scholarly journals Volumetric Computed Tomography Analysis of Middle Turbinate Aeration (Concha Bullosa) in Nasal Septal Deviation

2020 ◽  
Vol 3 (1) ◽  
pp. 10-12
Author(s):  
Zeynep Onerci Altunay ◽  
Keyword(s):  
Computed Tomography ◽  
Middle Turbinate ◽  
Septal Deviation ◽  
Concha Bullosa ◽  
Nasal Septal Deviation ◽  
Tomography Analysis

scholarly journals Relationships among Concha Bullosa, Nasal Septal Deviation, and Sinusitis: Retrospective Analysis of 296 Cases

2016 ◽  
Vol 95 (12) ◽  
pp. 487-491 ◽  
Author(s):  
Hasan H. Balikci ◽  
M. Mustafa Gurdal ◽  
Saban Celebi ◽  
Isa Ozbay ◽  
Mustafa Karakas
Keyword(s):  
Computed Tomography ◽  
Retrospective Analysis ◽  
Causal Relationship ◽  
Significant Relationship ◽  
Septal Deviation ◽  
Concha Bullosa ◽  
Sinus Disease ◽  
Nasal Septal Deviation ◽  
Computed Tomography Scans ◽  
Paranasal Sinus Computed Tomography

We aimed to investigate the relationships among concha bullosa (CB), nasal septal deviation (NSD), and sinus disease. We retrospectively reviewed paranasal sinus computed tomography scans obtained from 296 patients—132 men and 164 women, aged 17 to 76 years (median: 39)—who had been evaluated over a 19-month period. CBs were classified as lamellar, bulbous, and extensive. In cases of bilateral CB, the larger side was designated as dominant. In all, 132 patients (44.6%) exhibited pneumatization of at least one concha, 176 (59.5%) had NSD, and 187 (63.2%) had sinus disease. Some 89 of 106 patients with unilateral or one-side-dominant CB (84.0%) had NSD, 89 of 132 patients with CB (67.4%) had sinus disease, and 109 of the 176 patients with NSD (61.9%) had sinus disease. We found a statistically significant relationship between CB and contralateral NSD, but no significant relationship between CB and sinus disease or NSD and sinus disease. While CB is a common anatomic problem that may accompany NSD, a causal relationship between CB or NSD and sinus disease is dubious.

scholarly journals The effect of concha bullosa and nasal septal deviation on palatal dimensions: a cone beam computed tomography study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shishir Ram Shetty ◽  
Saad Wahby Al Bayatti ◽  
Natheer Hashim Al-Rawi ◽  
Vinayak Kamath ◽  
Sesha Reddy ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Hard Palate ◽  
Study Groups ◽  
Septal Deviation ◽  
Cone Beam ◽  
Concha Bullosa ◽  
Deviation Angle ◽  
Nasal Septal Deviation ◽  
Skeletal Malocclusion

Abstract Introduction Nasal septal deviation (NSD) and concha bullosa (CB) are associated with airway obstruction in mouth breathers. Mouth breathing is associated with alterations in maxillary growth and palatal architecture. The aim of our study was to determine the effect of the presence of CB and NSD on the dimensions of the hard palate using cone-beam computed tomography (CBCT). Materials and methods A retrospective study was conducted using CBCT scans of 200 study subjects. The study subjects were divided into four groups based on the presence of CB and NSD. Septal deviation angle (SDA), palatal interalveolar length (PIL), palatal depth (PD) and maxillopalatal arch angle (MPAA) were measured in the study groups. Results The presence of NSD and CB was associated with significant (p < 0.001) differences in the palatal dimensions of the study subjects. The PIL and MPA (p < 0.001) were significantly reduced (p < 0.001), whereas the PD was significantly increased (p < 0.001) in study subjects with NSD and CB. There was no significant change in the palatal dimensions between the unilateral and bilateral types of CB. Among the palatal dimensions, the PIL had the most significant association (R2 = 0.53) with SDA and CB. There was a significant correlation between the palatal dimensions and SDA when CB was present along with NSD. Conclusion Based on the results of this study, it can be concluded that the presence of NSD and CB have a significant effect on the palatal dimensions and, therefore, they may be associated with skeletal malocclusion.

scholarly journals Study of Prevalence of Concha Bullosa, Nasal Septal Deviation and Sinusitis based on CT Findings

2020 ◽  
Vol 26 (1) ◽  
pp. 18-23
Author(s):  
Salah Uddin Ahmmed ◽  
Md Nazrul Islam Khan ◽  
Md Zakir Hossain ◽  
Md Khairul Islam Mridha ◽  
Anower Parvez Bhuiyan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Head And Neck ◽  
Anatomical Variations ◽  
Neck Surgery ◽  
Septal Deviation ◽  
Concha Bullosa ◽  
Sinus Disease ◽  
Nasal Septal Deviation ◽  
Pathological Conditions

