Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study.

INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.

Impact of Transoral Endoscopic Vestibular Approach Thyroidectomy on Pathologic Assessment.

CONTEXT.­: Since 2016, transoral endoscopic thyroid resection with vestibular approach (TOETVA) has been increasingly performed in the United States. Although guidelines for the procedure are evolving, indeterminate and malignant preoperative cytopathologic diagnoses are not a contraindication. There are limited data related to the pathologic examination of these specimens. OBJECTIVE.­: To examine the clinicopathologic features of TOETVA specimens with particular attention to limitations of interpretation of pathologic parameters and final diagnosis. DESIGN.­: We reviewed age, sex, preoperative imaging and cytologic diagnoses, surgical pathology, and clinical follow-up data in TOETVA resections from our institution for procedures performed between March 2016 and December 2019. RESULTS.­: Fifty cases of TOETVA were identified, comprising 48 women and 2 men with a mean age of 47 years. Preoperative cytologic diagnoses were available in 47 cases and included 19 nondiagnostic/benign (Bethesda I/II), 24 follicular lesion of undetermined significance/suspicious for follicular neoplasm (Bethesda III/IV), and 4 suspicious/malignant diagnoses (Bethesda V/VI). Thirty-four cases (68%) among the surgical resection specimens showed disruption and/or fragmentation. Thirty-nine cases were negative for carcinoma, including hyperplasias and benign/indolent neoplasms. Eleven cases exhibited papillary thyroid carcinoma. Final diagnoses were reached in all disrupted/fragmented cases. In 2 cases of papillary thyroid carcinoma, tumor size, microscopic extrathyroidal extension, and margin status could not be determined. CONCLUSIONS.­: A significant proportion of TOETVA specimens are disrupted/fragmented, which can compromise information about tumors, including size, number, margin status, and microscopic extrathyroidal extension. Given that these parameters inform treatment and follow-up, this should be considered when selecting patients for TOETVA.

Patterns of sociocognitive stratification and perinatal risk in the child brain.

The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain-environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for adaptation and growth but also increased susceptibility to environmental perturbations, such as the characteristics of social relationships, family environment, quality of schools and activities, financial security, urbanization and pollution, drugs, cultural practices, and values, that all act in concert with our genetic architecture and biology. Our multivariate brain-behavior mapping in 7,577 children aged 9 to 11 y across 585 brain imaging phenotypes and 617 cognitive, behavioral, psychosocial, and socioeconomic measures revealed three population modes of brain covariation, which were robust as assessed by cross-validation and permutation testing, taking into account siblings and twins, identified using genetic data. The first mode revealed traces of perinatal complications, including preterm and twin birth, eclampsia and toxemia, shorter period of breastfeeding, and lower cognitive scores, with higher cortical thickness and lower cortical areas and volumes. The second mode reflected a pattern of sociocognitive stratification, linking lower cognitive ability and socioeconomic status to lower cortical thickness, area, and volumes. The third mode captured a pattern related to urbanicity, with particulate matter pollution (PM25) inversely related to home value, walkability, and population density, associated with diffusion properties of white matter tracts. These results underscore the importance of a multidimensional and interdisciplinary understanding, integrating social, psychological, and biological sciences, to map the constituents of healthy development and to identify factors that may precede maladjustment and mental illness.

Discovering markers of healthy aging: a prospective study in a Danish male birth cohort.

There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, Pcorrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study.

Discovering dynamic brain networks from big data in rest and task.

Brain activity is a dynamic combination of the responses to sensory inputs and its own spontaneous processing. Consequently, such brain activity is continuously changing whether or not one is focusing on an externally imposed task. Previously, we have introduced an analysis method that allows us, using Hidden Markov Models (HMM), to model task or rest brain activity as a dynamic sequence of distinct brain networks, overcoming many of the limitations posed by sliding window approaches. Here, we present an advance that enables the HMM to handle very large amounts of data, making possible the inference of very reproducible and interpretable dynamic brain networks in a range of different datasets, including task, rest, MEG and fMRI, with potentially thousands of subjects. We anticipate that the generation of large and publicly available datasets from initiatives such as the Human Connectome Project and UK Biobank, in combination with computational methods that can work at this scale, will bring a breakthrough in our understanding of brain function in both health and disease.

