Analysis of inferior nasal turbinate width and concha bullosa in subjects with nasal septum deviation: a cone beam tomography study

The Application of Mask Region-Based Convolutional Neural Networks in the Detection of Nasal Septal Deviation Using Cone Beam Computed Tomography Images: Proof-of-Concept Study

BACKGROUND

Artificial intelligence (AI) models are being increasingly studied for the detection of variations and pathologies in different imaging modalities. Nasal septal deviation (NSD) is an important anatomical structure with clinical implications. However, AI-based radiographic detection of NSD has not yet been studied.

OBJECTIVE

This research aimed to develop and evaluate a real-time model that can detect probable NSD using cone beam computed tomography (CBCT) images.

METHODS

Coronal section images were obtained from 204 full-volume CBCT scans. The scans were classified as normal and deviated by 2 maxillofacial radiologists. The images were then used to train and test the AI model. Mask region-based convolutional neural networks (Mask R-CNNs) comprising 3 different backbones-ResNet50, ResNet101, and MobileNet-were used to detect deviated nasal septum in 204 CBCT images. To further improve the detection, an image preprocessing technique (contrast enhancement [CEH]) was added.

RESULTS

The best-performing model-CEH-ResNet101-achieved a mean average precision of 0.911, with an area under the curve of 0.921.

CONCLUSIONS

The performance of the model shows that the model is capable of detecting nasal septal deviation. Future research in this field should focus on additional preprocessing of images and detection of NSD based on multiple planes using 3D images.

The use of CBCT in orthodontics with special focus on upper airway analysis in patients with sleep-disordered breathing

Applications of cone-beam CT (CBCT) in orthodontics have been increasingly discussed and evaluated in science and practice over the last two decades. The present work provides a comprehensive summary of current consolidated practice guidelines, cutting-edge innovative applications, and future outlooks about potential use of CBCT in orthodontics with a special focus on upper airway analysis in patients with sleep-disordered breathing. The present scoping review reveals that clinical applications of CBCT in orthodontics are broadly supported by evidence for the diagnosis of dental anomalies, temporomandibular joint disorders, and craniofacial malformations. On the other hand, CBCT imaging for upper airway analysis-including soft tissue diagnosis and airway morphology-needs further validation in order to provide better understanding regarding which diagnostic questions it can be expected to answer. Internationally recognized guidelines for CBCT use in orthodontics are existent, and similar ones should be developed to provide clear indications about the appropriate use of CBCT for upper airway assessment, including a list of specific clinical questions justifying its prescription.

Analysis of inferior nasal turbinate volume in subjects with nasal septum deviation: a retrospective cone beam tomography study

Background

The association of the linear dimensions of the inferior turbinate hypertrophy with nasal septal deviation has been studied recently. However, the volumetric dimensions provide a more accurate status of the turbinate hypertrophy compared to linear measurements. The aim of this study was to analyze the association of inferior nasal turbinate volume with the degree of nasal septal deviation (NSD).

Methods

A retrospective evaluation of the cone beam computed tomography (CBCT) scans of 412 patients was carried out to obtain 150 scans which were included in the study. The scans were categorized into three groups. Group 1 comprised of 50 scans of patients with no inferior turbinate hypertrophy (ITH) and no nasal septal deviation. Group 2 comprised of 50 scans of patients with ITH and no NSD; whereas Group 3 included 50 scans of patients with ITH and NSD. The total turbinate volume of inferior turbinates (bilateral) were determined by using Vesalius 3D software (PS-Medtech, Amsterdam, Netherlands).

Results

The intraclass correlation coefficient (ICC) between the volumetric estimations performed by the two radiologists was 0.82. There were no significant age and gender related changes in the total turbinate volume. Patients in Group 3 had significantly higher (p = 0.001) total turbinate volume compared to Group 2 and Group 1. There was a positive and significant correlation (r = 0.52, p = 0.002) between the degree of septal deviation and total turbinate volume. When the total turbinate volume of the patients with different types of septal deviation was compared in Group 3, a statistically significant difference (p = 0.001) was observed. Regression analysis revealed that the septal deviation angle (SDA) (p = 0.001) had a relationship with total turbinate volume. From the results of the study we can conclude that the total turbinate volume is higher in patients with nasal septal deviation. It can also be concluded that the septal deviation angle has a positive correlation with total turbinate volume. The data obtained from the study can be useful in post-surgical follow up and evaluation of patients with nasal septal deviation and hypertrophied inferior nasal turbinate.