Gastrointestinal Acute Radiation Syndrome: Mechanisms, Models, Markers, and Medical Countermeasures.

There have been a number of reported human exposures to high dose radiation, resulting from accidents at nuclear power plants (e.g., Chernobyl), atomic bombings (Hiroshima and Nagasaki), and mishaps in industrial and medical settings. If absorbed radiation doses are high enough, evolution of acute radiation syndromes (ARS) will likely impact both the bone marrow as well as the gastrointestinal (GI) tract. Damage incurred in the latter can lead to nutrient malabsorption, dehydration, electrolyte imbalance, altered microbiome and metabolites, and impaired barrier function, which can lead to septicemia and death. To prepare for a medical response should such an incident arise, the National Institute of Allergy and Infectious Diseases (NIAID) funds basic and translational research to address radiation-induced GI-ARS, which remains a critical and prioritized unmet need. Areas of interest include identification of targets for damage and mitigation, animal model development, and testing of medical countermeasures (MCMs) to address GI complications resulting from radiation exposure. To appropriately model expected human responses, it is helpful to study analogous disease states in the clinic that resemble GI-ARS, to inform on best practices for diagnosis and treatment, and translate them back to inform nonclinical drug efficacy models. For these reasons, the NIAID partnered with two other U.S. government agencies (the Biomedical Advanced Research and Development Authority, and the Food and Drug Administration), to explore models, biomarkers, and diagnostics to improve understanding of the complexities of GI-ARS and investigate promising treatment approaches. A two-day workshop was convened in August 2022 that comprised presentations from academia, industry, healthcare, and government, and highlighted talks from 26 subject matter experts across five scientific sessions. This report provides an overview of information that was presented during the conference, and important discussions surrounding a broad range of topics that are critical for the research, development, licensure, and use of MCMs for GI-ARS.

Unbiased review of digital diagnostic images in practice: informatics prototype and pilot study.

RATIONALE AND OBJECTIVES: Clinical and contextual information associated with images may influence how radiologists draw diagnostic inferences, highlighting the need to control multiple sources of bias in the methodologic design of investigations involving radiologic interpretation. In the past, manual control methods to mask review films presented in practice have been used to reduce potential interpretive bias associated with differences between viewing images for patient care and reviewing images for the purposes of research, education, and quality improvement. These manual precedents from the film era raise the question whether similar methods to reduce bias can be implemented in the modern digital environment. MATERIALS AND METHODS: A prototype application, CreateAPatient, was built for masking review case presentations within one institution's production radiology information system and picture archiving and communication system. To test whether CreateAPatient could be used to mask review images presented in practice, six board-certified radiologists participated in a pilot study. During pilot testing, seven digital chest radiographs, known to contain lung nodules and associated with fictitious patient identifiers, were mixed into the routine workloads of the participating radiologists while they covered general evening call shifts. The aim was to test whether it was possible to mask the presentation of these review cases, both by probing the interpreting radiologists to report detection and by conducting a forced-choice experiment on a separate cohort of 20 radiologists and information technology professionals. RESULTS: None of the participating radiologists reported awareness of review activity, and forced-choice detection was less than predicted at chance, suggesting that radiologists were effectively blinded. In addition, no evidence was identified of review reports unsafely propagating beyond their intended scope or otherwise interfering with patient care, despite integration of these records within production electronic work flow systems. CONCLUSIONS: Information technology can facilitate the design of unbiased methods involving professional review of digital diagnostic images.

Open access series of imaging studies: longitudinal MRI data in nondemented and demented older adults.

The Open Access Series of Imaging Studies is a series of neuroimaging data sets that are publicly available for study and analysis. The present MRI data set consists of a longitudinal collection of 150 subjects aged 60 to 96 years all acquired on the same scanner using identical sequences. Each subject was scanned on two or more visits, separated by at least 1 year for a total of 373 imaging sessions. Subjects were characterized using the Clinical Dementia Rating (CDR) as either nondemented or with very mild to mild Alzheimer's disease. Seventy-two of the subjects were characterized as nondemented throughout the study. Sixty-four of the included subjects were characterized as demented at the time of their initial visits and remained so for subsequent scans, including 51 individuals with CDR 0.5 similar level of impairment to individuals elsewhere considered to have "mild cognitive impairment." Another 14 subjects were characterized as nondemented at the time of their initial visit (CDR 0) and were subsequently characterized as demented at a later visit (CDR > 0). The subjects were all right-handed and include both men (n = 62) and women (n = 88). For each scanning session, three or four individual T1-weighted MRI scans were obtained. Multiple within-session acquisitions provide extremely high contrast to noise, making the data amenable to a wide range of analytic approaches including automated computational analysis. Automated calculation of whole-brain volume is presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.

Brain volume decline in aging: evidence for a relation between socioeconomic status, preclinical Alzheimer disease, and reserve.

