Computational fluid dynamics (CFD)-based calculation of intranasal airflow became an important method in rhinologic research. Current evidence shows weak to moderate correlation as well as a systematic underprediction of nasal resistance by numerical simulations. In this study, we investigate whether these differences can be explained by measurement uncertainties caused by rhinomanometric devices and procedures. Furthermore, preliminary findings regarding the impact of tissue movements are reported. A retrospective sample of 17 patients, who reported impaired nasal breathing and for which rhinomanometric (RMM) measurements using two different devices as well as computed tomography scans were available, was investigated in this study. Three patients also exhibited a marked collapse of the nasal valve. Agreement between both rhinomanometric measurements as well as between rhinomanometry and CFD-based calculations was assessed using linear correlation and Bland–Altman analyses. These analyses were performed for the volume flow rates measured at trans-nasal pressure differences of 75 and 150 Pa during inspiration and expiration. The correlation between volume flow rates measured using both RMM devices was good (R2 > 0.72 for all breathing states), and no relevant differences in measured flow rates was observed (21.6 ml/s and 14.8 ml/s for 75 and 150 Pa, respectively). In contrast, correlation between RMM and CFD was poor (R2 < 0.5) and CFD systematically overpredicted RMM-based flow rate measurements (231.8 ml/s and 328.3 ml/s). No differences between patients with and without nasal valve collapse nor between inspiration and expiration were observed. Biases introduced during RMM measurements, by either the chosen device, the operator or other aspects as for example the nasal cycle, are not strong enough to explain the gross differences commonly reported between RMM- and CFD-based measurement of nasal resistance. Additionally, tissue movement during breathing is most likely also no sufficient explanation for these differences.

This study’s objective was the generation of a standardized geometry of the healthy nasal cavity. An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the nasal resistance, wall shear stresses (WSS) and velocities were calculated as well as cross-sectional areas (CSA). Furthermore, individual WSS and static pressure distributions were mapped onto the average geometry. The average geometry featured an overall more regular shape that resulted in less resistance, reduced WSS and velocities compared to the median of the 25 geometries. Spatial distributions of WSS and pressure of the average geometry agreed well compared to the average distributions of all individual geometries. The minimal CSA of the average geometry was larger than the median of all individual geometries (83.4 vs. 74.7 mm²). The airflow observed within the average geometry of the healthy nasal cavity did not equal the average airflow of the individual geometries. While differences observed for integral measures were notable, the calculated values for the average geometry lay within the distributions of the individual parameters. Spatially resolved parameters differed less prominently.

Successful functional surgery on the nasal framework requires reliable and comprehensive diagnosis. In this regard, the authors introduce a new methodology: Digital Analysis of Nasal Airflow (diANA). It is based on computational fluid dynamics, a statistical shape model of the healthy nasal cavity and rhinologic expertise. diANA necessitates an anonymized tomographic dataset of the paranasal sinuses including the complete nasal cavity and, when available, clinical information. The principle of diANA is to compare the morphology and the respective airflow of an individual nose with those of a reference. This enables morphometric aberrations and consecutive flow field anomalies to localize and quantify within a patient's nasal cavity. Finally, an elaborated expert opinion with instructive visualizations is provided. Using diANA might support surgeons in decision-making, avoiding unnecessary surgery, gaining more precision, and target-orientation for indicated operations.

Functional surgery on the nasal framework requires referential criteria to objectively assess nasal breathing for indication and follow-up. This motivated us to generate a mean geometry of the nasal cavity based on a statistical shape model. In this study, the authors could demonstrate that the introduced nasal cavity's mean geometry features characteristics of the inner shape and airflow, which are commonly observed in symptom-free subjects. Therefore, the mean geometry might serve as a reference-like model when one considers qualitative aspects. However, to facilitate quantitative considerations and statistical inference, further research is necessary. Additionally, the authors were able to obtain details about the importance of the isthmus nasi and the inferior turbinate for the intranasal airstream.

