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Short Communication Open Access
Volume 3 | Issue 1 | DOI: https://doi.org/10.46439/neurobiology.3.012

The potential of computational fluid dynamics simulations of airflow in the nasal cavity

  • 1Department of Environmental, Process & Energy Engineering, MCI – The Entrepreneurial School, Austria
  • 2University Hospital of Otorhinolaryngology, Medical University Innsbruck, Austria
  • 3Department of Fluid Mechanics, Friedrich-Alexander University Erlangen-Nuremberg, Germany
+ Affiliations - Affiliations

Corresponding Author

Freysinger W, wolfgang.freysinger@i-med.ac.at

Received Date: November 05, 2020

Accepted Date: February 23, 2021

Abstract

Computational Fluid Dynamics (CFD) is a well-established and accepted tool for simulation and prediction of complex physical phenomena e.g., in combustion, aerodynamics or blood circulation. Recently CFD has entered the medical field due to the readily available high computational power of current graphics processing units, GPUs. Efficient numerical codes, commercial or open source, are available now. Thus, a wide range of medical themes is available for CFD almost in real-time in the medical environment now.
The available methods are on the point of reaching a usability status ready for everyday clinical use as a potential medical decision support system, provided adherence to the appropriate patient data protection rules and proper certification as a medical device.
This contribution outlines the current range of activities in our clinic in the field of Lattice-Boltzmann CFD based on CT and / or MR imagery and flashlights the following three areas: simulating the effect of nasal stents on breathing, predicting clinical Rhinomanometry and Rhinometry, and the numerical estimation of resection volumes for surgery to improve nasal breathing. The set of required methods is outlined, the three areas are discussed and summarized. The results presented are very preliminary insights into current research and need to be subject to further detailed evaluation, of course.
The results presented are very promising first steps in the direction of both digital patient diagnosis and therapy prediction. However, thorough and in-depth evaluation of the methods themselves and proper clinical studies to assess the merits of the technology are still required.

Keywords

Nasal airflow, Laser Doppler anemometry, Computational fluid dynamics, Breathing simulation, Nasal airflow optimization, Rhinomanometry, Surgery, Simulation, Diagnosis prediction

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