A Novel Computed Tomography-Based Automated Computational Framework for Individualized Radioactive Particle Deposition Modeling in the Human Respiratory Tract

This study introduces a comprehensive and automated framework for personalized particle deposition assessment in the human respiratory tract (HRT), overcoming the limitations of traditional models and offering a method for subject-specific studies. We introduce a novel computational framework, generating individualized particle deposition profiles and detailed dose maps leveraging 3D reconstructed HRT from Computed Tomography (CT) scans and advanced Computational Fluid and Particle Dynamics (CFPD) simulations. The work integrates 3D geometry reconstruction from CT scans using computer vision algorithms, geometry preprocessing for CFPD simulation readiness, pre-converged CFPD parameters for modeling airflow and particle simulation, and Monte Carlo source card generation for internal dose assessment from inhaled radioactive particles. Validation and verification of CFPD simulations confirmed convergence using a mesh with a base size of 1 mm. The workflow was tested on 14 different HRT geometries under various breathing conditions. The impaction parameter was used in our analysis to compare particle deposition efficiency results to those of previous literature, confirming our workflow accuracy. Particle and Heavy Ion Transport code System (PHITS) source cards were automatically generated using activity-weighted point sources from the CFPD-informed particle distribution profile. Our results showed a difference as high as 90 % in the absorbed fraction by specific organs compared to PHITS simulations using uniform particle distribution in the HRT. The presented automated workflow allows researchers to reduce the human hours spent on this task, typically spanning several hours or days, to a matter of minutes. This approach addresses the anatomical and physiological variations inherent in HRT, which are crucial for drug delivery systems, targeted respiratory therapies, and assessing inhaled radioactive particles at a subject-specific level.