Die Fortschritte in der Computertechnik spiegeln sich auch in der Praxis der Rhinochirurgie wider und können neue Entwicklungen befördern. Ziel des Beitrages ist es, diesen Zusammenhang anhand verschiedener Innovationen zu verdeutlichen. Dazu werden die digitale Fotodokumentation bzw. Ergebnissimulation, die Anwendung interaktiver 3‑D-Modelle des Nasengerüstes und die numerische Simulation der Nasenströmung diskutiert.

AbstractCurrently, there is no fully sufficient way to differentiate between symptomatic and normal nasal breathing. Using the nose's total resistance is disputed as a valid means to objectify nasal airflow, and the need for a more comprehensive diagnostic method is increasing. This work's aim was to test a novel approach considering intranasal wall shear stress (WSS) as well as static pressure maps obtained by computational fluid dynamics (CFD). X-ray computed tomography (CT) scan data of six symptom-free subjects and seven symptomatic patients were used. Patient-specific geometries of the nasal cavity were segmented from these datasets. Inspiratory and expiratory steady airflow simulations were performed using CFD. Calculated static pressures and WSSs were mapped onto a common template of the nasal septum, allowing for comparison of these parameters between the two patient groups. Significant differences in WSS distributions during the inspiratory phase could be identified between the two groups, whereas no differences were found for the expiratory phase. It is assumed that one essential feature of normal nasal breathing probably consists of distinctively different intranasal flow fields for inspiration and expiration. This is in accordance with previous investigations. The proposed method seems to be a promising tool for developing a new kind of patient-specific assessment of nasal breathing. However, more studies and a greater case number of data with an expanded focus would be ideal.

Anterior rhinomanometry is the current gold standard for the objective assessment of nasal breathing by determining the nasal resistance. However, computational fluid dynamics would allow spatially and temporally well- resolved investigation of additional flow parameters. In this study, measured values of nasal resistance are compared with measured values. An unclear discrepancy between the two methods was found, suggesting further investigation.

The current options for objective assessment of nasal breathing are limited. The maximum they can determine is the total nasal resistance. Possibilities to analyze the endonasal airstream are lacking. In contrast, numerical flow simulation is able to provide detailed information of the flow field within the nasal cavity. Thus, it has the potential to analyze the nasal airstream of an individual patient in a comprehensive manner and only a computed tomography (CT) scan of the paranasal sinuses is required. The clinical application is still limited due to the necessary technical and personnel resources. In particular, a statistically based referential characterization of normal nasal breathing does not yet exist in order to be able to compare and classify the simulation results.

The motivation behind the development of a new interactive three-dimensional (3D) model of the cartilaginous and bony framework of the nose originated from the significant demand for sophisticated patient communication and for accurate documentation of the surgical steps in rhinoplasty. Basically, the model consists of three features--the viewer function, the freehand function, and default applications--enabling the surgeon to replicate fundamental compilations of findings and to graphically document operative measures easily. The user is able to save all graphics in two-dimensional format and allocate them to patient files. Because the application was designed to be sufficiently universal without being too complex, the 3D model provides a well-balanced mix between freehand and default functions, representing the consistent development of currently available tools.

A reliable and comprehensive assessment of nasal breathing is problematic and still a common issue in rhinosurgery. Impairments of nasal breathing need an objective approach. In this regard, currently rhinomanometry is the only standard diagnostic tool available but has various limitations. However, in the last decade, computational fluid dynamics (CFD) has become a promising method in facing the challenge of qualifying nasal breathing. This article presents use of CFD with a symptom-free subject and a symptomatic patient. Thereby, certain flow field features and changes before and after surgery were investigated. Moreover, the study outlines suggestions for concrete rhinologic CFD applications.

Following the trend of specialization, rhinosurgery is increasingly developing into a relatively independent discipline. At the same time, it has an interdisciplinary character, which is also reflected in the presented articles.

