Prediction, prognosis and monitoring of neurodegeneration at biobank-scale via machine learning and imaging.

Background: Alzheimer's disease and related dementias (ADRD) and Parkinson's disease (PD) are the most common neurodegenerative conditions. These central nervous system disorders impact both the structure and function of the brain and may lead to imaging changes that precede symptoms. Patients with ADRD or PD have long asymptomatic phases that exhibit significant heterogeneity.

Differences in Brain Volume in Military Service Members and Veterans After Blast-Related Mild TBI: A LIMBIC-CENC Study.

Importance: Blast-related mild traumatic brain injuries (TBIs), the "signature injury" of post-9/11 conflicts, are associated with clinically relevant, long-term cognitive, psychological, and behavioral dysfunction and disability; however, the underlying neural mechanisms remain unclear.

Objective: To investigate associations between a history of remote blast-related mild TBI and regional brain volume in a sample of US veterans and active duty service members.

Design, Setting, And Participants: Prospective cohort study of US veterans and active duty service members from the Long-Term Impact of Military-Relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC), which enrolled more than 1500 participants at 5 sites used in this analysis between 2014 and 2023.

Developmental mouse brain common coordinate framework.

3D brain atlases are key resources to understand the brain's spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.

The ANTsX Ecosystem for Mapping the Mouse Brain.

Precision mapping techniques coupled with high resolution image acquisition of the mouse brain permit the study of the spatial organization of gene expression and their mutual interaction for a comprehensive view of salient structural/functional relationships. Such research is facilitated by standardized anatomical coordinate systems, such as the well-known Allen Common Coordinate Framework (AllenCCFv3), and the ability to spatially map to such standardized spaces. The Advanced Normalization Tools Ecosystem is a comprehensive open-source software toolkit for generalized quantitative imaging with applicability to multiple organ systems, modalities, and animal species.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank.

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem.

Pulmonary MRI with hyperpolarized xenon-129 demonstrates novel alterations in gas transfer across the air-blood barrier in asthma.

Background: Individuals with asthma can vary widely in clinical presentation, severity, and pathobiology. Hyperpolarized xenon-129 (Xe129) MRI is a novel imaging method to provide 3-D mapping of both ventilation and gas exchange in the human lung.

Purpose: To evaluate the functional changes in adults with asthma as compared to healthy controls using Xe129 MRI.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank.

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem.

Neurological Effects of Repeated Blast Exposure in Special Operations Personnel.

Exposure to blast overpressure has been a pervasive feature of combat-related injuries. Studies exploring the neurological correlates of repeated low-level blast exposure in career "breachers" demonstrated higher levels of tumor necrosis factor alpha (TNFα) and interleukin (IL)-6 and decreases in IL-10 within brain-derived extracellular vesicles (BDEVs). The current pilot study was initiated in partnership with the U.

Developmental Mouse Brain Common Coordinate Framework.

3D standard reference brains serve as key resources to understand the spatial organization of the brain and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of standard 3D reference atlases for developing mouse brains has hindered advancement of our understanding of brain development. Here, we present a multimodal 3D developmental common coordinate framework (DevCCF) spanning mouse embryonic day (E) 11.

ReMiND: Recovery of Missing Neuroimaging using Diffusion Models with Application to Alzheimer's Disease.

Objective: Missing data is a significant challenge in medical research. In longitudinal studies of Alzheimer's disease (AD) where structural magnetic resonance imaging (MRI) is collected from individuals at multiple time points, participants may miss a study visit or drop out. Additionally, technical issues such as participant motion in the scanner may result in unusable imaging data at designated visits.

Lung Volume Dependence and Repeatability of Hyperpolarized Xe MRI Gas Uptake Metrics in Healthy Volunteers and Participants with COPD.

Purpose: To assess the effect of lung volume on measured values and repeatability of xenon 129 (Xe) gas uptake metrics in healthy volunteers and participants with chronic obstructive pulmonary disease (COPD).

Materials And Methods: This Health Insurance Portability and Accountability Act-compliant prospective study included data (March 2014-December 2015) from 49 participants (19 with COPD [mean age, 67 years ± 9 (SD)]; nine women]; 25 older healthy volunteers [mean age, 59 years ± 10; 20 women]; and five young healthy women [mean age, 23 years ± 3]). Thirty-two participants underwent repeated Xe and same-breath-hold proton MRI at residual volume plus one-third forced vital capacity (RV+FVC/3), with 29 also undergoing one examination at total lung capacity (TLC).