The anatomical variations and pathological conditions of the sinonasal area can be easily identified using computed tomography (CT) scan. The study was done to observe the prevalence of concha bullosa (CB) and nasal septal deviation (DNS) in sinusitis patients. 135 CT scan of nose and paranasal (PNS) sinuses were taken and reviewed retrospectively for the presence of concha bullosa, nasal septal deviation and sinusitis in the department of Otolaryngology, Head and Neck Surgery, Border Guard Hospital, Dhaka from March 2019 to January 2020. Out of 135 patients, CT scan of nose and PNS revealed 74.81% patients exhibited some sinus disease, 68.14% nasal septal deviation and 42.22% had concha bullosa. In this study, we have done a retrospective analysis of the CT scan of PNS in order to assess the prevalence CB, DNS and sinusitis. Bangladesh J Otorhinolaryngol; April 2020; 26(1): 18-23

Do Anatomic Variations of the Middle Turbinate Have an Effect on Nasal Septal Deviation or Paranasal Sinusitis?

2011 ◽  
Vol 120 (9) ◽  
pp. 569-574 ◽  
Author(s):  
Jae Hoon Cho ◽  
Mun-Su Park ◽  
Yong Soo Chung ◽  
Seok-Chan Hong ◽  
Kui Hyang Kwon ◽  
...  
Keyword(s):  
Middle Turbinate ◽  
Septal Deviation ◽  
Anatomic Variations ◽  
Nasal Septal Deviation ◽  
Paranasal Sinusitis

scholarly journals Evaluation of the Prevalence of Concha Bullosa in Cone-Beam Computed Tomography Images

2020 ◽  
Vol 12 (3) ◽  
pp. 93-96
Author(s):  
Nasim Shams ◽  
Bahareh Shams ◽  
Zahra Sajadi
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Middle Turbinate ◽  
Cone Beam ◽  
P Value ◽  
Concha Bullosa ◽  
Computed Tomography Images ◽  
Significant Difference ◽  
And Gender ◽  
Sinus Ostium

Background: The ostiomeatal complex (OMC) is not a separate anatomical structure although it is a functional unit of structures, including the middle meatus, uncinate process, infundibulum, maxillary sinus ostium, ethmoidal bulla, anterior ethmoid sinus ostium, and frontal recess. Concha bullosa is the pneumatization of the concha, which is one of the most common anatomical variations in the middle turbinate. Methods: This study was conducted using the cone-beam computed tomography (CBCT) images of 172 patients in the archives of the Department of Oral and Maxillofacial Radiology, Dentistry School, Ahvaz Jundishapur. Patient information including age and gender, presence or absence of concha bullosa, the involved side (left or right), and its type (i.e., extensive, lamellar, and bulbous) were collected in the information form. Finally, the chi-square test (with SPSS, version 22) was used to analyze the data, and P value less than 0.05 was considered statistically significant. Results: Patients with and without concha bullosa were 39.1 and 41.7 years, respectively, but it was no significant difference in terms of age (P = 0.321). Out of 52 patients with concha bullosa, 19 (36.5%) cases were males and 33 (63.5%) of them were females. The prevalence of concha bullosa was higher for the bilateral side (20 patients, 38.5%, P = 0.000). The prevalence of bulbulsand lamellar-shape was nearly the same (32.7% and 30.8%, respectively). Eventually, the extensive shape with 36.5% was more frequent for the shape of concha bullosa (P = 0.000). Conclusions: The prevalence of concha bullosa was high. There was no significant difference in terms of age (P = 0.321) and gender (P = 0.058) of patients with concha bullosa. The extensive type and the bilateral appearance of concha bullosa were more significant (P = 0.000).

An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans

2020 ◽  
Vol 134 (4) ◽  
pp. 328-331 ◽  
Author(s):  
P Parmar ◽  
A-R Habib ◽  
D Mendis ◽  
A Daniel ◽  
M Duvnjak ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Computed Tomography ◽  
Diagnostic Accuracy ◽  
Convolutional Neural Network ◽  
Middle Turbinate ◽  
Concha Bullosa ◽  
Computed Tomography Images ◽  
Computed Tomography Scans ◽  
Neural Network Algorithm

AbstractObjectiveConvolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algorithm that can reliably determine if the middle turbinate is pneumatised (concha bullosa) on coronal sinus computed tomography images.MethodConsecutive high-resolution computed tomography scans of the paranasal sinuses were retrospectively collected between January 2016 and December 2018 at a tertiary rhinology hospital in Australia. The classification layer of Inception-V3 was retrained in Python using a transfer learning method to interpret the computed tomography images. Segmentation analysis was also performed in an attempt to increase diagnostic accuracy.ResultsThe trained convolutional neural network was found to have diagnostic accuracy of 81 per cent (95 per cent confidence interval: 73.0–89.0 per cent) with an area under the curve of 0.93.ConclusionA trained convolutional neural network algorithm appears to successfully identify pneumatisation of the middle turbinate with high accuracy. Further studies can be pursued to test its ability in other clinically important anatomical variants in otolaryngology and rhinology.

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