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Comparison of rhinomanometric and computational fluid dynamic assessment of nasal resistance with respect to measurement accuracy

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Abstract

Purpose

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.

Methods

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.

Results

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.

Conclusion

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.

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Notes

  1. NASAL, www.nasalsystems.es.

  2. Available via www.figshare.com; https://doi.org/10.6084/m9.figshare.19204971.

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Funding

No funding was received for conducting this study.

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Authors and Affiliations

  1. Department of Otorhinolaryngology and Facial Plastic Surgery, Park-Klinik Weissensee, Schönstraße 80, 13086, Berlin, Germany

    Nora Schmidt & Hans Behrbohm

  2. Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany

    Leonid Goubergrits, Thomas Hildebrandt & Jan Brüning

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Contributions

All roles according to CRediT (contributor roles taxonomy). All authors contributed to conceptualization, and writing, reviewing and editing. NS and JB carried out data curation, formal analysis and investigation, and wrote the original draft. NS, TH, LG and JB were responsible for methodology. HB, TH and LG took part in supervision. JB participated in visualization. All authors contributed to the article and approved the submitted version.

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Correspondence to Nora Schmidt.

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Schmidt, N., Behrbohm, H., Goubergrits, L. et al. Comparison of rhinomanometric and computational fluid dynamic assessment of nasal resistance with respect to measurement accuracy. Int J CARS 17, 1519–1529 (2022). https://doi.org/10.1007/s11548-022-02699-9

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