Evaluation of analytical particle deposition models against experimental mouse lung data

Particle deposition models were originally developed for pulmonary drug delivery and radiation dosimetry, yet their accuracy is also critical for assessing inhaled pollutants. Despite their widespread use, these models have been validated mainly against total deposition fractions in idealized geometries, leaving their performance against spatially resolved data largely untested. We implemented a probabilistic Markov chain deposition model that represents the airway tree as a graph of cylindrical segments. Per-segment capture probabilities combine impaction, sedimentation, and diffusion, with a piecewise airflow-split rule (local cross-sectional area proximally, distal-subtree volume distally). Three impaction kernels (Chan-Lippmann, Yeh-Schum, Zhang) were evaluated against the Lung Anatomy + Particle Deposition Mouse Archive (LAPDMouse), which reports spatially resolved per-airway deposition counts and per-mouse breathing parameters for 34 mice exposed to 0.5, 1, and 2 µm aerosols. Since LAPDMouse reports only spatial distributions of captured particles, agreement was evaluated as distributions over segmented airways. The piecewise model reproduces the experimental depth-wise distribution across all three particle sizes, placing 41%–55% of predicted captured particles in generation 12 and beyond, spanning the 41%–49% observed experimentally; among the three kernels, Chan-Lippmann tracks the experimental distal tail most closely. Lobe-wise residuals are moderate but structurally similar across all three impaction kernels, pointing to the 1-D reduction of proximal airflow allocation rather than a kernel-specific failure, consistent with CFD studies on realistic airway geometries. These findings are relevant for microplastic exposure assessment: analytical 1-D models can reproduce the captured-particle distribution, but regional predictions remain sensitive to how realistic anatomy is reduced to a branching graph, cylindrical airway segments, and simplified flow partitioning.