Computers in biology and medicine · 2021
Computational modeling of nasal nitric oxide flux from the paranasal sinuses: Validation against human experiment.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Spector Barak M, Shusterman Dennis J, Goldberg Andrew N, Weaver Edward M, Farag Alexander A, Otto Bradley A, Zhao Kai
Аннотация
BACKGROUND: Nitric oxide (NO) is important in respiratory physiology and airway defense. Although the paranasal sinuses are the major source of nasal NO, transport dynamics between the sinuses and nasal cavities are poorly understood.
METHODS: Exhaled nasal NO tracings were measured in two non-asthmatic subjects (one with allergic rhinitis, one without) using NO analyzer connected via face mask. We subsequently performed computational fluid dynamics NO emission simulations based on individual CT scans and compared to the experimental data.
RESULTS: Simulated exhaled NO tracings match well with experimental data (r > 0.84, p < 0.01) for both subjects, with measured peaks reaching 319.6 ppb in one subject (allergic-rhinitis), and 196.9 ppb in the other. The CFD simulation accurately captured the peak differences, even though the initial sinus NO concentration for both cases was set to the same 9000 ppb based on literature value. Further, the CFD simulation suggests that ethmoid sinuses contributed the most (>67%, other sinuses combined <33%) to total nasal NO emission in both cases and that diffusion contributes more than convective transport. By turning off diffusion (setting NO diffusivity to ~0), the NO emission peaks for both cases were reduced by >70%.
CONCLUSION: Historically, nasal NO emissions were thought to be contributed mostly by the maxillary sinuses (the largest sinuses) and active air movement (convection). Here, we showed that the ethmoid sinuses and diffusive transport dominate the process. These findings may have a substantial impact on our view of nasal NO emission mechanisms and sinus physiopathology in general.
METHODS: Exhaled nasal NO tracings were measured in two non-asthmatic subjects (one with allergic rhinitis, one without) using NO analyzer connected via face mask. We subsequently performed computational fluid dynamics NO emission simulations based on individual CT scans and compared to the experimental data.
RESULTS: Simulated exhaled NO tracings match well with experimental data (r > 0.84, p < 0.01) for both subjects, with measured peaks reaching 319.6 ppb in one subject (allergic-rhinitis), and 196.9 ppb in the other. The CFD simulation accurately captured the peak differences, even though the initial sinus NO concentration for both cases was set to the same 9000 ppb based on literature value. Further, the CFD simulation suggests that ethmoid sinuses contributed the most (>67%, other sinuses combined <33%) to total nasal NO emission in both cases and that diffusion contributes more than convective transport. By turning off diffusion (setting NO diffusivity to ~0), the NO emission peaks for both cases were reduced by >70%.
CONCLUSION: Historically, nasal NO emissions were thought to be contributed mostly by the maxillary sinuses (the largest sinuses) and active air movement (convection). Here, we showed that the ethmoid sinuses and diffusive transport dominate the process. These findings may have a substantial impact on our view of nasal NO emission mechanisms and sinus physiopathology in general.