's disease. According to the National Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high Alzheimer's disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220 (29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low Alzheimer's disease likelihood group. The 3-year progression rate to Alzheimer's disease-type dementia was 59% in the high Alzheimer's disease likelihood group, 22% in the isolated amyloid pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low Alzheimer's disease likelihood group. Our findings support the use of the proposed research criteria to identify Alzheimer's disease at the mild cognitive impairment stage. In clinical settings, the use of both amyloid and neuronal injury markers as proposed by the National Institute of Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials, selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer's disease likelihood group or the International Working Group-2 prodromal Alzheimer's disease group could be considered.

Do Beliefs about the Pathogenetic Role of Amyloid Affect the Interpretation of Amyloid PET in the Clinic.

BACKGROUND: Beliefs of dementia experts about the pathogenic role of amyloid in Alzheimer's disease (AD) may affect the use of amyloid positron emission tomography (PET). OBJECTIVE: To assess the role attributed to amyloid in AD pathogenesis by Italian dementia experts, and whether this modulates the impact of amyloid PET results in their diagnostic workup. METHODS: 22 dementia experts rated their beliefs about the pathogenic role of amyloid. Then, we asked them to rate the probability of change in diagnosis based on the result of amyloid PET for 7 case vignettes, depicting patients who initially received a diagnosis based on a comprehensive workup and later received amyloid PET results consistent or inconsistent with the clinical picture. RESULTS: 55% of the experts assigned a dominant role to amyloid, and 32% attributed a similar role to amyloid and tau in AD pathogenesis. The probability of change in diagnosis ranged from 17% (SD = 21.6) for cases with consistent to 51% (SD = 34) for cases with inconsistent PET versus clinical data. Diagnostic change was not biased by the clinicians' beliefs about AD pathogenesis. CONCLUSIONS: This work supports an unbiased interpretation of amyloid PET across different beliefs about the pathogenic role of amyloid, and a belief-independent reluctance to change diagnosis in cases where change is expected and recommended.

Hippocampal and amygdalar local structural differences in elderly patients with schizophrenia.

OBJECTIVES: Morphological abnormalities have been reported for the hippocampi and amygdalae in young schizophrenia patients, but very little is known about the pattern of abnormalities in elderly schizophrenia patients. Here we investigated local structural differences in the hippocampi and amygdalae of elderly schizophrenia patients compared with healthy elderly subjects. We also related these differences to clinical symptom severity. DESIGN: 20 schizophrenia patients (mean age: 67.4 ± 6.2 years; Mini-Mental State Exam: 22.8 ± 4.4) and 20 healthy elderly subjects (70.3 ± 7.5 years; 29.0 ± 1.1) underwent high resolution magnetic resonance imaging of the brain. The Radial Atrophy Mapping technique was used to reconstruct the 3D shape of the amygdala and the hippocampus. Local differences in tissue reductions were computed between groups and permutation tests were run to correct for multiple comparisons, in statistical maps thresholded at p = 0.05. RESULTS: Significant tissue reduction was observed bilaterally in the amygdala and hippocampus of schizophrenia patients. The basolateral-ventral-medial amygdalar nucleus showed the greatest involvement, with over 30% local tissue reduction. The centro-medial, cortical, and lateral nuclei were also atrophic in patients. The hippocampus showed significant tissue loss in the medio-caudal and antero-lateral aspects of CA1, and in medial section of its left head (pre- and para-subiculum). In the left amygdala and hippocampus, local tissue volumes were significantly correlated with negative symptoms. CONCLUSIONS: Tissue loss and altered morphology were found in elderly schizophrenia patients. Tissue loss mapped to amygdalo-hippocampal subregions known to have bidirectional and specific connections with frontal cortical and limbic structures and was related to clinical severity.

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA.

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis.

Coexistence of Amyotrophic Lateral Sclerosis and Alzheimer's Disease: Case Report and Review of the Literature.

