Image-based computational fluid dynamics in the lung: virtual reality or new clinical practice?

Area of Science:

• Computational fluid dynamics (CFD) applied to respiratory system modeling.
• Interdisciplinary approach integrating engineering and medicine for respiratory research.

Background:

• Personalized medicine requires understanding complex physiological processes.
• The respiratory system's function relies on precise air and blood flow dynamics.
• Computational fluid dynamics (CFD) is a powerful tool for analyzing fluid behavior in complex systems.

Purpose of the Study:

• To review the advancements and applications of CFD in the respiratory system.
• To highlight CFD's contribution to precision medicine in respiratory care.
• To focus on image-based, clinically relevant CFD for the ventilatory system.

Main Methods:

• Review of existing literature on CFD applications in the respiratory system.
• Focus on image-based CFD for analyzing fluid dynamics from nasal sinuses to alveolar airways.
• Integration of imaging data with CFD models for clinical applications.

Main Results:

• CFD accurately predicts fluid flow and pressure distribution in the respiratory tract.
• Image-based CFD enables improved design of aerosol delivery devices.
• CFD contributes to developing better biomarkers for lung function and surgical outcome predictions.

Conclusions:

• CFD is a crucial tool for advancing personalized respiratory medicine.
• Image-based CFD enhances understanding of respiratory fluid dynamics and aerosol transport.
• CFD applications improve device design, clinical trial biomarkers, and surgical planning in respiratory care.