Modelling structural determinants of ventilation heterogeneity: A perturbative approach

Area of Science:

• Computational biology
• Respiratory physiology
• Medical physics

Background:

• Multiple-breath washout (MBW) measures ventilation heterogeneity (VH) in obstructive lung diseases.
• Understanding how lung structure impacts MBW indices is crucial for clinical interpretation.

Purpose of the Study:

• To develop a computational model of lung gas mixing and ventilation.
• To predict MBW index responses to airway obstructions and heterogeneity.
• To explain the clinical utility of MBW in obstructive lung conditions.

Main Methods:

• Simulated a human lung as a bifurcating network with inter-regional airway constrictions.
• Employed a perturbative approach to model intra-regional airway heterogeneity.
• Analyzed the impact of varying airway radius and random structural variations on MBW indices (LCI, Scond).

Main Results:

• MBW indices detect severe airway constrictions (10-30% of healthy radius).
• Intra-regional heterogeneity increases MBW index variance, particularly with existing constrictions.
• Lung structural variability alone can cause clinically significant variability in LCI and Scond in simulated obstructive conditions.

Conclusions:

• The model explains MBW's success in distinguishing obstructive lung diseases from healthy controls.
• Computational modeling provides an efficient method to assess lung sensitivity to structural changes.
• Quantified uncertainty in MBW predictions due to lung mechanical and structural variability.