scholarly journals DISTRIBUTION OF ANATOMIC VARIATIONS OF THE NOSE AND PARANASAL SINUSES IN KASHMIRI POPULATION BY COMPUTED TOMOGRAPHY SCAN ANALYSIS.

2021 ◽  
pp. 58-60
Author(s):  
Owais Makhdoomi ◽  
Syed Waseem Abass ◽  
Majid Ul Islam Masoodi
Keyword(s):  
Computed Tomography ◽  
Paranasal Sinuses ◽  
Anatomic Variation ◽  
Disease Process ◽  
Inferior Turbinate ◽  
Anatomic Variations ◽  
Wide Range ◽  
Preoperative Ct ◽  
Kashmiri Population ◽  
Nose And Paranasal Sinuses

Background: Knowledge of anatomy constitutes an integral part of the total management of patients with sinonasal diseases. The aim of this study was to obtain the prevalence of sinonasal anatomic variations in the Kashmiri population and to understand their importance and impact on the disease process, as well as their influence on surgical management and outcome. Materials and Methods: This study is a prospective review of retrospectively performed normal computed tomography (CT) scans of the nose and paranasal sinuses in the adult Kashmiri population at SMHS Hospital. The scans were reviewed by two independent observers. Results: The most common anatomic variation after excluding agger nasi cells were pneumatized Crista Galli, which was seen in 69% of the scans. However, the least common variation seen in this series was Pneumatized inferior turbinate, which was encountered in 1.1 % of the cases. Conclusion: A wide range of regional differences in the prevalence of each anatomic variation exists. Understanding the preoperative CT scan is substantially important because it is the roadmap for the sinus surgeon. Detection of anatomic variations is vital for surgical planning and the prevention of complications.

scholarly journals ANATOMIC VARIATION OF CT SCAN IN CHRONIC RHINOSINUSITIS PATIENTS IN SANGLAH PROVINCIAL GENERAL HOSPITAL

2019 ◽  
Vol 12 (04) ◽  
pp. 2083-2086
Author(s):  
Luh Made Ratnawati ◽  
I Putu Yupindra Pradiptha
Keyword(s):  
General Hospital ◽  
Chronic Rhinosinusitis ◽  
Paranasal Sinuses ◽  
Anatomic Variation ◽  
Anatomical Variation ◽  
Operative Procedure ◽  
Septal Deviation ◽  
Anatomic Variations ◽  
Ostiomeatal Complex ◽  
Nose And Paranasal Sinuses

The anatomical abnormalities of the nose and paranasal sinuses are the most common causes of rhinosinusitis. These anatomical variations can cause obstruction of the ostiomeatal complex (OMC) and interfere with the mucociliary clearance which allows the occurrence of chronic rhinosinusitis. Knowing the anatomic variations of the nose and paranasal sinuses in rhinosinusitis patients whose undergo operative procedure at Sanglah Provincial General Hospital is important because it can be used as a reference for proper intervention to treat rhinosinusitis. This research is a descriptive study in the Ear Nose Throat - Head Neck Departement, Udayana University Medical School / Sanglah Provincial General Hospital Denpasar, from January 2018 to December 2018. The research location is at the ENT clinic, Sanglah Hospital, Denpasar. This research will be conducted in approximately 2 months (January 2019 to February 2019). The sample from this study was all rhinosinusitis patients who underwent operative procedure, both male and female for the period of 1 January – 31 December 2018. Based on the results of the research data, it was found that the most anatomic variation was septal deviation which was 24 people Anatomic variations cause chronic sinusitis by causing obstruction in the ostiomeatal complex (OMC) and affecting the mucociliary transport pattern. The most anatomical variation in this study is septal deviation.

scholarly journals Aplasia and agenesis of the frontal sinus in individual of southern region in Saudi Arabia

2021 ◽  
Vol 7 (5) ◽  
pp. 821
Author(s):  
Radeif Shamakhi ◽  
Musleh Mubaraki ◽  
Ramzi Dighriri ◽  
Azza Almarir ◽  
Alaa Alyahya
Keyword(s):  
Computed Tomography ◽  
Saudi Arabia ◽  
Paranasal Sinuses ◽  
Frontal Sinus ◽  
Southern Region ◽  
Ct Scans ◽  
Anatomic Variations ◽  
Computed Tomography Scans ◽  
Preoperative Ct ◽  
Frontal Sinuses

