Particle-Tracking Microrheology Using Micro-Optical Coherence Tomography.

Clinical manifestations of cystic fibrosis (CF) result from an increase in the viscosity of the mucus secreted by epithelial cells that line the airways. Particle-tracking microrheology (PTM) is a widely accepted means of determining the viscoelastic properties of CF mucus, providing an improved understanding of this disease as well as an avenue to assess the efficacies of pharmacologic therapies aimed at decreasing mucus viscosity. Among its advantages, PTM allows the measurement of small volumes, which was recently utilized for an in situ study of CF mucus formed by airway cell cultures. Typically, particle tracks are obtained from fluorescence microscopy video images, although this limits one's ability to distinguish particles by depth in a heterogeneous environment. Here, by performing PTM with high-resolution micro-optical coherence tomography (µOCT), we were able to characterize the viscoelastic properties of mucus, which enables simultaneous measurement of rheology with mucociliary transport parameters that we previously determined using µOCT. We obtained an accurate characterization of dextran solutions and observed a statistically significant difference in the viscosities of mucus secreted by normal and CF human airway cell cultures. We further characterized the effects of noise and imaging parameters on the sensitivity of µOCT-PTM by performing theoretical and numerical analyses, which show that our system can accurately quantify viscosities over the range that is characteristic of CF mucus. As a sensitive rheometry technique that requires very small fluid quantities, µOCT-PTM could also be generally applied to interrogate the viscosity of biological media such as blood or the vitreous humor of the eye in situ.

A functional anatomic defect of the cystic fibrosis airway.

RATIONALE: The mechanisms underlying cystic fibrosis (CF) lung disease pathogenesis are unknown. OBJECTIVES: To establish mechanisms linking anion transport with the functional microanatomy, we evaluated normal and CF piglet trachea as well as adult swine trachea in the presence of selective anion inhibitors. METHODS: We investigated airway functional microanatomy using microoptical coherence tomography, a new imaging modality that concurrently quantifies multiple functional parameters of airway epithelium in a colocalized fashion. MEASUREMENTS AND MAIN RESULTS: Tracheal explants from wild-type swine demonstrated a direct link between periciliary liquid (PCL) hydration and mucociliary transport (MCT) rates, a relationship frequently invoked but never experimentally confirmed. However, in CF airways this relationship was completely disrupted, with greater PCL depths associated with slowest transport rates. This disrupted relationship was recapitulated by selectively inhibiting bicarbonate transport in vitro and ex vivo. CF mucus exhibited increased viscosity in situ due to the absence of bicarbonate transport, explaining defective MCT that occurs even in the presence of adequate PCL hydration. CONCLUSIONS: An inherent defect in CF airway surface liquid contributes to delayed MCT beyond that caused by airway dehydration alone and identifies a fundamental mechanism underlying the pathogenesis of CF lung disease in the absence of antecedent infection or inflammation.

Performance of crisis standards of care guidelines in a cohort of critically ill COVID-19 patients in the United States.

Many US states published crisis standards of care (CSC) guidelines for allocating scarce critical care resources during the COVID-19 pandemic. However, the performance of these guidelines in maximizing their population benefit has not been well tested. In 2,272 adults with COVID-19 requiring mechanical ventilation drawn from the Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID) multicenter cohort, we test the following three approaches to CSC algorithms: Sequential Organ Failure Assessment (SOFA) scores grouped into ranges, SOFA score ranges plus comorbidities, and a hypothetical approach using raw SOFA scores not grouped into ranges. We find that area under receiver operating characteristic (AUROC) curves for all three algorithms demonstrate only modest discrimination for 28-day mortality. Adding comorbidity scoring modestly improves algorithm performance over SOFA scores alone. The algorithm incorporating comorbidities has modestly worse predictive performance for Black compared to white patients. CSC algorithms should be empirically examined to refine approaches to the allocation of scarce resources during pandemics and to avoid potential exacerbation of racial inequities.

Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines.

