Elucidating vaccine efficacy using a correlate of protection, demographics, and logistic regression.

BACKGROUND: Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. Understanding the effect of covariates on efficacy is key to decisions by vaccine developers and public health authorities. METHODS: This work evaluates the impact of including correlate of protection (CoP) data in logistic regression on its performance in identifying statistically and clinically significant covariates in settings typical for a vaccine phase 3 trial. The proposed approach uses CoP data and covariate data as predictors of clinical outcome (diseased versus non-diseased) and is compared to logistic regression (without CoP data) to relate vaccination status and covariate data to clinical outcome. RESULTS: Clinical trial simulations, in which the true relationship between CoP data and clinical outcome probability is a sigmoid function, show that use of CoP data increases the positive predictive value for detection of a covariate effect. If the true relationship is characterized by a decreasing convex function, use of CoP data does not substantially change positive or negative predictive value. In either scenario, vaccine efficacy is estimated more precisely (i.e., confidence intervals are narrower) in covariate-defined subgroups if CoP data are used, implying that using CoP data increases the ability to determine clinical significance of baseline covariate effects on efficacy. CONCLUSIONS: This study proposes and evaluates a novel approach for assessing baseline demographic covariates potentially affecting VE. Results show that the proposed approach can sensitively and specifically identify potentially important covariates and provides a method for evaluating their likely clinical significance in terms of predicted impact on vaccine efficacy. It shows further that inclusion of CoP data can enable more precise VE estimation, thus enhancing study power and/or efficiency and providing even better information to support health policy and development decisions.

Savings in CT Net Scan Energy Consumption: Assessment Using Dose Report Metrics and Comparison With Savings in Idle State Energy Consumption.

BACKGROUND. CT scanners' net scan state (i.e., image acquisition period) represents a potential target for energy savings through protocol adjustments. However, gauging CT energy savings is difficult without installing costly energy monitors. OBJECTIVE. The purpose of this article was to assess correlations between CT dose report metrics and energy consumption during the system net scan state and to compare theoretic energy savings from matching percentage reductions in energy consumption during net scan and idle system states. METHODS. Current sensors were installed on a single CT scanner. A phantom was scanned at varying kilovoltage settings and effective tube current-rotation time settings. A retrospective assessment was performed in 32 patients (mean age, 61.2 ± 17.9 [SD] years; 17 men, 15 women) who underwent 32 single-energy noncontrast abdominopelvic CT examinations from September 22, 2021, to September 27, 2021, on the same scanner. Correlations between dose report metrics and net scan energy consumption were assessed in the phantom and clinical scans, and equations were generated to derive net scan energy consumption from DLP. An additional retrospective assessment was performed in 1355 patients (mean age, 59.3 ± 16.9 years; 663 men, 692 women) who underwent 1728 single-energy noncontrast abdominopelvic CT examinations from January 1, 2021, through December 31, 2021, on the same scanner to estimate net scan energy consumption per examination. This information was integrated with literature-derived values to compare estimated annual national energy savings resulting from 20% reductions in net scan and idle state energy consumption. RESULTS. Net scan energy consumption in the phantom scans showed high linear correlation with DLP (R2 = 0.87), and, in the clinical scans, high linear correlation with CTDIvol (R2 = 0.89) and very high linear correlation with DLP (R2 = 0.92). When combining mean DLP in examinations performed in the 1-year interval, an equation relating DLP and net scan energy consumption and literature values estimated that annual national energy savings was 14.9 times greater (40,437,870 kWh/2,704,000 kWh) by targeting the idle state rather than net scan state. CONCLUSION. CT net scan energy savings can be inferred from reductions in dose report metrics. However, targeting net scan energy consumption has modest impact relative to targeting idle state energy consumption. CLINICAL IMPACT. Environmental sustainability efforts should target the idle state energy consumption of CT.

RadioGraphics Update: Parathyroid CT and Primary Hyperparathyroidism.

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Projecting hospital utilization during the COVID-19 outbreaks in the United States.

In the wake of community coronavirus disease 2019 (COVID-19) transmission in the United States, there is a growing public health concern regarding the adequacy of resources to treat infected cases. Hospital beds, intensive care units (ICUs), and ventilators are vital for the treatment of patients with severe illness. To project the timing of the outbreak peak and the number of ICU beds required at peak, we simulated a COVID-19 outbreak parameterized with the US population demographics. In scenario analyses, we varied the delay from symptom onset to self-isolation, the proportion of symptomatic individuals practicing self-isolation, and the basic reproduction number R0 Without self-isolation, when R0 = 2.5, treatment of critically ill individuals at the outbreak peak would require 3.8 times more ICU beds than exist in the United States. Self-isolation by 20% of cases 24 h after symptom onset would delay and flatten the outbreak trajectory, reducing the number of ICU beds needed at the peak by 48.4% (interquartile range 46.4-50.3%), although still exceeding existing capacity. When R0 = 2, twice as many ICU beds would be required at the peak of outbreak in the absence of self-isolation. In this scenario, the proportional impact of self-isolation within 24 h on reducing the peak number of ICU beds is substantially higher at 73.5% (interquartile range 71.4-75.3%). Our estimates underscore the inadequacy of critical care capacity to handle the burgeoning outbreak. Policies that encourage self-isolation, such as paid sick leave, may delay the epidemic peak, giving a window of time that could facilitate emergency mobilization to expand hospital capacity.

