Model analysis of multiple breath nitrogen washout data: robustness to variations in breathing pattern

Area of Science:

• Pulmonary Physiology
• Respiratory Medicine
• Medical Imaging and Instrumentation

Background:

• Multiple breath nitrogen washout (MBNW) is a technique used to assess lung function.
• Traditional analysis of MBNW data relies on identifying Phase-III, which can be challenging with irregular breathing.
• A novel model-based method has been developed to overcome this limitation.

Purpose of the Study:

• To evaluate the impact of irregular breathing patterns on the intra-subject variability of parameters derived from a new model-based MBNW analysis.
• To compare the variability of model-derived parameters with those obtained from conventional Phase-III slope analysis.

Main Methods:

• Nitrogen fraction at the mouth was measured in healthy and asthmatic subjects during controlled and free breathing.
• A model-fitting approach was used to analyze MBNW data, yielding parameters like functional residual capacity (FRC_M), dead space volume (V_D), and regional ventilation heterogeneity ([Formula: see text]).
• Conventional Phase-III slope analysis was also performed to obtain parameters such as Scond and Sacin.

Main Results:

• The model-based method demonstrated low intra-participant coefficients of variation for FRC_M (<5.2%), V_D (<5.4%), [Formula: see text] (<9.0%), and S_acin-M (<45.6%) during controlled breathing.
• During free breathing, variability for model parameters remained relatively low: FRC_M (<4.6%), V_D (<5.3%), [Formula: see text] (<13.2%), and S_acin-M (<103.2%).
• Conventional parameters showed higher variability, particularly Scond and Sacin, especially during free breathing.

Conclusions:

• The model-fitting approach for MBNW analysis provides a robust measure of regional ventilation heterogeneity ([Formula: see text]).
• This method is less susceptible to breathing pattern irregularities compared to traditional Phase-III slope analysis.
• The findings suggest improved reliability and accuracy of MBNW analysis using the model-based approach, particularly in non-ideal breathing conditions.