Geometric Validation of Continuous, Finely Sampled 3-D Reconstructions From aOCT and CT in Upper Airway Models

Identification and treatment of obstructive airway disorders (OADs) are greatly aided by imaging of the geometry of the airway lumen. Anatomical optical coherence tomography (aOCT) is a promising high-speed and minimally invasive endoscopic imaging modality for providing micrometer-resolution scans of the upper airway. Resistance to airflow in OADs is directly caused by the reduction in luminal cross-sectional area (CSA). It is hypothesized that aOCT can produce airway CSA measurements as accurate as that from computed tomography (CT). Scans of machine hollowed cylindrical tubes were used to develop methods for segmentation and measurement of airway lumen in CT and aOCT. Simulated scans of virtual cones were used to validate 3-D resampling and reconstruction methods in aOCT. Then, measurements of two segments of a 3-D printed pediatric airway phantom from aOCT and CT independently were compared to ground truth CSA. In continuous unobstructed regions, the mean CSA difference for each phantom segment was 2.2 ± 3.5 and 1.5 ± 5.3 mm2 for aOCT, and -3.4 ± 4.3 and -1.9 ± 1.2 mm2 for CT. Because of the similar magnitude of these differences, these results support the hypotheses and underscore the potential for aOCT as a viable alternative to CT in airway imaging, while offering greater potential to capture respiratory dynamics

Finite-time fluctuations in the degree statistics of growing networks

This paper presents a comprehensive analysis of the degree statistics in models for growing networks where new nodes enter one at a time and attach to one earlier node according to a stochastic rule. The models with uniform attachment, linear attachment (the Barab\'asi-Albert model), and generalized preferential attachment with initial attractiveness are successively considered. The main emphasis is on finite-size (i.e., finite-time) effects, which are shown to exhibit different behaviors in three regimes of the size-degree plane: stationary, finite-size scaling, large deviations.Comment: 33 pages, 7 figures, 1 tabl

Localized compliance measurement of the airway wall using anatomic optical coherence elastography

We describe an elastographic method to circumferentially-resolve airway wall compliance using endoscopic, anatomic optical coherence tomography (aOCT) combined with an intraluminal pressure catheter. The method was first demonstrated on notched silicone phantoms of known elastic modulus under respiratory ventilation, where localized compliance measurements were validated against those predicted by finite element modeling. Then, ex vivo porcine tracheas were scanned, and the pattern of compliance was found to be consistent with histological identification of the locations of (stiff) cartilage and (soft) muscle. This quantitative method may aid in diagnosis and monitoring of collapsible airway wall tissues in obstructive respiratory disorders

Combined anatomical optical coherence tomography and intraluminal pressure reveal viscoelasticity of the in vivo airway

It is hypothesized that the local, viscoelastic (time-dependent) properties of the airway are important to accurately model and ultimately predict dynamic airway collapse in airway obstruction. Toward this end, we present a portable, endoscopic, swept-source anatomical optical coherence tomography (aOCT) system combined with a pressure catheter to capture local airway dynamics in vivo during respiration. aOCT scans were performed in the airways of a mechanically ventilated pig under paralysis with dynamic and static ventilation protocols. Validation of dynamic aOCT luminal cross-sectional area (CSA) measurements against Cine CT, obtained during the same exam, showed an aggregate difference of 15 % ± 3 %. aOCT-derived CSA obtained in the in vivo trachea also exhibited hysteresis as a function of pressure, depicting the viscoelastic nature of the airway wall. The volumetric imaging capabilities were validated by comparing aOCT- and CT-derived geometries of the porcine airway spanning nine generations from the trachea to the bronchioles. The ability to delineate regional differences in airway viscoelastic properties, by measuring airway deformation using aOCT combined with intraluminal pressure, paves the way to patient-specific models of dynamic airway collapse

Sensing Inhalation Injury-Associated Changes in Airway Wall Compliance by Anatomic Optical Coherence Elastography

Quantitative methods for assessing the severity of inhalation (burn) injury are needed to aid in treatment decisions. We hypothesize that it is possible to assess the severity of injuries on the basis of differences in the compliance of the airway wall. Here, we demonstrate the use of a custom-built, endoscopic, anatomic optical coherence elastography (aOCE) system to measure airway wall compliance. The method was first validated using airway phantoms, then performed on ex vivo porcine tracheas under varying degrees of inhalation (steam) injury. A negative correlation between aOCE-derived compliance and severity of steam injuries is found, and spatially-resolved compliance maps reveal regional heterogeneity in airway properties

The spread of epidemic disease on networks

The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. In addition to the standard but unrealistic case of fixed infectiveness time and fixed and uncorrelated probability of transmission between all pairs of individuals, we solve cases in which times and probabilities are non-uniform and correlated. We also consider one simple case of an epidemic in a structured population, that of a sexually transmitted disease in a population divided into men and women. We confirm the correctness of our exact solutions with numerical simulations of SIR epidemics on networks.Comment: 12 pages, 3 figure

LD Hub:a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

Motivation: LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. Results: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies