C108-15 Ventilation Distribution in a Three-Dimensional (3D) Binary Airway Tree With Regional Acinar Elastances Mapped From Computed Tomography (CT)-Based Deformation

Abstract Rationale Numerical simulation of ventilation distribution provides quantitative insights into air flow distribution within the complex geometry of the lung. Such simulations reveal regional differences in ventilation, assess the impact of disease, and offer a noninvasive, reproducible means to study pulmonary mechanics with potential to improve respiratory care. Registering and mapping regional lung elastances derived from CT-based Jacobian determinants onto the acini of a virtual airway tree provides spatially heterogeneous properties that simulate in vivo lung mechanics more accurately. Compared to those using uniform or Perlin-based acinar elastances, the resulting simulations may yield more physiologically realistic ventilation distribution, and improve the fidelity of functional lung modeling. Method A one-dimensional (1D) airway tree of a 40 kg porcine lung was generated within a three-dimensional (3D) domain using a space-filling algorithm, yielding 30,959 airway segments and 15,479 terminal points for acinar placement. An anesthetized pig at the same weight received volumetric 3D CT scans during static breath holds at various pressure settings. The voxel-wise elastances derived from the CT images were mapped to the acini of the numerical airway tree via non-rigid registration and Voronoi partitioning. The nodes of the numerical airway tree represent the effects of viscous dissipation and convective acceleration of gas flow through cylindrical airway segments, along with the viscoelastic behavior of airway walls and surrounding parenchyma. Regional ventilation to individual acini was evaluated by traversing the entire tree with a recursive flow-division algorithm, enabling computation of acinar flow and pressure distributions. The simulations were performed across a wide range of ventilation frequencies, to examine the resulting ventilation distributions. Results Compared with the uniform acinar elastance setup, the simulations using mapped acinar properties exhibited greater regional variations in pressure (Figure 1) and flow magnitude, as well as phase difference, across the wide range of ventilation frequencies. Acinar flow magnitudes showed a substantially broader range below the resonant or corner frequency, while acinar pressure magnitudes remained relatively similar in this region. Overall, simulations incorporating mapped acinar elastances are considered more physiologically realistic. Conclusion Numerical simulation of ventilation distribution offers a noninvasive way to study lung mechanics and optimize respiratory care. By mapping CT-derived regional elastances onto acini, simulations capture in vivo spatial heterogeneity and lung realism more accurately, yielding more physiologically meaningful ventilation patterns than those using uniform or Perlin-based acinar elastances. This abstract is funded by: W81XWH-21-1-0507, W911NF-23-1-0004