We describe a case of amyotrophic lateral sclerosis (ALS) associated with Alzheimer's disease (AD) and review the literature about the coexistence of the two entities, highlighting the following: mean age at onset is 63.8 years, with slight female predominance; ALS tends to manifest after cognitive impairment and often begins in the bulbar region; average disease duration is 3 years; cognitive phenotype is mostly amnestic; the pattern of brain involvement is, in most cases, consistent with AD. Our case and the reviewed ones suggest that patients with ALS and dementia lacking unequivocal features of FTD should undergo additional examinations in order to recognize AD.

Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment.

BACKGROUND AND OBJECTIVE: Multicenter study aiming at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-Mild Cognitive Impairment, pre-MCI). METHODS: Data were obtained from the Network-AD project (NET-2011-02346784). The included subjects underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and, amyloid-PET. We used Principal Component Analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism. RESULTS: A total of 105 subjects (SCD=49, pre-MCI=56) were included. FDG-PET was normal in 45% of subjects and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the subjects that underwent amyloid-PET (n=60). PCA resulted in three neuropsychological factors: 1) executive/visuo-motor, correlating with hypometabolism in frontal, occipital cortices and basal ganglia; 2) memory, correlating with hypometabolism in temporo-parietal regions; 3) visuo-spatial/constructional, correlating with hypometabolism in fronto-parietal cortices. Two factors emerged from the neuropsychiatric PCA: 1) affective, correlating with hypometabolism in orbito-frontal, cingulate cortex, insula; 2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal and parietal regions. DISCUSSION: FDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI subjects. These results indicate that SCD and pre-MCI represent heterogeneous populations. Consistently, different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.

Educational interventions to improve detection and management of cognitive decline in primary care-An Italian multicenter pragmatic study.

Introduction: Timely detection of cognitive decline in primary care is essential to promote an appropriate care pathway and enhance the benefits of interventions. We present the results of a study aimed to evaluate the effectiveness of an educational intervention addressed to Italian family physicians (FPs) to improve timely detection and management of cognitive decline. Materials and methods: We conducted a pre-post study in six Italian health authorities (HAs) involving 254 FPs and 3,736 patients. We measured process and outcome indicators before the intervention (1 January 2014 to 31 December 2016) and after the intervention (1 January 2018 to 31 December 2019). One interactive face-to-face session workshop was delivered by local cognitive disorders and dementia specialists and FP advisors at each HA, in the period September 2017-December 2017. The session focused on key messages of the local Diagnostic and Therapeutic Care Pathway (DTCP) or regional guidelines: (a) the role of the FP for a timely suspicion of cognitive decline is fundamental; (b) when cognitive decline is suspected, the role of the FP is active in the diagnostic work-up; (c) FP's knowledge on pharmacological and non-pharmacological interventions is essential to improve the management of patients with cognitive decline. Results: An overall improvement in diagnostic procedures and management of patients with cognitive decline by FPs after the intervention was observed. The number of visits per year performed by FPs increased, and the time interval between the first FP consultation and the diagnosis was optimized. Neuroleptic use significantly decreased, whereas the use of benzodiazepines remained steadily high. Non-pharmacological interventions, or use of support services, were underrepresented even in the post-intervention. Differences among the participating HAs were identified and discussed. Discussion: Results from this study suggest the success of the educational intervention addressed to FPs in improving early detection and management of cognitive decline, highlighting the importance to continue medical education in this field. At the same time, further initiatives of care pathway dissemination and implementation should promote strategies to enhance interactions between primary and secondary care optimizing the collaboration between FPs and specialists.

Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data.

BACKGROUND: Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer's disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue. METHODS: Following the initiative of the University of Washington's National Alzheimer's Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms. RESULTS: Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward. CONCLUSIONS: The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings.

Postinfectious Neurologic Complications in COVID-19: A Complex Case Report.

A 40-y-old woman with severe acute respiratory syndrome coronavirus 2 infection developed neurologic manifestations (confusion, agitation, seizures, dyskinesias, and parkinsonism) a few weeks after the onset of severe acute respiratory syndrome. MRI and cerebrospinal fluid analyses were unremarkable, but 18F-FDG PET/CT showed limbic and extralimbic hypermetabolism. A full recovery, alongside 18F-FDG normalization in previously hypermetabolic areas, was observed after intravenous immunoglobulin administration.