BACKGROUND: Several states have released Crisis Standards of Care (CSC) guidelines for the allocation of scarce critical care resources. Most guidelines rely on Sequential Organ Failure Assessment (SOFA) scores to maximize lives saved, but states have adopted different stances on whether to maximize long-term outcomes (life-years saved) by accounting for patient comorbidities. METHODS: We compared 4 representative state guidelines with varying approaches to comorbidities and analyzed how CSC prioritization correlates with clinical outcomes. We included 27 laboratory-confirmed COVID-19 patients admitted to ICUs at Brigham and Women's Hospital from March 12 to April 3, 2020. We compared prioritization algorithms from New York, which assigns priority based on SOFA alone; Maryland, which uses SOFA plus severe comorbidities; Pennsylvania, which uses SOFA plus major and severe comorbidities; and Colorado, which uses SOFA plus a modified Charlson comorbidity index. RESULTS: In pairwise comparisons across all possible pairs, we found that state guidelines frequently resulted in tie-breakers based on age or lottery: New York 100% of the time (100% resolved by lottery), Pennsylvania 86% of the time (18% by lottery), Maryland 93% of the time (35% by lottery), and Colorado: 32% of the time (10% by lottery). The prioritization algorithm with the strongest correlation with 14-day outcomes was Colorado (rs = -0.483. p = 0.011) followed by Maryland (rs = -0.394, p =0.042), Pennsylvania (rs = -0.382, p = 0.049), and New York (rs = 0). An alternative model using raw SOFA scores alone was moderately correlated with outcomes (rs = -0.448, p = 0.019). CONCLUSIONS: State guidelines for scarce resource allocation frequently resulted in identical priority scores, requiring tie-breakers based on age or lottery. These findings suggest that state CSC guidelines should be further assessed empirically to understand whether they meet their goals.

Initial clinical findings of a mathematical model to predict survival of head and neck cancer.

OBJECTIVES: (1) Identify clinical features that impact survival for head and neck cancer. (2) Determine the individual contribution to mortality of significant clinical features. (3) Develop a web-based calculator to integrate clinical features and predict survival outcome for individual patients. STUDY DESIGN: Analysis of a national cancer database. We fit patient data to the binary-biological model of cancer lethality, a mathematical model designed to predict cancer outcome. The model predicts the risk of cancer death, using information on tumor size, nodal status, and other prognostic factors. SUBJECTS AND METHODS: Analysis was carried out on a cohort of ~50,000 patients with head and neck cancer from the Survey, Epidemiology and End-Results (SEER) 2009 data set and validated with a cohort of ~1300 patients from an institutional Massachusetts General Hospital/Massachusetts Eye and Ear Infirmary database. We developed a web-based calculator written in JavaScript, PHP, and HTML. RESULTS: The risk of death due to head and neck cancer increases monotonically with tumor size. Each positive lymph node is associated with ~14% extra risk of death. Anatomical site, age, race, tumor extension, N stage, and extracapsular spread contribute to mortality. The lethal impact of these prognostics factors can be accurately estimated by the Size + Nodes + PrognosticMarkers (SNAP) method. CONCLUSIONS: This predictive cancer model and web-based calculator provide a basis for estimating the risk of death for head and neck cancer patients by assigning values to the lethal contributions of tumor size, number of positive nodes, anatomical site, tumor extension, N stage, extracapsular spread, age at diagnosis, and race.

Method for quantitative study of airway functional microanatomy using micro-optical coherence tomography.

We demonstrate the use of a high resolution form of optical coherence tomography, termed micro-OCT (µOCT), for investigating the functional microanatomy of airway epithelia. µOCT captures several key parameters governing the function of the airway surface (airway surface liquid depth, periciliary liquid depth, ciliary function including beat frequency, and mucociliary transport rate) from the same series of images and without exogenous particles or labels, enabling non-invasive study of dynamic phenomena. Additionally, the high resolution of µOCT reveals distinguishable phases of the ciliary stroke pattern and glandular extrusion. Images and functional measurements from primary human bronchial epithelial cell cultures and excised tissue are presented and compared with measurements using existing gold standard methods. Active secretion from mucus glands in tissue, a key parameter of epithelial function, was also observed and quantified.