Quantitative brain volumetric data has shown promise in predicting cognitive decline however, due to labor-intensive manual segmentation methods required, this technique has had limited clinical applicability. Our aim was to assess the diagnostic efficacy of using NeuroreaderTM(NR), a FDA cleared automated segmentation software, in patients with mild cognitive impairment (MCI) to supplement neuropsychological testing. 349 MCI patients with 3 year follow up were included of which 155 progressed to AD within 3-years. Clinical data was obtained through the Alzheimer's Disease Neuroimaging Initiative, a publically available North American database. Baseline and 1 year differences in 12 regions of interest (ROI) were analyzed using NeuroreaderTM. Receiver Operating Characteristic (ROC) curves were generated using 1 year changes in Mini Mental Status Exam (MMSE) scores with and without NR metrics. Results were compared using the DeLong method to assess the diagnostic efficacy of NR. Adjusting for age, gender, and education level, combining 1-year changes in NR metrics with MMSE scores outperformed MMSE scores alone. AUC 86.4% (CI 82.7 – 90.2) vs AUC 79.9% (CI 75.2 – 84.6). AUC difference(DeLong), p < .05. Tracking 1 yr. brain volumetry with Neuroreader can improve the prediction of 3 year AD conversion in patients with MCI . Comparing model using 1-year MMSE changes alone (Red) vs. 1-year MMSE changes with 1-year NR changes (Blue). Model combining MMSE and NR out-performed model using MMSE alone (AUC 86.4% vs. AUC 79.9%).
The success of 11C-PIB in imaging Aβ amyloid pathology prompted a search for an 18F-labeled agent, suitable for regional production and wide community use. We studied three related 18F-labeled compounds in 42 cognitively healthy elderly volunteers and 39 individuals with AD. Participants received a single i.v. injection of either 10 mCi (370 MBq) 18F-AV-45, 5 mCi (195 MBq) 18F-AV-138, or 5 mCi 18F-AV-144, followed by 90 min dynamic brain PET imaging. The pattern of tracer uptake and retention was similar across the three compounds: individuals with AD showed selective retention of tracer in cortical areas expected to be high in amyloid deposition, whereas healthy elderly volunteers showed rapid wash out, with only minimal cortical tracer retention. Standard uptake values (SUVs) were calculated for regions including the frontal cortex, temporal cortex, precuneus and cerebellum. SUV ratios (SUVRs) were calculated as ratios of cortical target areas to the cerebellum. Compared to the cognitively healthy volunteers, the individuals with AD showed consistently higher SUVRs in the cortical target areas, for all three compounds. The precuneus was most sensitive region; e.g., 50–70 min after injection of 18F-AV-45, the median precuneus to cerebellum SUVR was 1.87 for individuals with AD and 1.19 for volunteers. Two of 16 cognitively healthy volunteers studied with 18F-AV-45, 2 of 13 studied with 18F-AV-144 and 1 of 9 studied with 18F-AV-138 (5 of 42 total) showed a pattern of tracer uptake similar to individuals with AD. Mintun et al (Neurology, 67:446, 2006) have reported a similar percentage of Aβ positive elderly volunteers using 11C-PIB. Two individuals diagnosed as AD (one studied with 18F-AV-45 and one studied with 18F-AV-138) had a pattern of tracer uptake similar to healthy volunteers. Chart notes for both patients suggested an unusual presentation – prominent Parkinsonism in one case and slowly progressive dementia in the other. Although the compounds were similar in pattern and quantitation of tracer retention, there were differences in kinetics, with 18F-AV-144 most rapid and 18F-AV-138 slowest, and in dosimetry and image quality, which will be considered in selecting the lead compound for Phase II development.