Automatic multispectral MRI segmentation of human hippocampal subfields: an evaluation of multicentric test-retest reproducibility.

Accurate and reproducible automated segmentation of human hippocampal subfields is of interest to study their roles in cognitive functions and disease processes. Multispectral structural MRI methods have been proposed to improve automated hippocampal subfield segmentation accuracy, but the reproducibility in a multicentric setting is, to date, not well characterized. Here, we assessed test-retest reproducibility of FreeSurfer 6.0 hippocampal subfield segmentations using multispectral MRI analysis pipelines (22 healthy subjects scanned twice, a week apart, at four 3T MRI sites). The harmonized MRI protocol included two 3D-T1, a 3D-FLAIR, and a high-resolution 2D-T2. After within-session T1 averaging, subfield volumes were segmented using three pipelines with different multispectral data: two longitudinal ("long_T1s" and "long_T1s_FLAIR") and one cross-sectional ("long_T1s_FLAIR_crossT2"). Volume reproducibility was quantified in magnitude (reproducibility error-RE) and space (DICE coefficient). RE was lower in all hippocampal subfields, except for hippocampal fissure, using the longitudinal pipelines compared to long_T1s_FLAIR_crossT2 (average RE reduction of 0.4-3.6%). Similarly, the longitudinal pipelines showed a higher spatial reproducibility (1.1-7.8% of DICE improvement) in all hippocampal structures compared to long_T1s_FLAIR_crossT2. Moreover, long_T1s_FLAIR provided a small but significant RE improvement in comparison to long_T1s (p = 0.015), whereas no significant DICE differences were found. In addition, structures with volumes larger than 200 mm3 had better RE (1-2%) and DICE (0.7-0.95) than smaller structures. In summary, our study suggests that the most reproducible hippocampal subfield FreeSurfer segmentations are derived from a longitudinal pipeline using 3D-T1s and 3D-FLAIR. Adapting a longitudinal pipeline to include high-resolution 2D-T2 may lead to further improvements.

Keeping People with Dementia or Mild Cognitive Impairment in Employment: A Literature Review on Its Determinants.

Background: Approximately 10-20% of people with early onset dementias (EOD) or mild cognitive impairment (MCI) are aged under 65 and, due to extended working life and increasing prevalence of dementias, they more and more frequently will be present in the active workforce. This review aimed to synthesize the available information about the ability of people with EOD or MCI to retain their participation in the labor workforce. Methods: We searched SCOPUS and EMBASE for peer-reviewed papers that reported studies assessing work ability in employees with EOD or MCI that were published in the period of January 2010 to August 2019. Results: We selected four publications, in which 1012 participants with EOD or MCI were enrolled (41.2% males). Cognitive difficulties rather than motor dysfunction were found to reduce patients' ability to work. Two main themes emerged: management of dementia in the workplace and the impact of symptoms on working status. Conclusions: EOD and MCI impact on workforce participation by determining problems in executive functions. Although this review was based on a small sample of studies, it can be shown that support in the workplace may act as a facilitator to enhance workforce participation, and occupational health professionals can help patients with EOD or MCI continue working as much as possible.

Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts.

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify-CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD (n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from "slight" to "significant" in 80% of the cases. Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology.

Research criteria for the diagnosis of prodromal dementia with Lewy bodies.

The prodromal phase of dementia with Lewy bodies (DLB) includes (1) mild cognitive impairment (MCI), (2) delirium-onset, and (3) psychiatric-onset presentations. The purpose of our review is to determine whether there is sufficient information yet available to justify development of diagnostic criteria for each of these. Our goal is to achieve evidence-based recommendations for the recognition of DLB at a predementia, symptomatic stage. We propose operationalized diagnostic criteria for probable and possible mild cognitive impairment with Lewy bodies, which are intended for use in research settings pending validation for use in clinical practice. They are compatible with current criteria for other prodromal neurodegenerative disorders including Alzheimer and Parkinson disease. Although there is still insufficient evidence to propose formal criteria for delirium-onset and psychiatric-onset presentations of DLB, we feel that it is important to characterize them, raising the index of diagnostic suspicion and prioritizing them for further investigation.