Hyperpolarized Xenon-129: A New Tool to Assess Pulmonary Physiology in Patients with Pulmonary Fibrosis.

Purpose: The existing tools to quantify lung function in interstitial lung diseases have significant limitations. Lung MRI imaging using inhaled hyperpolarized xenon-129 gas (Xe) as a contrast agent is a new technology for measuring regional lung physiology. We sought to assess the utility of the Xe MRI in detecting impaired lung physiology in usual interstitial pneumonia (UIP).

An Anatomical Template for the Normalization of Medical Images of Adult Human Hands.

During medical image analysis, it is often useful to align (or 'normalize') a given image of a given body part to a representative standard (or 'template') of that body part. The impact that brain templates have had on the analysis of brain images highlights the importance of templates in general. However, templates for human hands do not exist.

DeepComBat: A Statistically Motivated, Hyperparameter-Robust, Deep Learning Approach to Harmonization of Neuroimaging Data.

Neuroimaging data from multiple batches (i.e. acquisition sites, scanner manufacturer, datasets, etc.

Differential effects of emotional valence on mnemonic performance with greater hippocampal maturity.

The hippocampal formation (HF) facilitates declarative memory, with subfields providing unique contributions to memory performance. Maturational differences across subfields facilitate a shift toward increased memory specificity, with peripuberty sitting at the inflection point. Peripuberty is also a sensitive period in the development of anxiety disorders.

Posterior white matter hyperintensities are associated with reduced medial temporal lobe subregional integrity and long-term memory in older adults.

White matter hyperintensities are a marker of small vessel cerebrovascular disease that are strongly related to cognition in older adults. Similarly, medial temporal lobe atrophy is well-documented in aging and Alzheimer's disease and is associated with memory decline. Here, we assessed the relationship between lobar white matter hyperintensities, medial temporal lobe subregional volumes, and hippocampal memory in older adults.

Automated analysis of low-field brain MRI in cerebral malaria.

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images. These methods, however, may not translate to low-resolution images acquired on magnetic resonance imaging (MRI) scanners with lower magnetic field strength.

Deformation-based morphometry identifies deep brain structures protected by ocrelizumab.

Background: Despite advancements in treatments for multiple sclerosis, insidious disease progression remains an area of unmet medical need, for which atrophy-based biomarkers may help better characterize the progressive biology.

Methods: We developed and applied a method of longitudinal deformation-based morphometry to provide voxel-level assessments of brain volume changes and identified brain regions that were significantly impacted by disease-modifying therapy.

Results: Using brain MRI data from two identically designed pivotal trials of relapsing multiple sclerosis (total N = 1483), we identified multiple deep brain regions, including the thalamus and brainstem, where volume loss over time was reduced by ocrelizumab (p < 0.

Mitigating site effects in covariance for machine learning in neuroimaging data.

To acquire larger samples for answering complex questions in neuroscience, researchers have increasingly turned to multi-site neuroimaging studies. However, these studies are hindered by differences in images acquired across multiple sites. These effects have been shown to bias comparison between sites, mask biologically meaningful associations, and even introduce spurious associations.

Negative overgeneralization is associated with anxiety and mechanisms of pattern completion in peripubertal youth.

This study examines neural mechanisms of negative overgeneralization, the increased likelihood of generalizing negative information, in peri-puberty. Theories suggest that weak pattern separation [overlapping representations are made distinct, indexed by dentate gyrus/ cornu ammonis (CA)3 hippocampal subfield activation] underlies negative overgeneralization. We alternatively propose that neuro-maturational changes that favor pattern completion (cues reinstate stored representations, indexed by CA1 activation) are modulated by circuitry involved in emotional responding [amygdala, medial prefrontal cortices (mPFC)] to drive negative overgeneralization.

Image- versus histogram-based considerations in semantic segmentation of pulmonary hyperpolarized gas images.

Purpose: To characterize the differences between histogram-based and image-based algorithms for segmentation of hyperpolarized gas lung images.

Methods: Four previously published histogram-based segmentation algorithms (ie, linear binning, hierarchical k-means, fuzzy spatial c-means, and a Gaussian mixture model with a Markov random field prior) and an image-based convolutional neural network were used to segment 2 simulated data sets derived from a public (n = 29 subjects) and a retrospective collection (n = 51 subjects) of hyperpolarized 129Xe gas lung images transformed by common MRI artifacts (noise and nonlinear intensity distortion). The resulting ventilation-based segmentations were used to assess algorithmic performance and characterize optimization domain differences in terms of measurement bias and precision.