Background and Purpose: To characterize the global physician community’s opinions on the use of digital tools for COVID-19 public health surveillance and self-surveillance. Materials and Methods: Cross-sectional, random, stratified survey done on Sermo, a physician networking platform, between September 9 and 15, 2020. We aimed to sample 1000 physicians divided among the USA, EU, and rest of the world. The survey questioned physicians on the risk-benefit ratio of digital tools, as well as matters of data privacy and trust. Statistical Analysis Used: Descriptive statistics examined physicians’ characteristics and opinions by age group, gender, frontline status, and geographic region. ANOVA, t -test, and Chi-square tests with P < 0.05 were viewed as qualitatively different. As this was an exploratory study, we did not adjust for small cell sizes or multiplicity. We used JMP Pro 15 (SAS), as well as Protobi. Results: The survey was completed by 1004 physicians with a mean (standard deviation) age of 49.14 (12) years. Enthusiasm was highest for self-monitoring smartwatches (66%) and contact tracing apps (66%) and slightly lower (48-56%) for other tools. Trust was highest for health providers (68%) and lowest for technology companies (30%). Most respondents (69.8%) felt that loosening privacy standards to fight the pandemic would lead to misuse of privacy in the future. Conclusion: The survey provides foundational insights into how physicians think of surveillance.
Alzheimer's disease (AD) is characterized by cognitive deficits that become increasingly debilitating with disease progression. Event-related potentials (ERP) provide a real-time physiological measure of cognitive performance that can be useful for both patients’ cognitive assessment and evaluation of the pro-cognitive effects of novel therapies. In the present study, we have measured correlations between ERP features and psychometric tests that are the current gold standard for cognitive assessment and evaluation of therapeutic interventions in AD. Moreover, we have investigated how well ERP features track composite z-scores generated from the psychometric/behavioral tests for cognitive domains affected in AD. 100 subjects between 60 and 90 years old with probable mild AD and 100 age-matched Controls (HC) were recruited at seven clinical sites in the US. All study subjects underwent psychometric and ERP testing. The neuropsychological tests were chosen as a comprehensive battery of tests that included those selected for the ADNI project. The ERP protocol consisted of a two-deviant active auditory oddball paradigm; the test was administered in outpatient settings, using an integrated hardware/software system for data collection and analysis. At the end of the study, latency and amplitude of the ERP features were automatically extracted from the data. These measures were then correlated with the results from individual psychometric tests and standardized z-scores for processing speed, executive function, immediate memory, delayed (recall) memory, and attention. Preliminary data analyses on a subset of ERP features show significant correlations between P3a amplitude and the Digit Symbol Substitution test, and between P3b amplitude and the Category Fluency Test. Our data confirms previous findings that these two ERP features reflect semantic memory and attention respectively. Analysis of correlations between ERP features and standardized z-scores for cognitive dimensions is underway. At present, assessment of cognitive function in AD and evaluation of pro-cognitive effects of novel therapies are mostly done using psychometric and behavioral measures. Though these tests provide useful cognitive measures, they can be expensive and time consuming. Preliminary results from our study suggest that ERP can provide an inexpensive, practical alternative that is not subject to language barriers or rater bias.
Community detection in real-world graphs presents a number of challenges. First, even if the number of detected communities grows linearly with the graph size, it becomes impossible to manually inspect each community for value added to the application knowledge base. Mining for communities with query nodes as knowledge priors could allow for filtering out irrelevant information and for enriching end-users knowledge associated with the problem of interest, such as discovery of genes functionally associated with the Alzheimer's (AD) biomarker genes.Second, the data-intensive nature of community enumeration challenges current approaches that often assume that the input graph and the detected communities fit in memory. As computer systems scale, DRAM memory sizes are not expected to increase linearly, while technologies such as SSD memories have the potential to provide much higher capacities at a lower power-cost point, and have a much lower latency than disks. Out-of-core algorithms and/or database-inspired indexing could provide an opportunity for different design optimizations for query-driven community detection algorithms tuned for emerging architectures.Therefore, this work addresses the need for query-driven and memory-efficient community detection. Using maximal cliques as the community definition, due to their high signal-to-noise ratio, we propose and systematically compare two contrasting methods: indexed-based and out-of-core. Both methods improve peak memory efficiency as much as 1000X compared to the state-of-the-art. However, the index-based method, which also has a 10-to-100-fold run time reduction, outperforms the out-of-core algorithm in most cases. The achieved scalability enables the discovery of diseases that are known to be or likely associated with Alzheimer's when the genome-scale network is mined with AD biomarker genes as knowledge priors.
