Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-13T01:43:40.022Z Has data issue: false hasContentIssue false
  • English
  • Français

Expiratory nasal sound analysis as a new method for evaluation of nasal obstruction in patients with nasal septal deviation: comparison of expiratory nasal sounds from both deviated and normal nasal cavity

Published online by Cambridge University Press:  25 June 2007

R Tahamiler ,
S Canakcioglu ,
S Yilmaz  and
A Dirican
R Tahamiler*
Affiliation:
Departments of Otorhinolaryngology, Cerrahpasa Medicine School, Istanbul University, Turkey
S Canakcioglu
Affiliation:
Departments of Otorhinolaryngology, Cerrahpasa Medicine School, Istanbul University, Turkey
S Yilmaz
Affiliation:
Departments of Otorhinolaryngology, Cerrahpasa Medicine School, Istanbul University, Turkey
A Dirican
Affiliation:
Departments of Biostatistics, Cerrahpasa Medicine School, Istanbul University, Turkey
*
Address for correspondence: Dr Rauf Tahamiler, Kozyatagi Central Hospital, Kozyatagi Sok No 5 Kozyatagi tr-34742 Istanbul, Turkey. Fax: +90 216 3847748 E-mail: tahamiler@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

The reliability of nasal obstruction measurements could be improved, and several new techniques are being developed. Our objective was to investigate the use of a new software program, Odiosoft-Rhino, in the assessment of nasal obstruction via analysis of the sounds of nasal expiration.

Methods:

We compared the nasal symptom scores and Odiosoft-Rhino and acoustic rhinometry test results for 61 patients with known nasal septal deviation.

Results:

We found a significant difference, and a correlation, between Odiosoft-Rhino results at 2000–4000 Hz and 4000–6000 Hz intervals, and the minimal cross-sectional area 2.2 cm from the nostril, in the right nasal cavity in patients with right-sided deviations. Similar results were observed for the left nasal cavity in patients with left-sided deviations.

Conclusions:

The Odiosoft-Rhino software test is noninvasive, requires minimal cooperation and experience, and provides results that can be saved as digital data. Additionally, data from the Odiosoft-Rhino test are strongly correlated with acoustic rhinometry results and visual analogue scores of nasal obstruction. It seems that sound intensity within the 2000–4000 Hz and 4000–6000 Hz intervals is more sensitive than other sound intensity intervals. Thus, we speculate that Odiosoft-Rhino testing could be used as a new diagnostic method in order to evaluate nasal airflow in clinical practice.

Keywords

Nasal CavityNasal ObstructionResearch DesignRhinometry
Type
Main Articles
Information
The Journal of Laryngology & Otology , Volume 122 , Issue 2 , February 2008 , pp. 150 - 154
Copyright
Copyright © JLO (1984) Limited 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1 Van Erck, E, Votion, D, Art, T, Lekeux, P. Qualitative and quantitative evaluation of equine respiratory mechanics by impulse oscillometry. Equine Vet J 2006;38:52–8CrossRefGoogle ScholarPubMed
2 Grutzenmacher, S, Lang, C, Mlynski, R, Mlynski, B, Mlynski, G. Long-term rhinoflowmetry: a new method for functional rhinologic diagnostics. Am J Rhinol 2005;19:53–7CrossRefGoogle ScholarPubMed
3 Wustenberg, EG, Huttenbrink, KB, Hauswald, B, Hampel, U, Schleicher, E. Optical Rhinometry. Continuous, direct measurement of swelling of the nasal mucosa with allergen provocation, real-time monitoring of the nasal provocation test using optical rhinometry [in German]. HNO 2004;52:798–806Google ScholarPubMed
4 Cuddihy, PJ, Eccles, R. The use of nasal spirometry for the assessment of unilateral nasal obstruction associated with changes in posture in healthy subjects and subjects with upper respiratory tract infection. Clin Otolaryngol 2003;28:108–11CrossRefGoogle ScholarPubMed
5 Seren, E. Frequency spectra of normal expiratory nasal sound. Am J Rhinol 2005;19:257–61CrossRefGoogle ScholarPubMed
6 Pasterkamp, H, Kraman, SS, Wodıcka, GR. Respiratory sounds. Am J Respir 1997;156:974–87Google ScholarPubMed
7 Cheetham, BMG, Giordano, A, Helisto, P. Digitisation of data for respiratory sound recordings. Eur Respir Rev 2000;10:625–35Google Scholar
8 Charbonneau, G, Sudraud, M, Soufflet, G. Method for the evaluation of flow rate from pulmonary sounds. Bull Eur Physiopathol Respir 1987;23:265–70Google ScholarPubMed
9 Kraman, SS, Pasterkamp, H, Kompis, M, Takase, M, Wodicka, GR. Effects of breathing pathways on tracheal sound spectral features. Respir Physiol 1998;111:295–300CrossRefGoogle ScholarPubMed
10 Charbonneau, G, Ademovic, E, Cheetham, BMG, Malmberg, LP, Vanderschoot, J, Sovijärvi, ARA. Basic techniques for respiratory sound analysis. Eur Respir Rev 2000;10:625–35Google Scholar
11 Tahamiler, R, Edizer, DT, Canakcioglu, S. Nasal expiratory sound analysis in healthy people. Otolaryngol Head Neck Surg 2006;134:605–8CrossRefGoogle ScholarPubMed
12 Tahamiler, R, Edizer, DT, Canakcioglu, S, Guvenc, MG, Inci, E, Dirican, A. Nasal sound analysis: a new method for evaluating nasal obstruction in allergic rhinitis. Laryngoscope 2006;116:2050–4CrossRefGoogle ScholarPubMed
13 Mamikoglu, B, Houser, S, Akbar, I, Ng, B, Corey, JP. Acoustic rhinometry and computed tomography scans for the diagnosis of nasal septal deviation, with clinical correlation. Otolaryngol Head Neck Surg 2000;123:61–8CrossRefGoogle ScholarPubMed
14 Seren, E. Web-based analysis of nasal sound spectra. Telemed J E Health 2005;11:578–82CrossRefGoogle ScholarPubMed