From complex data to biological insight: 'DEKER' feature selection and network inference.

Network inference is a valuable approach for gaining mechanistic insight from high-dimensional biological data. Existing methods for network inference focus on ranking all possible relations (edges) among all measured quantities such as genes, proteins, metabolites (features) observed, which yields a dense network that is challenging to interpret. Identifying a sparse, interpretable network using these methods thus requires an error-prone thresholding step which compromises their performance. In this article we propose a new method, DEKER-NET, that addresses this limitation by directly identifying a sparse, interpretable network without thresholding, improving real-world performance. DEKER-NET uses a novel machine learning method for feature selection in an iterative framework for network inference. DEKER-NET is extremely flexible, handling linear and nonlinear relations while making no assumptions about the underlying distribution of data, and is suitable for categorical or continuous variables. We test our method on the Dialogue for Reverse Engineering Assessments and Methods (DREAM) challenge data, demonstrating that it can directly identify sparse, interpretable networks without thresholding while maintaining performance comparable to the hypothetical best-case thresholded network of other methods.

The Global Diet Quality Score Is Inversely Associated with Nutrient Inadequacy, Low Midupper Arm Circumference, and Anemia in Rural Adults in Ten Sub-Saharan African Countries.

BACKGROUND: Key nutrient deficits remain widespread throughout sub-Saharan Africa (SSA) whereas noncommunicable diseases (NCDs) now cause one-third of deaths. Easy-to-use metrics are needed to track contributions of diet quality to this double burden. OBJECTIVES: We evaluated comparative performance of a novel food-based Global Diet Quality Score (GDQS) against other diet metrics in capturing nutrient adequacy and undernutrition in rural SSA adults. METHODS: We scored the GDQS, Minimum Dietary Diversity-Women (MDD-W), and Alternative Healthy Eating Index-2010 (AHEI-2010) using FFQ data from rural men and nonpregnant, nonlactating women of reproductive age (15-49 y) in 10 SSA countries. We evaluated Spearman correlations between metrics and energy-adjusted nutrient intakes, and age-adjusted associations with BMI, midupper arm circumference (MUAC), and hemoglobin in regression models. RESULTS: Correlations between the GDQS and an energy-adjusted aggregate measure of dietary protein, fiber, calcium, iron, zinc, vitamin A, folate, and vitamin B-12 adequacy were 0.34 (95% CI: 0.30, 0.38) in men and 0.37 (95% CI: 0.32, 0.41) in women. The GDQS was associated (P < 0.05) with lower odds of low MUAC [GDQS quintile (Q) 5 compared with Q1 OR in men: 0.44, 95% CI: 0.22, 0.85; women: 0.57, 95% CI: 0.31, 1.03] and anemia (Q5/Q1 OR in men: 0.56, 95% CI: 0.32, 0.98; women: 0.60, 95% CI: 0.35, 1.01). The MDD-W correlated better with some nutrient intakes, though associated marginally with low MUAC in men (P = 0.07). The AHEI-2010 correlated better with fatty acid intakes, though associated marginally with low MUAC (P = 0.06) and anemia (P = 0.14) in women. Overweight/obesity prevalence was low, and neither the GDQS, MDD-W, nor AHEI-2010 were predictive. CONCLUSIONS: The GDQS performed comparably with the MDD-W in capturing nutrient adequacy-related outcomes in rural SSA. Given limited data on NCD outcomes and the cross-sectional study design, prospective studies are warranted to assess GDQS performance in capturing NCD outcomes in SSA.

Accuracy of 190-keV Virtual Monoenergetic Dual-Energy CT for Determining the Presence or Absence of Intravitreal Silicone Oil.

OBJECTIVE. We hypothesized that intravitreal silicone oil would show attenuation similar to that of fat on dual-energy CT 190-keV virtual monoenergetic images (VMIs) with high frequency and that this appearance would enable confident determination of the presence or absence of intravitreal silicone oil. The purpose of the present study was to test our hypothesis in a blinded multireader study of selected patients with and without intravitreal silicone oil as well as in an unblinded ROI-based assessment. MATERIALS AND METHODS. In this retrospective study of 50 dual-energy CT examinations of the head that included 100 globes (64 that were normal, 19 that exhibited hyperattenuating mimics, and 17 that contained silicone oil), three neuroradiologists independently assessed anonymized 190-keV VMIs for intravitreal attenuation similar to that of fat. Interobserver agreement was calculated. The mean attenuation value on weighted-average images and 190-keV VMIs was recorded. RESULTS. The three readers identified intravitreal attenuation values similar to that of fat in 100% of globes that contained silicone oil and 0% of globes that did not contain silicone oil (100% sensitivity, specificity, PPV, and accuracy) with 100% agreement. The mean attenuation value of silicone oil on 190-keV VMIs was -55 HU, which was significantly less than the mean attenuation on 190-keV VMIs of normal globes and hyperattenuating mimics (p < .001 for both). CONCLUSION. Intravitreal silicone oil shows attenuation of -60 to -49 HU on 190-keV VMIs. With the use of these images only, three neuroradiologists identified intravitreal silicone oil with 100% accuracy and perfect agreement.