Objective The purpose of this study was to assess the status of 156 adult volunteers with major depressive disorder (MDD) 6 months after completion of a study in which they were randomly assigned to a 4-month course of aerobic e-ercise, sertraline therapy, or a combination of e-ercise and sertraline. Methods The presence and severity of depression were assessed by clinical interview using the Diagnostic Interview Schedule and the Hamilton Rating Scale for Depression (HRSD) and by self-report using the Beck Depression Inventory. Assessments were performed at baseline, after 4 months of treatment, and 6 months after treatment was concluded (ie, after 10 months). Results After 4 months patients in all three groups e-hibited significant improvement; the proportion of remitted participants (ie, those who no longer met diagnostic criteria for MDD and had an HRSD score <8) was comparable across the three treatment conditions. After 10 months, however, remitted subjects in the e-ercise group had significantly lower relapse rates (p = .01) than subjects in the medication group. Exercising on one’s own during the follow-up period was associated with a reduced probability of depression diagnosis at the end of that period (odds ratio = 0.49, p = .0009). Conclusions Among individuals with MDD, e-ercise therapy is feasible and is associated with significant therapeutic benefit, especially if e-ercise is continued over time.
Medial temporal lobe activation, as measured by functional magnetic resonance imaging (fMRI), has been proposed as a possible early marker of Alzheimer's disease (AD). Decreases in medial temporal lobe activation in AD have been well described, however findings in the mild cognitive impairment (MCI) population have been less consistent. The purpose of this study was to detect changes in functional brain activity in incipient AD across the entire brain using fMRI during a face–name associative memory encoding task. The paradigm involved encoding of novel face–name pairs and familiar face–name pairs which were presented to the subject within a blocked design for later retrieval. Thirty–four non–demented individuals with MCI, 13 patients with mild AD, and 28 healthy elderly controls participated in the study. The left hippocampus and right parahippocampal gyrus revealed decreased activation for novel vs familiar face–name encoding in AD, but not in the MCI group, whereas left fusiform gyrus showed decreased activation in MCI. Bilateral posterior cingulate cortex (PCC), including the precuneus, demonstrated “deactivation” in the healthy elderly controls. The magnitude of deactivation demonstrated a monotonic decrease from controls to MCI to AD in an ANCOVA analysis, using age as a covariate. Deactivation in the PCC also significantly correlated with score on the delayed portion of the California Verbal Learning Test (CVLT). Findings of decreased deactivation in the PCC are consistent with those of other studies indicating decreased default–mode activity in AD. Deactivation in the PCC could be a more sensitive and early fMRI marker of AD compared to activation in the MTL, which is less consistent in the prodromal stages of the disease. Current findings further support the hypothesis that default–mode activity in the PCC might be related to episodic memory processing, which is impaired in mild and prodromal AD.
Dementia caregivers often have negative health consequences from their on-going caregiving responsibilities and are often described as being the "hidden patients". Dementia caregivers brain health has not been thoroughly assessed to determine if and how caregiver burden may affect cognitive performance. To test the effects of psychological distress on cognitive performance among dementia caregivers, psychological characteristics and brain performance were assessed via an online study using a lifestyle survey and Brain Performance Test (BPT) developed by Lumosity along with DANA an FDA cleared neurocogntive assessment tool. Participants consisted of 558 caregivers (the majority being Female) of dementia patients (Alzheimer's, Vascular, Other). Participants self-reported on their level of education, perceived personal support and perceived physical health and completed the BPT. The survey and BPT were administered to 558 caregivers of dementia patients. We found that the majority of caregivers scored lower on the BPT when compared to a population of similar average age (N= 81,076). This study also demonstrated that perceived physical health positively predicts cognitive performance for those caregivers with above average levels of perceived support. This study extends current research on the relationship between caregiving and cognitive functioning by examining the impact of psychological well-being on cognitive performance of caregivers of dementia patients. Although cognitive decline has been shown to occur with age, the findings of this study illustrate that caregivers of dementia patients perform, on average, lower than those of similar age. This study found that neither perceived physical health nor perceived personal support, alone, influences cognitive performance among caregivers of dementia patients. Indeed, the findings in this study demonstrate that a combination of perceived physical health and perceived support predict greater cognitive performance for caregivers with a high perception of support. Furthermore, this study demonstrate that this tool can be used for assess early detection of cognitive decline.
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