<p class="abstract"><strong>Background:</strong> The aim of this study was to demonstrate the prevalence of anatomic variations of frontal sinus in people of southern region in Saudi Arabia.</p><p class="abstract"><strong>Methods:</strong> This study used a retrospective radiological design to analyze computed tomography scans of 117 patients aged between 18 and 80 years of southern region in Saudi Arabia were used in this study. Patients with altered anatomy (iatrogenic or pathological) were excluded, CT scans were analyzed to demonstrate the incidence of anatomic variations of frontal sinus in people of southern region in Saudi Arabia.</p><p class="abstract"><strong>Results:</strong> The study included 117 patients, 75 of whom were males (64%) and 42 of whom were females (36%) with ages ranging from 18 to 80 years. The prevalence of bilateral frontal sinus aplasia is 5.9 % and 3.4% is in the unilateral frontal sinus.</p><p class="abstract"><strong>Conclusions:</strong> These figures on frontal sinus aplasia are critical in convincing surgeons to perform a preoperative CT scan of the paranasal sinuses and concentrate on the appearance of frontal sinuses on CT images to avoid unwanted complications during sinus surgeries.</p><p class="abstract"> </p>

scholarly journals Development of a fully automatic deep learning system for L3 selection and body composition assessment on computed tomography

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiyeon Ha ◽  
Taeyong Park ◽  
Hong-Kyu Kim ◽  
Youngbin Shin ◽  
Yousun Ko ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Anatomic Variation ◽  
External Validation ◽  
Abdominal Muscle ◽  
Anatomic Variations ◽  
Success Rates ◽  
Technical Success ◽  
Segmentation Accuracy ◽  
Distance Difference ◽  
Fully Automatic

AbstractAs sarcopenia research has been gaining emphasis, the need for quantification of abdominal muscle on computed tomography (CT) is increasing. Thus, a fully automated system to select L3 slice and segment muscle in an end-to-end manner is demanded. We aimed to develop a deep learning model (DLM) to select the L3 slice with consideration of anatomic variations and to segment cross-sectional areas (CSAs) of abdominal muscle and fat. Our DLM, named L3SEG-net, was composed of a YOLOv3-based algorithm for selecting the L3 slice and a fully convolutional network (FCN)-based algorithm for segmentation. The YOLOv3-based algorithm was developed via supervised learning using a training dataset (n = 922), and the FCN-based algorithm was transferred from prior work. Our L3SEG-net was validated with internal (n = 496) and external validation (n = 586) datasets. Ground truth L3 level CT slice and anatomic variation were identified by a board-certified radiologist. L3 slice selection accuracy was evaluated by the distance difference between ground truths and DLM-derived results. Technical success for L3 slice selection was defined when the distance difference was < 10 mm. Overall segmentation accuracy was evaluated by CSA error and DSC value. The influence of anatomic variations on DLM performance was evaluated. In the internal and external validation datasets, the accuracy of automatic L3 slice selection was high, with mean distance differences of 3.7 ± 8.4 mm and 4.1 ± 8.3 mm, respectively, and with technical success rates of 93.1% and 92.3%, respectively. However, in the subgroup analysis of anatomic variations, the L3 slice selection accuracy decreased, with distance differences of 12.4 ± 15.4 mm and 12.1 ± 14.6 mm, respectively, and with technical success rates of 67.2% and 67.9%, respectively. The overall segmentation accuracy of abdominal muscle areas was excellent regardless of anatomic variation, with CSA errors of 1.38–3.10 cm2. A fully automatic system was developed for the selection of an exact axial CT slice at the L3 vertebral level and the segmentation of abdominal muscle areas.

scholarly journals Anatomical variations of intra-sphenoid sinus septations in a sample of Kashmiri population: a non-contrast computed tomography study

2019 ◽  
Vol 7 (5) ◽  
pp. 1445
Author(s):  
Abdul Haseeb Wani ◽  
Yassar Shiekh ◽  
Arshed Hussain Parry ◽  
Zahid Qayoom
Keyword(s):  
Computed Tomography ◽  
Skull Base ◽  
Sphenoid Sinus ◽  
Anatomical Variations ◽  
Carotid Canal ◽  
Preoperative Ct ◽  
Kashmiri Population ◽  
Glandular Structures ◽  
The Right ◽  
Age Range

