Geometric morphometric contribution to septal deviation analysis
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The nasal septum presents inter-individual conformational variations. The objectives of this study were to establish a validated protocol for nasal septum analysis using geometric morphometrics (GM) to establish a classification of septal deviations (SD).
This was a retrospective study including two groups of patients: patients operated on by septoplasty (SD group) and patients without nasal obstruction (control group). The 3D segmentation model was extracted from CT scans. Thirty landmarks were defined on the nasal septum and validated by MANOVA Procrustes. Using a clusterization process, the septum was classified to reflect its different conformations. Nasal resistances were compared between the two groups.
Fifty scans of patients with SD were included. The percentage of variability due to measurement error was 7.9% across all landmarks. We identified two clusters for the SD group. Using GM, conformation of cluster 1 (S-shaped) and cluster 2 (C-shaped) was visualized and identified. There was a statistically significant difference regarding nasal resistance between each cluster in the SD group compared with the control group (p < 0.05).
This work is a first step in SD exploration, contributing to a clearer appreciation of the interactions between nasal conformation and function. An SD classification was devised based on a reliable and reproducible statistical analysis. Enhanced understanding of conformation/function interactions will improve the diagnosis and treatment of nasal obstruction.
KeywordsNasal septum Nasal obstruction Septal deviation Geometric morphometrics Landmarks Cluster
TR: main author. DH, PD: data collection. PA: statistics. JM: study design
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- 1.Baumann I, Baumann H (2007) A new classification of septal deviations. Rhinology 45(3):220–223Google Scholar
- 3.Bookstein F (1993) Morphometric tools for landmark data: geometry and biology. J Classif 10(1):133–136Google Scholar
- 5.Buyukertan M, Keklikoglu N, Kokten G (2003) A morphometric consideration of nasal septal deviations by people with paranasal complaints: a computed tomography study. Rhinology 41:21–24Google Scholar
- 9.Guyomarc’h P, Santos F, Dutailly B, Desbarats P, Bou C, Coqueugniot H (2012) Three-dimensional computer-assisted craniometrics: a comparison of the uncertainty in measurement induced by surface reconstruction performed by two computer programs. Forensic Sci Int 219(1–3):221–227CrossRefGoogle Scholar
- 11.Heimer D (1983) Sleep apnea syndrome treated by repair of deviated nasal septum. Chest J 84(2):184Google Scholar
- 20.Rao J, Kumar E, Babu K, Chowdary V, Singh J, Rangamani S (2005) Classification of nasal septal deviations—relation to sinonasal pathology. Indian J Otolaryngol 57(3):199Google Scholar
- 22.Teixeira J, Certal V, Chang ET, Camacho M (2016) Nasal septal deviations: a systematic review of classification systems. Plast Surg Int 2016:7089123Google Scholar
- 23.Tomasi M (1997) The deviated nose. Classification and treatment. A propos of 100 cases. Ann Otolaryngol Chir Cervicofac 114(1–2):41–50Google Scholar
- 24.Zeng W, Chen G, Ju R, Yin H, Tian W, Tang W (2018) The combined application of database and three-dimensional image registration technology in the restoration of total nose defect. J Craniofac Surg 29(5):e484–e487Google Scholar