Preliminary assessment of the potential for, and limitations to, terrestrial negative emission technologies in the UK.

The aggregate technical potential for land-based negative emissions technologies (NETs) in the UK is estimated to be 12-49 Mt C eq. per year, representing around 8-32% of current emissions. The proportion of this potential that could be realized is limited by a number of cost, energy and environmental constraints which vary greatly between NETs.

A common brain network links development, aging, and vulnerability to disease.

Several theories link processes of development and aging in humans. In neuroscience, one model posits for instance that healthy age-related brain degeneration mirrors development, with the areas of the brain thought to develop later also degenerating earlier. However, intrinsic evidence for such a link between healthy aging and development in brain structure remains elusive. Here, we show that a data-driven analysis of brain structural variation across 484 healthy participants (8-85 y) reveals a largely--but not only--transmodal network whose lifespan pattern of age-related change intrinsically supports this model of mirroring development and aging. We further demonstrate that this network of brain regions, which develops relatively late during adolescence and shows accelerated degeneration in old age compared with the rest of the brain, characterizes areas of heightened vulnerability to unhealthy developmental and aging processes, as exemplified by schizophrenia and Alzheimer's disease, respectively. Specifically, this network, while derived solely from healthy subjects, spatially recapitulates the pattern of brain abnormalities observed in both schizophrenia and Alzheimer's disease. This network is further associated in our large-scale healthy population with intellectual ability and episodic memory, whose impairment contributes to key symptoms of schizophrenia and Alzheimer's disease. Taken together, our results suggest that the common spatial pattern of abnormalities observed in these two disorders, which emerge at opposite ends of the life spectrum, might be influenced by the timing of their separate and distinct pathological processes in disrupting healthy cerebral development and aging, respectively.

Using public relations strategies to prompt populations at risk to seek health information: the Hanford Community Health Project.

The Hanford Community Health Project (HCHP) addressed health concerns among "downwinders" exposed to releases of radioactive iodine (I-131) from the Hanford Nuclear Reservation in the 1940s and 1950s. After developing educational materials and conducting initial outreach, HCHP had to decide whether to apply its limited resources to an advertising or public relations approach. The decision to apply public relations strategies was effective in driving awareness of the risk communication message at the community level, reinvigorating the affected community, and ultimately increasing the number of people who sought information about their risk of exposure and related health issues. HCHP used a series of communication tools to reach out to local and regional media, medical and health professionals, and community organizations. The campaign was successful in increasing the number of unique visitors to HCHP Web site and educating and activating the medical community around the releases of I-131 and patient care choices.

Brain atrophy assessment in multiple sclerosis: importance and limitations.

The use of MR imaging-derived methods to provide sensitive and reproducible assessments of brain volume (eg, to estimate atrophy) has increased the interest in this measure as a reliable indicator of disease progression in many neurologic disorders, including multiple sclerosis (MS). After an overview of the most commonly used methods for assessing brain atrophy state and changes in MS, this article discusses the clinical relevance of the most recent developments and reflects on its interpretation in a complex disease such as MS. Some caveats of these measurements are considered and possible future approaches discussed for improving the potential of this measure in assessing and monitoring pathologic evolution and treatment efficacy in this disease.

Influence of noninvasive peripheral arterial blood pressure measurements on assessment of dynamic cerebral autoregulation.

Assessment of dynamic cerebral autoregulation (CA) requires continuous recording of arterial blood pressure (ABP). In humans, noninvasive ABP recordings with the Finapres device have often been used for this purpose. We compared estimates of dynamic CA derived from Finapres with those from invasive recordings in the aorta. Measurements of finger noninvasive ABP (Finapres), intra-aortic ABP (Millar catheter), surface ECG, transcutaneous CO2, and bilateral cerebral blood flow velocity (CBFV) in the middle cerebral arteries were simultaneously and continuously recorded in 27 patients scheduled for percutaneous coronary interventions. Phase, gain, coherence, and CBFV step response from both the Finapres and intra-arterial catheter were estimated by transfer function analysis. A dynamic autoregulation index (ARI) was also calculated. For both hemispheres, the ARI index and the CBFV step response recovery at 4 s were significantly greater for the Finapres-derived estimates than for the values obtained from aortic pressure. The transfer function gain for frequencies <0.1 Hz was significantly smaller for the Finapres estimates. The phase frequency response was significantly greater for the Finapres estimates at frequencies >0.1 Hz, but not at lower frequencies. The Finapres gives higher values for the efficiency of dynamic CA compared with values derived from aortic pressure measurements, as indicated by biases in the ARI index, CBFV step response, gain, and phase. Despite the significance of these biases, their relatively small amplitude indicates a good level of agreement between indexes of CA derived from the Finapres compared with corresponding estimates obtained from invasive measurements of aortic ABP.

