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Anatomical Variations Detected in Computed Tomography of the Paranasal Sinuses

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Anatomical variations of the paranasal sinuses are common and clinically significant, particularly in the context of chronic rhinosinusitis and endoscopic sinus surgery. Accurate identification of these variants is essential to prevent surgical complications. Computed tomography (CT) is the preferred imaging modality for evaluating these variations due to its superior visualization of bony anatomy. Aim: was to review the anatomical variations of the paranasal sinuses and their prevalence as detected by computed tomography. Patients and methods: This cross-sectional study was conducted at Benha University Hospital between 2022 and 2023. A total of 185 patients aged 15–77 years, undergoing CT scans of the nose and paranasal sinuses for various pathologies, were included using a random sampling technique. Exclusion criteria included postoperative status, trauma, sinonasal neoplasms, and pregnancy. Multi-detector CT scans in axial, coronal, and sagittal planes were used to evaluate anatomical variations and sinus pathology. Results: A total of 185 patients underwent CT evaluation of the nose and paranasal sinuses. The mean age was 47.2 ± 18.8 years, and 63.8% were males. Anatomical variations included concha bullosa (64.9%), agger nasi cells (97.8%), Haller cells (42.2%), paradoxical middle turbinates (16.2%), Onodi cells (10.8%), and deviated uncinate process (29.8%). Among concha bullosa cases, the lamellar type was most common (64.2%). Most agger nasi and concha bullosa cases were bilateral (71.8% and 61.6%, respectively). Absent frontal sinuses were found in 9.2% of cases.Conclusion: CT imaging provides a reliable and detailed assessment of paranasal sinus anatomy, enabling the identification of anatomical variations with clinical relevance.
Authors: Riyadh Mohammed Hanoon, Mohamed Awaad Tawfik, Hisham Elsayed Alsheikh
Institution: Benha University
Language: English
Subfield: Surgery
Field: Medicine
Open Access status: bronze
OpenAlex ID: W4417532986
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