OBJECTIVES: To assess the relation between socioeconomic status (SES) and structural brain change in nondemented older adults and to ascertain the potential role of preclinical Alzheimer disease (AD). DESIGN: Cross-sectional and longitudinal observation. SETTING: Alzheimer's Disease Research Center, St Louis, Missouri. PARTICIPANTS: Volunteer sample of 362 nondemented adults aged 18 to 93 years. The main cohort of 100 was evaluated for dementia and SES; a Clinical Dementia Rating (CDR) of 0 (no dementia) and middle, high-middle, or high SES was required for eligibility. All 362 received magnetic resonance imaging; of the main 100, 91 received follow-up clinical assessment, and 33 received follow-up magnetic resonance imaging over at least a 3-year interval. A separate sample of 58 CDR 0 participants (aged 47 to 86 years) took part in amyloid imaging with Pittsburgh Compound B (PiB) labeled with radioactive carbon ((11)C). MAIN OUTCOME MEASURES: Whole-brain volume adjusted for head size (aWBV) and change per year. RESULTS: aWBV declined by 0.22% per year between the ages of 20 and 80 years with accelerated decline in advanced aging. Controlling for effects of age and sex in older adults (>65 years) with CDR 0, higher SES was associated with smaller aWBV (3.8% difference spanning the sample range from middle to high privilege, P< .01) and more rapid volume loss (0.39% per year to 0.68% per year from middle to high privilege, P< .05). aWBV was reduced by 2.5% in individuals positive for PiB binding (n=9) as compared with individuals negative for PiB binding (n=49, P< .05), supporting an influence of undetected preclinical AD. Follow-up clinical data revealed that brain volume reduction associated with SES was greater in those who later developed very mild dementia (preclinical CDR 0 group, n=19) compared with those who remained nondemented (stable CDR 0 group, n=64; group x SES interaction, P< .05). CONCLUSIONS: Privileged nondemented older adults harbor more preclinical brain atrophy, consistent with their having greater reserve against the expression of AD.

White matter lesions are prevalent but differentially related with cognition in aging and early Alzheimer disease.

BACKGROUND: White matter lesions (WMLs) are prevalent in nondemented aging and in Alzheimer disease (AD). Their relationship with cognition in the earliest stages of AD is unknown. OBJECTIVE: To assess the relationship between WMLs and cognition in nondemented aging and in early-stage AD. DESIGN: Cross-sectional study. SETTING: Alzheimer Disease Research Center, St Louis, MO. PARTICIPANTS: Participants were nondemented (n = 88) or had very mild (n = 48) or mild (n = 20) AD. MAIN OUTCOME MEASURES: Regression coefficients for deep WMLs and periventricular WMLs (PVWMLs) as predictors of cognition, after controlling for age, educational achievement, brain atrophy, and infarctlike lesions. RESULTS: White matter lesions were present in nondemented aging and in early-stage AD, with no group differences in deep WML burden and a modest PVWML burden increase in the AD group. The prevalence of infarctlike lesions was equivalent between groups. Age and hypertension were related to deep WML burden and PVWML burden. Deep WML burden and PVWML burden were associated with reduced global cognition in AD but not in nondemented aging. A PVWML x AD status interaction for global cognition suggests that the relationship between PVWMLs and cognition is modified by AD. In AD, global cognitive reductions were related to impairments in visual memory, processing speed, and executive function. CONCLUSIONS: White matter lesions are prevalent in nondemented aging and in early-stage AD, and their presence influences cognitive impairment in the earliest stages of AD. Individuals with early-stage AD may be more vulnerable to the cognitive effect of WMLs than nondemented aging individuals with similar WML burden.

Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory.

Alzheimer's disease (AD) and antecedent factors associated with AD were explored using amyloid imaging and unbiased measures of longitudinal atrophy in combination with reanalysis of previous metabolic and functional studies. In total, data from 764 participants were compared across five in vivo imaging methods. Convergence of effects was seen in posterior cortical regions, including posterior cingulate, retrosplenial, and lateral parietal cortex. These regions were active in default states in young adults and also showed amyloid deposition in older adults with AD. At early stages of AD progression, prominent atrophy and metabolic abnormalities emerged in these posterior cortical regions; atrophy in medial temporal regions was also observed. Event-related functional magnetic resonance imaging studies further revealed that these cortical regions are active during successful memory retrieval in young adults. One possibility is that lifetime cerebral metabolism associated with regionally specific default activity predisposes cortical regions to AD-related changes, including amyloid deposition, metabolic disruption, and atrophy. These cortical regions may be part of a network with the medial temporal lobe whose disruption contributes to memory impairment.

A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume.

Atlas normalization, as commonly used by functional data analysis, provides an automated solution to the widely encountered problem of correcting for head size variation in regional and whole-brain morphometric analyses, so long as an age- and population-appropriate target atlas is used. In the present article, we develop and validate an atlas normalization procedure for head size correction using manual total intracranial volume (TIV) measurement as a reference. The target image used for atlas transformation consisted of a merged young and old-adult template specifically created for cross age-span normalization. Automated atlas transformation generated the Atlas Scaling Factor (ASF) defined as the volume-scaling factor required to match each individual to the atlas target. Because atlas normalization equates head size, the ASF should be proportional to TIV. A validation analysis was performed on 147 subjects to evaluate ASF as a proxy for manual TIV measurement. In addition, 19 subjects were imaged on multiple days to assess test-retest reliability. Results indicated that the ASF was (1) equivalent to manual TIV normalization (r = 0.93), (2) reliable across multiple imaging sessions (r = 1.00; mean absolute percentage of difference = 0.51%), (3) able to connect between-gender head size differences, and (4) minimally biased in demented older adults with marked atrophy. Hippocampal volume differences between nondemented (n = 49) and demented (n = 50) older adults (measured manually) were equivalent whether corrected using manual TIV or automated ASF (effect sizes of 1.29 and 1.46, respectively). To provide normative values, ASF was used to automatically derive estimated TIV (eTIV) in 335 subjects aged 15-96 including both clinically characterized nondemented (n = 77) and demented (n = 90) older adults. Differences in eTIV between nondemented and demented groups were negligible, thus failing to support the hypothesis that large premorbid brain size moderates Alzheimer's disease. Gender was the only robust factor that influenced eTIV. Men showed an approximately approximately 12% larger eTIV than women. These results demonstrate that atlas normalization using appropriate template images provides a robust, automated method for head size correction that is equivalent to manual TIV correction in studies of aging and dementia. Thus, atlas normalization provides a common framework for both morphometric and functional data analysis.