The nasal septum deviation index (NSDI) based on CBCT data

Objective: To assess whether three-dimensional morphometric parameters could be useful in nasal septal deviation (NSD) diagnosis and, secondarily, whether CBCT could be considered an adequate imaging technique for the proposed task. Methods: We analysed images of 46 subjects who underwent CBCT for reasons not related to this study. Two experienced operators divided all the images into healthy and NSD subjects. Subsequently, the images were segmented using ITK Snap in order to obtain the three-dimensional model of the nasal airways and compute four morphological parameters: septal deviation angle (SDA), percentage of volume difference between right and left side of the nasal airways, nasal airway total volume and a new synthetic septal deviation index (SDI). Principal component analysis (PCA) was used to unveil relationships between each variable and the global nasal airway variability. Results:, Differences between the groups were found in SDA (p < 0.001), in volume percentage difference (p < 0.05) and in SDI (p < 0.001). PCA showed high correlation between the SDI and the first principal component (0.97, p < 0.001). Conclusions: Among the analysed parameters, SDI seemed to be the most suitable for the quantitative assessment of NSD, and CBCT allowed accurate assessment of airway morphology.