Nasal cavity airflow: Comparing laser doppler anemometry and computational fluid dynamic simulations

Berger, Manuel; Pillei, Martin; Mehrle, Andreas; Recheis, Wolfgang; Kral, Florian; Kraxner, Michael; Bárdosi, Z; Freysinger, Wolfgang

doi:10.1016/j.resp.2020.103533

Cited by 9 publications

(23 citation statements)

References 19 publications

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“…This change is not reflected within the LB simulation [22]. The resolution of the spatial discretization was considered sufficient and mesh independent [11]. However, the resolution was not sufficient to resolve sub-millimetric turbulent flow phenomena, especially when the air-space cross section was smaller than 3-5 cells (0.702-1.17 mm).…”

Section: Discussionmentioning

confidence: 99%

“…Sailfish CFD [14], a lattice Boltzmann (LB) code running on an Nvidia GeForce RTX 2080 Ti graphic processing unit (GPU), was used for simulation of the nasal airflow [11]. One nasal airflow simulation on the GPU required less than 5 min of computational time.…”

Section: Simulation Parametersmentioning

confidence: 99%

“…In our study, we investigated the correlations and agreements between the results from AAR and an in-house developed CT-based CFD approach for multiple subjects. Our CFD simulations of nasal airflow were previously validated with laser Doppler anemometry (LDA) [11]. LDA is a fluid flow measurement technique that captures the velocity of particles in the flow field.…”

Section: Introductionmentioning

confidence: 99%

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Agreement between rhinomanometry and computed tomography-based computational fluid dynamics

et al. 2021

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Purpose Active anterior rhinomanometry (AAR) and computed tomography (CT) are standardized methods for the evaluation of nasal obstruction. Recent attempts to correlate AAR with CT-based computational fluid dynamics (CFD) have been controversial. We aimed to investigate this correlation and agreement based on an in-house developed procedure. Methods In a pilot study, we retrospectively examined five subjects scheduled for septoplasty, along with preoperative digital volume tomography and AAR. The simulation was performed with Sailfish CFD, a lattice Boltzmann code. We examined the correlation and agreement of pressure derived from AAR (RhinoPress) and simulation (SimPress) and these of resistance during inspiration by 150 Pa pressure drop derived from AAR (RhinoRes150) and simulation (SimRes150). For investigation of correlation between pressures and between resistances, a univariate analysis of variance and a Pearson’s correlation were performed, respectively. For investigation of agreement, the Bland–Altman method was used. Results The correlation coefficient between RhinoPress and SimPress was r = 0.93 (p < 0.001). RhinoPress was similar to SimPress in the less obstructed nasal side and two times greater than SimPress in the more obstructed nasal side. A moderate correlation was found between RhinoRes150 and SimRes150 (r = 0.65; p = 0.041). Conclusion The simulation of rhinomanometry pressure by CT-based CFD seems more feasible with the lattice Boltzmann code in the less obstructed nasal side. In the more obstructed nasal side, error rates of up to 100% were encountered. Our results imply that the pressure and resistance derived from CT-based CFD and AAR were similar, yet not same.

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Section: Discussionmentioning

confidence: 99%

Section: Simulation Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Agreement between rhinomanometry and computed tomography-based computational fluid dynamics

et al. 2021

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“…LB features advantages for optimizing respiratory flow with Cartesian meshes and isotropic grid spacing in Sailfish CFD [ 6 ] and grid cells can simply be added or removed from the fluid domain. LB is preferred over FVM, since it reached good agreement to experimental data for the nasal cavity [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…A code to optimize the shape of the nasal cavity based on fluid flow analysis is presented. LDA validated LB simulations [ 12 ] are used to find high pressure gradient regions (HPGRs).…”

Section: Introductionmentioning

confidence: 99%

Pre-surgery planning tool for estimation of resection volume to improve nasal breathing based on lattice Boltzmann fluid flow simulations

et al. 2021

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Purpose State-of-the-art medical examination techniques (e.g., rhinomanometry and endoscopy) do not always lead to satisfactory postoperative outcome. A fully automatized optimization tool based on patient computer tomography (CT) data to calculate local pressure gradient regions to reshape pathological nasal cavity geometry is proposed. Methods Five anonymous pre- and postoperative CT datasets with nasal septum deviations were used to simulate the airflow through the nasal cavity with lattice Boltzmann (LB) simulations. Pressure gradient regions were detected by a streamline analysis. After shape optimization, the volumetric difference between the two shapes of the nasal cavity yields the estimated resection volume. Results At LB rhinomanometry boundary conditions (bilateral flow rate of 600 ml/s), the preliminary study shows a critical pressure gradient of −1.1 Pa/mm as optimization criterion. The maximum coronal airflow ΔA := cross-section ratio $$\frac{\mathrm{virtual surgery }}{\mathrm{post}-\mathrm{surgery}}$$ virtual surgery post - surgery found close to the nostrils is 1.15. For the patients a pressure drop ratio ΔΠ := (pre-surgery − virtual surgery)/(pre-surgery − post-surgery) between nostril and nasopharynx of 1.25, 1.72, −1.85, 0.79 and 1.02 is calculated. Conclusions LB fluid mechanics optimization of the nasal cavity can yield results similar to surgery for air-flow cross section and pressure drop between nostril and nasopharynx. The optimization is numerically stable in all five cases of the presented study. A limitation of this study is that anatomical constraints (e.g. mucosa) have not been considered.

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Computational analysis of human upper airway aerodynamics

Hebbink

Wessels²,

Hagmeijer³

et al. 2022

Med Biol Eng Comput

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There is a considerable interest in understanding transient human upper airway aerodynamics, especially in view of assessing the effects of various ventilation therapies. Experimental analyses in a patient-specific manner pose challenges as the upper airway consists of a narrow confined region with complex anatomy. Pressure measurements are feasible, but, for example, PIV experiments require special measures to accommodate for the light refraction by the model. Computational fluid dynamics can bridge the gap between limited experimental data and detailed flow features. This work aims to validate the use of combined lattice Boltzmann method and a large eddy scale model for simulating respiration, and to identify clinical features of the flow and show the clinical potential of the method. Airflow was computationally analyzed during a realistic, transient, breathing profile in an upper airway geometry ranging from nose to trachea, and the resulting pressure calculations were compared against in vitro experiments. Simulations were conducted on meshes containing about 1 billion cells to ensure accuracy and to capture intrinsic flow features. Airway pressures obtained from simulations and in vitro experiments are in good agreement both during inhalation and exhalation. High velocity pharyngeal and laryngeal jets and recirculation in the region of the olfactory cleft are observed.

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Nasal cavity airflow: Comparing laser doppler anemometry and computational fluid dynamic simulations

Cited by 9 publications

References 19 publications

Agreement between rhinomanometry and computed tomography-based computational fluid dynamics

Agreement between rhinomanometry and computed tomography-based computational fluid dynamics

Pre-surgery planning tool for estimation of resection volume to improve nasal breathing based on lattice Boltzmann fluid flow simulations

Computational analysis of human upper airway aerodynamics

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