The Together for Health - Virginia Research Program: A Multi-Modal Approach for Population Health Assessment.

Background: The Together for Health-Virginia (T4H-VA) Research Program aimed to advance cancer prevention, education, and outreach in Virginia. Creating a representative and inclusive cohort is critical to the program's mission and quality of outcomes. The T4H-VA Research Program utilized a multi-modal sampling approach to improve population health assessment.

Development of a decentralized cohort for studying post-acute sequelae of COVID-19 in India in the Data4life Study.

Background: Decentralized, digital health studies can provide real-world evidence of the lasting effects of COVID-19 on physical, socioeconomic, psychological, and social determinant factors of health in India. Existing research cohorts, however, are small and were not designed for longitudinal collection of comprehensive data from India's diverse population. Data4Life is a nationwide, digitally enabled, health research initiative to examine the post-acute sequelae of COVID-19 across individuals, communities, and regions.

A Digital Health Initiative (COVIDsmart) for Remote Data Collection and Study of COVID-19's Impact on the State of Virginia: Prospective Cohort Study.

Background: The COVID-19 pandemic has affected people's lives beyond severe and long-term physical health symptoms. Social distancing and quarantine have led to adverse mental health outcomes. COVID-19-induced economic setbacks have also likely exacerbated the psychological distress affecting broader aspects of physical and mental well-being.

Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records.

Background: Prostate cancer (PCa) screening is not routinely conducted in men aged 55 and younger, although this age group accounts for more than 10% of cases. Polygenic risk scores (PRSs) and patient data applied toward early prediction of PCa may lead to earlier interventions and increased survival. We have developed machine learning (ML) models to predict PCa risk in men 55 and under using PRSs combined with patient data.

Massive external validation of a machine learning algorithm to predict pulmonary embolism in hospitalized patients.

Background: Pulmonary embolism (PE) is a life-threatening condition associated with ~10% of deaths of hospitalized patients. Machine learning algorithms (MLAs) which predict the onset of pulmonary embolism (PE) could enable earlier treatment and improve patient outcomes. However, the extent to which they generalize to broader patient populations impacts their clinical utility.

Predicting Falls in Long-term Care Facilities: Machine Learning Study.

Background: Short-term fall prediction models that use electronic health records (EHRs) may enable the implementation of dynamic care practices that specifically address changes in individualized fall risk within senior care facilities.

Objective: The aim of this study is to implement machine learning (ML) algorithms that use EHR data to predict a 3-month fall risk in residents from a variety of senior care facilities providing different levels of care.

Methods: This retrospective study obtained EHR data (2007-2021) from Juniper Communities' proprietary database of 2785 individuals primarily residing in skilled nursing facilities, independent living facilities, and assisted living facilities across the United States.

Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm.

Background: Strokes represent a leading cause of mortality globally. The evolution of developing new therapies is subject to safety and efficacy testing in clinical trials, which operate in a limited timeframe. To maximize the impact of these trials, patient cohorts for whom ischemic stroke is likely during that designated timeframe should be identified.

Cognitive complaints are associated with smaller right medial temporal gray-matter volume in younger postmenopausal women.

Objective: Menopause is associated with increasing cognitive complaints and older women are at increased risk of developing Alzheimer disease compared to men. However, there is difficulty in early markers of risk using objective performance measures. We investigated the impact of subjective cognitive complaints on the cortical structure in a sample of younger postmenopausal women.

Preliminary Evidence That Cortical Amyloid Burden Predicts Poor Response to Antidepressant Medication Treatment in Cognitively Intact Individuals With Late-Life Depression.

Objective: Amyloid accumulation, the pathological hallmark of Alzheimer's disease, may predispose some older adults to depression and cognitive decline. Deposition of amyloid also occurs prior to the development of cognitive decline. It is unclear whether amyloid influences antidepressant outcomes in cognitively intact depressed elders.

Accelerated brain aging predicts impaired cognitive performance and greater disability in geriatric but not midlife adult depression.

Depression is associated with markers of accelerated aging, but it is unclear how this relationship changes across the lifespan. We examined whether a brain-based measure of accelerated aging differed between depressed and never-depressed subjects across the adult lifespan and whether it was related to cognitive performance and disability. We applied a machine-learning approach that estimated brain age from structural MRI data in two depressed cohorts, respectively 170 midlife adults and 154 older adults enrolled in studies with common entry criteria.

