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Computational Fluid Dynamics Modeling of Nasal Obstruction and Associations with Patient-Reported Outcomes

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Zwicker,  David
Max Planck Research Group Theory of Biological Fluids, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

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Citation

Barbarite, E., Gadkaree, S. K., Melchionna, S., Zwicker, D., & Lindsay, R. W. (2021). Computational Fluid Dynamics Modeling of Nasal Obstruction and Associations with Patient-Reported Outcomes. Plastic & Reconstructive Surgery, 148, 592e-600e. doi:10.1097/PRS.0000000000008328.


Cite as: https://hdl.handle.net/21.11116/0000-0009-CE12-B
Abstract
Nasal obstruction is a common problem, with significant impact on quality of life. Accurate diagnosis may be challenging because of the complex and dynamic nature of the involved anatomy. Computational fluid dynamics modeling has the ability to identify specific anatomical defects, allowing for a targeted surgical approach. The goal of the current study is to better understand nasal obstruction as it pertains to disease-specific quality of life by way of a novel computational fluid dynamics model of nasal airflow.

Fifty-three patients with nasal obstruction underwent computational fluid dynamics modeling based on computed tomographic imaging. Nasal resistance was compared to demographic data and baseline subjective nasal patency based on Nasal Obstructive Symptom Evaluation scores.