Background: The COVID-19 pandemic is changing clinical practice in neurology, after the governments decided the introduction of social distancing and interruption of medical non-emergency services in many countries. Teleneurology is an effective tool for the remote evaluation of patients but its adoption for frontotemporal lobar dementia (FTD) is in a preliminary stage. Objective: We evaluated multidisciplinary assessment of patients with FTD using telehealth during the COVID-19 pandemic. Methods: All patients received a diagnosis of FTD during 2018-2019 according to international criteria. A structured questionnaire and Clinical Dementia Rating Scale (CDR)-FTD were used by the neurologist with patients and/or caregivers. Index symptoms of COVID-19 infection were searched. Results: Twenty-eight clinical interviews were completed with caregivers and four with both patients/caregivers. Most patients and caregivers were satisfied with the neurological interview and expressed their willingness to continue to be included in remote evaluation programs (90%). Fifty percent of patients experienced significant worsening of clinical picture and quality of life since the start of social distancing. The CDR-FTD scale revealed a significant worsening of behavior (p = 0.01) and language functions (p = 0.009), compared to the last in-person evaluation at the center. One patient presented index symptoms of COVID-19 infection and was confirmed to be positive for COVID-19 with pharyngeal swab. Conclusion:The study was conducted in Italy, one of the countries hit particularly hard by the COVID-19 pandemic, with interruption of all non-emergency medical services. Our study indicates that telemedicine is a valid tool to triage patients with FTD to increase practice outreach and efficiency.

Recent research on behavioral variant frontotemporal dementia (bvFTD) has shown that personality changes and executive dysfunctions are accompanied by a disease-specific anatomical pattern of cortical and subcortical atrophy. We investigated the structural topological network changes in patients with bvFTD in comparison to healthy controls. In particular, 25 bvFTD patients and 20 healthy controls underwent structural 3T MRI. Next, bilaterally averaged values of 34 cortical surface areas, 34 cortical thickness values, and six subcortical volumes were used to capture single-subject anatomical connectivity and investigate network organization using a graph theory approach. Relative to controls, bvFTD patients showed altered small-world properties and decreased global efficiency, suggesting a reduced ability to combine specialized information from distributed brain regions. At a local level, patients with bvFTD displayed lower values of local efficiency in the cortical thickness of the caudal and rostral middle frontal gyrus, rostral anterior cingulate, and precuneus, cuneus, and transverse temporal gyrus. A significant correlation was also found between the efficiency of caudal anterior cingulate thickness and Mini-Mental State Examination (MMSE) scores in bvFTD patients. Taken together, these findings confirm the selective disruption in structural brain networks of bvFTD patients, providing new insights on the association between cognitive decline and graph properties.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a progressive cognitive decline, mostly prominent in the domain of memory, but also associated with other cognitive deficits and non-cognitive symptoms. Reduced muscle strength is common in AD. However, the current understanding of its relationship with cognitive decline is limited. This study investigates the relationship between muscle strength and cognition in patients with AD and mild cognitive impairment (MCI). We enrolled 148 consecutive subjects, including 74 patients with probable AD dementia, 37 MCI, and 37 controls. Participants underwent neuropsychological evaluation focused on attention, working memory, declarative memory and learning. Muscle strength and muscle mass were measured through hand dynamometer and bio-electrical impedance analysis, respectively. Patients with AD dementia were divided with respect to the severity of cognitive impairment into mild and moderate-to-severe patients. Moderate-to-severe patients with AD presented lower handgrip strength than MCI and controls. No differences were observed in muscle mass. In MCI and AD dementia, handgrip strength was associated with overall cognitive functioning, attentional and memory performance. The routine implementation of handgrip strength assessment in the clinical work-up of patients with MCI and AD could potentially represent a simple method to monitor functional and cognitive decline along the disease course.

Background The clinical diagnosis of behavioral variant frontotemporal dementia (bvFTD) in patients with a history of primary psychiatric disorder (PPD) is challenging. PPD shows the typical cognitive impairments observed in patients with bvFTD. Therefore, the correct identification of bvFTD onset in patients with a lifetime history of PPD is pivotal for an optimal management. Methods Twenty‐nine patients with PPD were included in this study. After clinical and neuropsychological evaluations, 16 patients with PPD were clinically classified as bvFTD (PPD‐bvFTD+), while in 13 cases clinical symptoms were associated with the typical course of the psychiatric disorder itself (PPD‐bvFTD–). Voxel‐ and surface‐based investigations were used to characterize gray matter changes. Volumetric and cortical thickness measures were used to predict the clinical diagnosis at a single‐subject level using a support vector machine (SVM) classification framework. Finally, we compared classification performances of magnetic resonance imaging (MRI) data with automatic visual rating scale of frontal and temporal atrophy. Results PPD‐bvFTD+ showed a gray matter decrease in thalamus, hippocampus, temporal pole, lingual, occipital, and superior frontal gyri compared to PPD‐bvFTD– ( p < .05, family‐wise error‐corrected). SVM classifier showed a discrimination accuracy of 86.2% in differentiating PPD patients with bvFTD from those without bvFTD. Conclusions Our study highlights the utility of machine learning applied to structural MRI data to support the clinician in the diagnosis of bvFTD in patients with a history of PPD. Gray matter atrophy in temporal, frontal, and occipital brain regions may represent a useful hallmark for a correct identification of dementia in PPD at a single‐subject level.

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