Background: The sphenoid sinus shows multitude of variations in pneumatization, size and pattern of septations leading to differences in its segmentation. Pre-operative knowledge of their attachment especially to posterolateral bony walls covering vital structures is of utmost importance for a safe trans-sphenoidal approach for various surgical procedures involving skull base. Non-contrast computed tomography (NCCT) with its ability to provide multiplanar reformations (MPR) with sharp algorithms is now a reference standard for visualization of these intra-sphenoid sinus septations preoperatively. The objective of this study was to determine the number and attachment of intra-sphenoid sinus septations in a Kashmiri population sample.Methods: NCCT head images of 591 patients in the age range of 16 to 75 years were analyzed retrospectively. Individuals with age less than 16 years, previous surgery involving skull base/sphenoid sinus, trauma causing hem sinus/fractures around skull base or having space occupying lesions around skull base/sphenoid sinus were excluded from the study. On the CT workstation multi-planar coronal, sagittal and axial reconstructions were performed and subsequently examined.Results: The age range was 16 to 75 years with mean age of 43.56 years of which 453 (76.6%) were males and 138 (23.4%) were females. Single intra-sphenoid septation was the most common anatomic variant in present study (79.7%) being complete in 71.7% and partial or incomplete in 8% of the examined subjects. Double septa were found in 11% inpresent study and more than 2 septae in 3.4%. After sellar attachment (51%) the next most common site of attachment was to the carotid canal (29.5%) (23% to left ICA and 6.5% to the right ICA).Conclusions: Intricate knowledge about sphenoid sinus, its pneumatization and anatomical variations in intra-sphenoid sinus septations and its relationship with the surrounding vital structures is of utmost importance before performing any endoscopic/open surgery involving skull base via trans-sphenoidal approach. The present study shows that a significant percentage of septal attachment to the carotid canal makes main sphenoidal septum as not so reliable landmark for endoscopic procedures as used to be in the pre-imaging era. Thus, preoperative CT is mandatory to avoid injuries to para-sellar neurovascular and glandular structures.

scholarly journals Total Aplasia of the Paranasal Sinuses

2013 ◽  
Vol 4 (2) ◽  
pp. ar.2013.4.0056 ◽  
Author(s):  
Hakan Korkmaz ◽  
Mukadder Korkmaz
Keyword(s):  
Computed Tomography ◽  
Paranasal Sinus ◽  
Paranasal Sinuses ◽  
High Rate ◽  
Anatomic Variations ◽  
Structural Variations

Although a variety of theories have been proposed about functions of the paranasal sinuses, not one is clear today. Nonetheless, paranasal sinus–related diseases are associated with a high rate of morbidities. Therefore, it is essential to identify the structure and pathophysiology of the paranasal sinuses. Computed tomography (CT) is a valuable tool displaying anatomic variations and diseases. Because paranasal sinus development is a complex and long-lasting process, there are great structural variations between individuals. Several degrees and combinations of aplasias and hypoplasias have been reported; however, there is only one case of total paranasal sinus aplasia in the literature. Here, we present the second case of total paranasal sinus aplasia. Paranasal sinus development, functions of the paranasal sinuses, and the role of CT were evaluated.

Vascular leiomyoma of the inferior turbinate–report of a case and review of the literature

1988 ◽  
Vol 102 (12) ◽  
pp. 1159-1160 ◽  
Author(s):  
G. S. Hanna ◽  
A. B. Akosa ◽  
M. H. Ali
Keyword(s):  
Smooth Muscle ◽  
Nasal Obstruction ◽  
Paranasal Sinuses ◽  
Facial Pain ◽  
English Literature ◽  
Inferior Turbinate ◽  
Review Of The Literature ◽  
Vascular Leiomyoma ◽  
Nose And Paranasal Sinuses ◽  
Benign Tumours

AbstractLeiomyoma of the nose and paranasal sinuses is rare. It constitutes about 1 per cent of all benign tumours. This is due to the paucity of smooth muscle in the nose.In this paper, the authors present one case of vascular leiomyoma which arose in the inferior turbinate in a 64-year-old lady. It was treated by partial turbinectomy with the relief of her symptoms of nasal obstruction, epistaxis and facial pain.The English literature on the topic is reviewed.

scholarly journals Concha Bullosa in Paradoxical Middle Turbinate: A New Variation

2016 ◽  
Vol 9 (3) ◽  
pp. 141-142 ◽  
Author(s):  
Mohammad W El-Anwar ◽  
Ahmed I Ali
Keyword(s):  
Computed Tomography ◽  
Ct Scan ◽  
Laboratory Tests ◽  
Anatomic Variation ◽  
Middle Turbinate ◽  
Anatomic Variations ◽  
Concha Bullosa ◽  
Normal Limits ◽  
Osteomeatal Complex ◽  
The Right

ABSTRACT Introduction Concha bullosa is the most common anatomic variation of osteomeatal complex region that is generally seen in the middle turbinate (MT). Materials and methods A 25-year-old male presented with headache and nasal obstruction. Computed tomography (CT) scan documented right paradoxical MT. The right MT also showed aerated concha bullosa with narrow right osteomeatal area. Routine preoperative laboratory tests were within normal limits. Results This case of concha bullosa in paradoxically bent MT was reported, described, and could be safely managed endoscopically. Patient was symptom free up to date without any complication, recurrence, or other pathology. Conclusion Computed tomography may easily identify such uncommon anatomic variations of the osteomeatal region. This directs the surgeon attention to these variations as a cause of headache and osteomeatal area obstruction. How to cite this article El-Anwar MW, Ali AI. Concha Bullosa in Paradoxical Middle Turbinate: A New Variation. Clin Rhinol An Int J 2016;9(3):141-142.

Sign in / Sign up

Export Citation Format

Share Document