West Virginia Medical Institute: the Quality Improvement Organization for West Virginia.

The Federal Quality Improvement program, (QIO), charged with quality improvement and some case review activities is conducted under a contract with the Centers for Medicare and Medicaid Services (formerly HCFA), now CMS. Every state has one organization which handles this program and in West Virginia, the West Virginia Medical Institute has been responsible for this work for over 30 years. When case review is involved, the conclusions are communicated to individual physicians and hospitals. Occasionally, serious quality of care concerns are encountered. This article explains the case review process and why cases are selected, and also makes suggestions about how individual physicians may appeal or respond. It is designed to help enhance understanding of the program and its goals.

Pre-exposure chemoprophylaxis for HIV: it is time.

The HIV-1 plague continues unabatedly across sub-Saharan Africa. In Botswana and Swaziland, nearly 40% of the entire adult population is already infected. No current program is capable of slowing the advancing tide. An effective vaccine and widespread treatment are years, if not, decades away. In this most urgent situation, I propose that pre-exposure chemoprophylaxis be studied as a means to reduce the spread of HIV-1 among at-risk individuals.

HIV CTL escape: at what cost?

Recent data have established the HIV-1 and SIV escape CTL through epitope mutation. However, three novel studies prove that such escape comes at a "cost" to overall viral fitness. Understanding how HIV-1/SIV escape CTL and the impact of the escape mutations has tremendous importance in developing CTL based vaccines. Further, a CTL based HIV-1 vaccine is likely to have long-term protective effect against disease only if the escape virus is significantly weakened compared with wild type.

Multilevel linear modelling for FMRI group analysis using Bayesian inference.

Functional magnetic resonance imaging studies often involve the acquisition of data from multiple sessions and/or multiple subjects. A hierarchical approach can be taken to modelling such data with a general linear model (GLM) at each level of the hierarchy introducing different random effects variance components. Inferring on these models is nontrivial with frequentist solutions being unavailable. A solution is to use a Bayesian framework. One important ingredient in this is the choice of prior on the variance components and top-level regression parameters. Due to the typically small numbers of sessions or subjects in neuroimaging, the choice of prior is critical. To alleviate this problem, we introduce to neuroimage modelling the approach of reference priors, which drives the choice of prior such that it is noninformative in an information-theoretic sense. We propose two inference techniques at the top level for multilevel hierarchies (a fast approach and a slower more accurate approach). We also demonstrate that we can infer on the top level of multilevel hierarchies by inferring on the levels of the hierarchy separately and passing summary statistics of a noncentral multivariate t distribution between them.

Constrained linear basis sets for HRF modelling using Variational Bayes.

FMRI modelling requires flexible haemodynamic response function (HRF) modelling, with the HRF being allowed to vary spatially and between subjects. To achieve this flexibility, voxelwise parameterised HRFs have been proposed; however, inference on such models is very slow. An alternative approach is to use basis functions allowing inference to proceed in the more manageable General Linear Model (GLM) framework. However, a large amount of the subspace spanned by the basis functions produces nonsensical HRF shapes. In this work we propose a technique for choosing a basis set, and then the means to constrain the subspace spanned by the basis set to only include sensible HRF shapes. Penny et al. showed how Variational Bayes can be used to infer on the GLM for FMRI. Here we extend the work of Penny et al. to give inference on the GLM with constrained HRF basis functions and with spatial Markov Random Fields on the autoregressive noise parameters. Constraining the subspace spanned by the basis set allows for far superior separation of activating voxels from nonactivating voxels in FMRI data. We use spatial mixture modelling to produce final probabilities of activation and demonstrate increased sensitivity on an FMRI dataset.