Texture Analysis of F-18 Fluciclovine PET/CT to Predict Biochemically Recurrent Prostate Cancer: Initial Results.

Predicting biochemical recurrence of prostate cancer is imperative for initiating early treatment, which can improve the outcome of cancer treatment. However, because of inter- and intrareader variability in interpretation of F-18 fluciclovine positron emission tomography/computed tomography (PET/CT), it is difficult to reliably discern between necrotic tissue owing to radiation therapy and tumor tissue. Our goal is to develop a computational methodology using Haralick texture analysis that can be used as an adjunct tool to improve and standardize the interpretation of F-18 fluciclovine PET/CT to identify biochemical recurrence of prostate cancer.

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder.

To reconcile the inconsistency of the association between the resting-state functional connectivity (RSFC) and cognitive performance in healthy and depressed groups due to high variance of both measures, we proposed a Bayesian spatio-temporal model to precisely and accurately estimate the RSFC in depressed and nondepressed participants. This model was employed to estimate spatially-adjusted functional connectivity (saFC) in the extended default mode network (DMN) that was hypothesized to correlate with cognitive performance in both depressed and nondepressed. Multiple linear regression models were used to study the relationship between DMN saFC and cognitive performance scores measured in the following four cognitive domains while adjusting for age, sex, and education.

In vivo network models identify sex differences in the spread of tau pathology across the brain.

Introduction: We examined networks of tau connectivity between brain regions based on correlations of their [F]flortaucipir positron emission tomography (PET) uptake to evaluate sex-specific differences in brain-wide tau propagation.

Methods: PET data of clinically normal and mild cognitive impairment (MCI) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to examine differences in network architectures across the groups.

Results: The tau-based network architecture resembled progression of tauopathy from Braak stage I to VI regions.

Persistent Intrinsic Functional Network Connectivity Alterations in Middle-Aged and Older Women With Remitted Depression.

Background: In younger adults, residual alterations in functional neural networks persist during remitted depression. However, there are fewer data for midlife and older adults at risk of recurrence. Such residual network alterations may contribute to vulnerability to recurrence.

Associations of informant-based sleep reports with Alzheimer's disease pathologies.

Purpose: Recent studies have found associations of increased brain amyloid beta (Aβ) accumulation and several abnormal sleep-wake patterns, including shorter latency and increased fragmentation in preclinical Alzheimer's disease (AD). There is little known about the relationship between sleep and tau. The objective of this study was to understand the associations of both tau and Aβ with early signs of sleep and night-time behavior changes in clinically normal elderly adults.

The relationship between domain-specific subjective cognitive decline and Alzheimer's pathology in normal elderly adults.

We evaluated the associations of subjective (self-reported everyday cognition [ECog]) and objective cognitive measures with regional amyloid-β (Aβ) and tau accumulation in 86 clinically normal elderly subjects from the Alzheimer's Disease Neuroimaging Initiative. Regression analyses were conducted to identify whether individual ECog domains (Memory, Language, Organization, Planning, Visuospatial, and Divided Attention) were equally or differentially associated with regional [F]florbetapir and [F]flortaucipir uptake and how these associations compared to those obtained with objective cognitive measures. A texture analysis, the weighted 2-point correlation, was used as an additional approach for estimating the whole-brain tau burden without positron emission tomography intensity normalization.

Hyperpolarizing Concentrated Metronidazole NO Group over Six Chemical Bonds with More than 15 % Polarization and a 20 Minute Lifetime.

The NMR hyperpolarization of uniformly N-labeled [ N ]metronidazole is demonstrated by using SABRE-SHEATH. In this antibiotic, the NO group is hyperpolarized through spin relays created by N spins in [ N ]metronidazole, and the polarization is transferred from parahydrogen-derived hydrides over six chemical bonds. In less than a minute of parahydrogen bubbling at approximately 0.

Task-based design of a synthetic-collimator SPECT system used for small animal imaging.

Purpose: In traditional multipinhole SPECT systems, image multiplexing - the overlapping of pinhole projection images - may occur on the detector, which can inhibit quality image reconstructions due to photon-origin uncertainty. One proposed system to mitigate the effects of multiplexing is the synthetic-collimator SPECT system. In this system, two detectors, a silicon detector and a germanium detector, are placed at different distances behind the multipinhole aperture, allowing for image detection to occur at different magnifications and photon energies, resulting in higher overall sensitivity while maintaining high resolution.