The suggested concept of rhinorespiratory homeostasis is a new theoretical model for the discussion of physiologic and physical principles of nasal breathing. This model is based on a comprehensive view of nasal functions that takes comparative animal physiology into account. Consequently, it has a universal cross-species character and emphasizes the central role of nasal secretion. In contrast to the established view, the focus is transferred from the inspired air to the nasal wall. This concept considers the parietal effect of airflow represented by wall shear stress with special regard to the epithelial lining fluid. It delivers one possible mechanism of an inherent triggering of the nasal cycle. Furthermore, the issue of biological fluid-structure interaction is introduced. This article presents a rethinking of nasal breathing that was inspired by clinical experience and results of flow field investigations through computational fluid dynamics.

Rhinologists are often faced with the challenge of assessing nasal breathing from a functional point of view to derive effective therapeutic interventions. While the complex nasal anatomy can be revealed by visual inspection and medical imaging, only vague information is available regarding the nasal airflow itself: Rhinomanometry delivers rather unspecific integral information on the pressure gradient as well as on total flow and nasal flow resistance. In this article we demonstrate how the understanding of physiological nasal breathing can be improved by simulating and visually analyzing nasal airflow, based on an anatomically correct model of the upper human respiratory tract. In particular we demonstrate how various information visualization (InfoVis) techniques, such as a highly scalable implementation of parallel coordinates, time series visualizations, as well as unstructured grid multi-volume rendering, all integrated within a multiple linked views framework, can be utilized to gain a deeper understanding of nasal breathing. Evaluation is accomplished by visual exploration of spatio-temporal airflow characteristics that include not only information on flow features but also on accompanying quantities such as temperature and humidity. To our knowledge, this is the first in-depth visual exploration of the physiological function of the nose over several simulated breathing cycles under consideration of a complete model of the nasal airways, realistic boundary conditions, and all physically relevant time-varying quantities.

A requirement for normal breathing through the nose is an undisturbed passage through the nasal airways. If this condition is not fulfilled due to any obstruction or deformation, surgical correction of the nasal airways might be required. Rhinosurgery is a reconstructive surgical approach that reshapes the nose and/or nasal structure and often is used to correct birth defects or other breathing problems. To understand the effects of nasal anatomy on normal breathing, a team in Germany composed of members from the Zuse-Institute Berlin, Asklepios Clinic Birkenwerder and CFX Berlin Software GmbH carried out simulations using ANSYS CFX computational fluid dynamics (CFD) software. The research team based the analysis models on highly detailed internal and external nasal anatomy. The ability to simulate complex airflow characteristics with regard to individual anatomy enables the study of the physiology and pathophysiology of nasal breathing on a per patient basis. As a result, fluid flow simulations can become an extremely useful tool in treatment planning for functional rhinosurgery. For this study, the research team based their investigations on a reference model of the nasal airways created from actual human anatomy without obvious pathologic symptoms. To develop a geometric model for this case, researchers first acquired a helical computed tomography (CT) scan of a male volunteer following local administration of a decongestant. High-resolution tomography with an almost isotropic spatial resolution of 0.37 x 0.37 x 0.4 millimeters allowed for the representation of internal anatomical structures with sufficient detail. This provided the team with three-dimensional geometric information that they used to create a simulation model of the nasal and paranasal cavities. The research team then used AMIRA[4] software to reconstruct and Pathlines for air flow during inhalation, colored by velocity

Our objective is to analyze and understand the physiology and patho-physiology of normal nasal breathing. To this end, airflow simulations based on computational fluid dynamics (CFD) are presented for a highly detailed anatomy of the upper respiratory tract from the external nose to the larynx, including frontal and maxillary sinuses, as well as the ethmoid. Complex flow phenomena are investigated with regard to individual anatomy and its variations. We are aiming to gain insight into the relationship between morphology and flow behaviour in order to provide general treatment proposals and to develop computer assisted planning tools for decision support in functional rhinosurgery.

Though treatment methods in ear nose and throat surgery have constantly improved over time, the prediction of a successful individual therapy under consideration of regular nasal airflow remains a challenging task Airflow simulations based on computational fluid dynamics are presented for a highly detailed anatomy of a nasal airway including frontal and paranasal sinuses, being reconstructed from tomographic data. The simulation of complex airflow characteristics with regard to individual anatomy enables us to study the physiology and pathophysiology of nasal breathing, thus being able to support treatment planning in functional rhinosurgery.