Exhaled breath analysis is a promising method for medical monitoring and diagnostics because it is non-invasive and limitlessly repeatable. The Fractional concentration of exhaled Nitric Oxide (FeNO), one of the best-studied biomarkers in exhaled breath, is a biomarker of airway inflammation used in the clinical assessment of asthma and environmental epidemiology. FeNO is conventionally assessed at a 50 ml/s exhalation flow rate (denoted FeNO50). In clinical practice, respiratory physicians are increasingly guiding treatment decisions using FeNO50. In environmental epidemiology, a growing body of literature shows that FeNO50 is a sensitive marker of respiratory response to inhaled environmental exposures. I specialize in a novel method of assessing FeNO: “multiple flow FeNO analysis” which noninvasively assesses airway and alveolar sources of NO, as described in Figure 1 below.
Figure 1. Cartoon overview of multiple flow FeNO analysis. (a) Multiple measurements of FeNO are conducted at different expiratory flow rates. (b) Data on the raw time-series of flow and FeNO are recorded during each maneuver. (c) Maneuvers are summarized by the average flow and average FeNO over a “stable” interval and plotted as FeNO vs. flow. (d) A statistical model links a deterministic model of NO in the lower respiratory tract (e.g., closed form solution to the steady-state two compartment model) with the measured FeNO vs. flow data to estimate “NO parameters” quantifying airway and alveolar sources: the airway wall concentration (CawNO), the airway wall diffusivity (DawNO), and the alveolar concentration (CANO).
An open issue in this field has been that the deterministic models of airway and alveolar NO were relatively well-developed, but the statistical methods for estimating their parameters were not. Existing methods relied on overly simplistic approximations and discarded valuable data. Also, the sampling design of exhalation flow rates was largely based on the available flow restrictors (though a restrictor could be manufactured for any flow rate within reasonable physiological bounds), and statistically optimal designs had not been identified. My statistical methods research program focuses on these issues.