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Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Computational fluid dynamics (CFD) of lung airflow during normal and pathophysiological breathing provides insight into regional pulmonary ventilation. By integrating CFD methods with 4D lung imaging workflows, regions of normal pulmonary function can be spared during treatment planning. To facilitate the use of CFD simulations in a clinical setup, a robust, automated, and CFD-compliant airway mesh generation technique is necessary.

Methods

We define a CFD-compliant airway mesh to be devoid of blockages of airflow and leaks in the airway path, both of which are caused by airway meshing errors that occur when using conventional meshing techniques. We present an algorithm to create a CFD-compliant airway mesh in an automated manner. Beginning with a medial skeleton of the airway segmentation, the branches were tracked, and 3D points at which bifurcations occur were identified. Airway branches and bifurcation features were isolated to allow for automated and careful meshing that considered their anatomical nature.

Results

We present the meshing results from three state-of-the-art tools and compare them with the meshes generated by our algorithm. The results show that fully CFD-compliant meshes were automatically generated for an ideal geometry and patient-specific CT scans. Using an open-source smoothed-particle hydrodynamics CFD implementation, we compared the airflow using our approach and conventionally generated airway meshes.

Conclusion

Our meshing algorithm was able to successfully generate a CFD-compliant mesh from pre-segmented lung CT scans, providing an automatic meshing approach that enables interventional CFD simulations to guide lung procedures such as radiotherapy or lung volume reduction surgery.

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Funding

This work is supported by the Tobacco Related Disease Research Program 27IR‐0056, NIH R56 1R56HL139767‐01A1, Ken and Wendy Ruby Foundation, and the UCLA Department of Radiation Oncology.

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Authors and Affiliations

  1. University of California, Los Angeles, CA, 90095, USA

    Michael Lauria, Kamal Singhrao, Bradley Stiehl, Daniel Low, Jonathan Goldin, Igor Barjaktarevic & Anand Santhanam

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  1. Michael Lauria
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  2. Kamal Singhrao
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  3. Bradley Stiehl
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Correspondence to Michael Lauria.

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Lauria, M., Singhrao, K., Stiehl, B. et al. Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics. Int J CARS 17, 185–197 (2022). https://doi.org/10.1007/s11548-021-02465-3

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