Characterizing nitric oxide exchange dynamics during tidal breathing: Theory

P. Conderelli, Steven George

Research output: Contribution to journalConference article

Abstract

Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.

Original languageEnglish (US)
Pages (from-to)1489-1490
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
StatePublished - Dec 1 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002

Fingerprint

Nitric oxide
Nitric Oxide
Respiration
Lung
Pulmonary diseases
Gases
Exhalation
Ventilation
Flow rate
Inhalation
Fluxes
Lung Diseases
Uncertainty

Keywords

  • Airways
  • Diffusing capacity
  • NO
  • Parameter estimation
  • Tidal breathing

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

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abstract = "Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10{\%}). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.",
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N2 - Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.

AB - Parametric characterization of nitric oxide (NO) gas exchange using a two-compartment model of the lungs is a potentially promising, non-invasive technique to characterize inflammatory lung diseases. Currently, this techniques is limited to single breath maneuvers, including pre-expiratory breath-hold, which is cumbersome for children and individuals with compromised lung function. The current study extends the two-compartment model to parametric characterization of NO gas exchange from tidal breathing data. We assess the potential to estimate up to six flow-independent parameters, and study alternate breathing patterns by varying breathing frequency and inspiratory/expiratory flow rate ratio at constant alveolar ventilation rate. We identify three, easily characterized flow-independent parameters, which include maximum airway flux, steady state alveolar concentration, and airway volume (uncertainty < 10%). Rapid inhalation followed by slow (long duration) exhalation facilitates estimates of all flow-independent parameters. Our results demonstrate the potential of parametric analysis of tidal breathing data to characterize NO pulmonary exchange.

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