The Prevalence of Internal Auditory Canal Diverticula Is Constant Over a Large Age Range Among Patients Not Imaged for Hearing Loss.

OBJECTIVE: The objective of this study is to establish the prevalence of internal auditory canal diverticula spanning all age groups imaged for reasons other than hearing loss and to investigate changes in prevalence with age to determine if it is a finding that develops over time. METHODS: We retrospectively evaluated 1000 cervical spine computed tomographies obtained in patients age 0-99 years for presence of internal auditory canal diverticula. RESULTS: A total of 405 patients (208 men; 197 women) were included. Internal auditory canal diverticula were identified in 23 patients (5.7%). No statistically significant association between internal auditory canal diverticula and patient age was found (P = 0.68). CONCLUSIONS: The prevalence of internal auditory canal diverticula on cervical spine computed tomographies is 5.7%. No change in prevalence was observed with increasing age supporting the hypothesis that internal auditory canal diverticula represent a normal anatomic variant rather than acquired pathology.

Unique Characteristics of Intravitreal Silicone Oil on Dual-Energy Computed Tomography.

Silicone oil is used as an intravitreal injection to treat retinal detachment. This material can spread into the subarachnoid space, where it may be mistaken for acute hemorrhage on single-energy computed tomography. This report describes the appearance of intravitreal silicone oil on dual-energy computed tomography, emphasizing unique virtual monoenergetic imaging characteristics that allow for confident differentiation of silicone oil from hemorrhage as well as from other potential single-energy mimics, such as calcium and iodine.

Agriculture, Aid, and Economic Growth in Africa.

How can foreign aid to agriculture support economic growth in Africa? This paper constructs a geographically indexed applied general equilibrium model that considers pathways through which aid might affect growth and structural transformation of labor markets in the context of soil nutrient variation, minimum subsistence consumption requirements, domestic transport costs, labor mobility, and constraints to self-financing of agricultural inputs.Using plausible parameters, the model is presented for Uganda as an illustrative case.We present three stylized scenarios to demonstrate the potential economy-wide impacts of both soil nutrient loss and replenishment, and how foreign aid can be targeted to support agricultural inputs that boost rural productivity and shift labor to boost real wages. One simulation shows how a temporary program of targeted official development assistance (ODA) for agriculture could generate, contrary to traditional Dutch disease concerns, an expansion in the primary tradable sector and positive permanent productivity and welfare effects, leading to a steady decline in the need for complementary ODA for budget support.

Orbital Interstitial Fluid: Evidence of a Potential Pathway for Extracranial Cerebrospinal Fluid Absorption.

BACKGROUND AND PURPOSE: The aim of the study was to describe the prevalence and characteristics of orbital interstitial fluid seen on magnetic resonance (MR) images of infants and young children. MATERIALS AND METHODS: Fat-suppressed axial T2-weighted MR images of 100 consecutive infants and young children (<6 years) without orbital pathology were retrospectively reviewed by 2 neuroradiologists. The presence, location, and extent of high-signal orbital interstitial fluid were characterized and tabulated as a function of age. RESULTS: Orbital interstitial fluid was detected in 90 (90%) of the 100 subjects overall, present in 100% (75/75) of infants and children younger than 3 years, 75% (12/16) of those aged 3 to 5 years, and 33% (3/9) of those aged 5 to 6 years. The fluid was bilateral and symmetric in all cases. Two morphologic patterns were distinguished, which often co-existed: (1) a focal discrete curvilinear band of fluid in the posterior-lateral orbit, more common in younger patients, and (2) an ill-defined, lace-like pattern primarily in the superior orbit seen in subjects of all ages. CONCLUSIONS: Orbital interstitial fluid as detected by fat-suppressed T2-weighted MR imaging is a nearly universal finding in infants and young children and should not be considered pathologic. It may have either a focal or lace-like pattern or both. Orbital interstitial fluid decreases in size and prevalence as a function of age but is still present in nearly half of children aged 4 to 6 years. Possible explanations concerning the nature and origin of this fluid are presented, including the fascinating possibility that the fluid represents an extracranial pathway for outflow of cerebrospinal fluid.

How to Incorporate Dual-Energy Computed Tomography Into Your Neuroradiology Practice: Questions and Answers.

Dual-energy computed tomography (DECT) has many current and evolving applications in neuroradiology including material decomposition, improving conspicuity of iodinated contrast enhancement, and artifact reduction. However, there are multiple challenges in incorporating DECT into practice including hardware selection, postprocessing software requirements, technologist and physician training, and numerous workflow issues. This article reviews in a question-and-answer format common issues that arise when incorporating DECT into a busy neuroradiology practice.