Dennis J Shusterman1, Barak M Spector2, Andrew N Goldberg3, Edward M Weaver4, Bradley A Otto2, Kai Zhao2. 1. Division of Occupational and Environmental Medicine, University of California, San Francisco, San Francisco, California, USA. 2. Department of Otolaryngology - Head and Neck Surgery, Ohio State University, Columbus, Ohio, USA. 3. Department of Otolaryngology - Head and Neck Surgery, University of California, San Francisco, San Francisco, California, USA. 4. Department of Otolaryngology - Head and Neck Surgery, University of Washington & Seattle Veterans Administration Medical Center, Seattle, Washington, USA.
Abstract
BACKGROUND: Upper airway nitric oxide (NO) is physiologically important in airway regulation and defense, and nasal NO (nNO) levels typically exceed those in exhaled breath (fractional exhaled NO [FeNO]). Elevated concentrations of NO sampled from the nose, in turn, reflect even higher concentrations in the paranasal sinuses, suggesting a "reservoir" role for the latter. However, the dynamics of NO flux within the sinonasal compartment are poorly understood. METHODS: Data from 10 human subjects who had previously undergone both real-time nNO sampling and computed tomography (CT) scanning of the sinuses were analyzed using computational fluid dynamics (CFD) methods. Modeled and observed nNO values during the initial 2-s transient ("spike") during nasal exhalation were then compared. RESULTS: Examining the initial 2-s transient spike for each subject (as well as the pooled group), there was a statistically significant correlation between modeled and observed nNO levels, with r values ranging from 0.43 to 0.89 (p values ranging from <0.05 to <0.0001). Model performance varied between subjects, with weaker correlations evident in those with high background (FeNO) levels. In addition, the CFD simulation suggests that ethmoid sinuses (>60%) and diffusion process (>54%) contributed most to total nasal NO emissions. CONCLUSION: Analysis of this dataset confirms that CFD is a valuable modeling tool for nNO dynamics, and highlights the importance of the ethmoid sinuses, as well as the role of diffusion as an initiating step in sinonasal NO flux. Future model iterations may apply more generally if baseline FeNO is taken into account.
BACKGROUND: Upper airway nitric oxide (NO) is physiologically important in airway regulation and defense, and nasal NO (nNO) levels typically exceed those in exhaled breath (fractional exhaled NO [FeNO]). Elevated concentrations of NO sampled from the nose, in turn, reflect even higher concentrations in the paranasal sinuses, suggesting a "reservoir" role for the latter. However, the dynamics of NO flux within the sinonasal compartment are poorly understood. METHODS: Data from 10 human subjects who had previously undergone both real-time nNO sampling and computed tomography (CT) scanning of the sinuses were analyzed using computational fluid dynamics (CFD) methods. Modeled and observed nNO values during the initial 2-s transient ("spike") during nasal exhalation were then compared. RESULTS: Examining the initial 2-s transient spike for each subject (as well as the pooled group), there was a statistically significant correlation between modeled and observed nNO levels, with r values ranging from 0.43 to 0.89 (p values ranging from <0.05 to <0.0001). Model performance varied between subjects, with weaker correlations evident in those with high background (FeNO) levels. In addition, the CFD simulation suggests that ethmoid sinuses (>60%) and diffusion process (>54%) contributed most to total nasal NO emissions. CONCLUSION: Analysis of this dataset confirms that CFD is a valuable modeling tool for nNO dynamics, and highlights the importance of the ethmoid sinuses, as well as the role of diffusion as an initiating step in sinonasal NO flux. Future model iterations may apply more generally if baseline FeNO is taken into account.
Authors: Julia S Kimbell; Guilherme J M Garcia; Dennis O Frank; Daniel E Cannon; Sachin S Pawar; John S Rhee Journal: Am J Rhinol Allergy Date: 2012 May-Jun Impact factor: 2.467
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Authors: Pasquale Ambrosino; Antonio Molino; Giorgio Alfredo Spedicato; Paolo Parrella; Roberto Formisano; Andrea Motta; Matteo Nicola Dario Di Minno; Mauro Maniscalco Journal: J Clin Med Date: 2020-01-11 Impact factor: 4.241