A new data analysis approach for measuring longitudinal changes of metabolism in cognitively normal elderly adults.

Introduction: Previously, we discussed several critical barriers in including [F] fluorodeoxyglucose positron emission tomography ([F]FDG-PET) imaging of preclinical Alzheimer's disease (AD) subjects. These factors included the reference region selection and intensity normalization of PET images and the within- and across-subject variability of affected brain regions. In this study, we utilized a novel FDG-PET analysis, the regional FDG time correlation coefficient, rFTC, that can address and resolve these barriers and provide a more sensitive way of monitoring longitudinal changes in metabolism of cognitively normal elderly adults.

Application of Haralick texture features in brain [F]-florbetapir positron emission tomography without reference region normalization.

Objectives: Semi-quantitative image analysis methods in Alzheimer's Disease (AD) require normalization of positron emission tomography (PET) images. However, recent studies have found variabilities associated with reference region selection of amyloid PET images. Haralick features (HFs) generated from the Gray Level Co-occurrence Matrix (GLCM) quantify spatial characteristics of amyloid PET radiotracer uptake without the need for intensity normalization.

Longitudinal Positron Emission Tomography in Preventive Alzheimer's Disease Drug Trials, Critical Barriers from Imaging Science Perspective.

Recent Alzheimer's trials have recruited cognitively normal people at risk for Alzheimer's dementia. Due to the lack of clinical symptoms in normal population, conventional clinical outcome measures are not suitable for these early trials. While several groups are developing new composite cognitive tests that could serve as potential outcome measures by detecting subtle cognitive changes in normal people, there is a need for longitudinal brain imaging techniques that can correlate with temporal changes in these new tests and provide additional objective measures of neuropathological changes in brain.

Reference tissue normalization in longitudinal (18)F-florbetapir positron emission tomography of late mild cognitive impairment.

Background: Semiquantitative methods such as the standardized uptake value ratio (SUVR) require normalization of the radiotracer activity to a reference tissue to monitor changes in the accumulation of amyloid-β (Aβ) plaques measured with positron emission tomography (PET). The objective of this study was to evaluate the effect of reference tissue normalization in a test-retest (18)F-florbetapir SUVR study using cerebellar gray matter, white matter (two different segmentation masks), brainstem, and corpus callosum as reference regions.

Methods: We calculated the correlation between (18)F-florbetapir PET and concurrent cerebrospinal fluid (CSF) Aβ1-42 levels in a late mild cognitive impairment cohort with longitudinal PET and CSF data over the course of 2 years.

Development of a Germanium Small-Animal SPECT System.

Advances in fabrication techniques, electronics, and mechanical cooling systems have given rise to germanium detectors suitable for biomedical imaging. We are developing a small-animal SPECT system that uses a double-sided Ge strip detector. The detector's excellent energy resolution may help to reduce scatter and simplify processing of multi-isotope imaging, while its ability to measure depth of interaction has the potential to mitigate parallax error in pinhole imaging.

Modeling clustered activity increase in amyloid-beta positron emission tomographic images with statistical descriptors.

Background: Amyloid-beta (Aβ) imaging with positron emission tomography (PET) holds promise for detecting the presence of Aβ plaques in the cortical gray matter. Many image analyses focus on regional average measurements of tracer activity distribution; however, considerable additional information is available in the images. Metrics that describe the statistical properties of images, such as the two-point correlation function (S2), have found wide applications in astronomy and materials science.

Reducing multiplexing artifacts in multi-pinhole SPECT with a stacked silicon-germanium system: a simulation study.

In pinhole single photon emission computed tomography (SPECT), multi-pinhole collimators can increase sensitivity but may lead to projection overlap, or multiplexing, which can cause image artifacts. In this work, we explore whether a stacked-detector configuration with a germanium and a silicon detector, used with 123I (27-32, 159 keV), where little multiplexing occurs in the Si projections, can reduce image artifacts caused by highly-multiplexed Ge projections. Simulations are first used to determine a reconstruction method that combines the Si and Ge projections to maximize image quality.