Document Type : Original Article

Authors

1 Eye Research Center, Department of Eye, Amiralmomenin Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.

2 Poursina Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran

3 Associate Professor of Biostatistics Department of Biostatistics, School of Health Road Trauma Research Center Guilan University of Medical Sciences

Abstract

Backgrounds: External dacryocystorhinostomy (DCR) failure is sometimes due to pathologies located within the nasal cavity. Preoperative computerized tomography (CT) scan is useful in the assessment of nasolacrimal drainage and adjacent anatomical structures; however, it is not routinely performed before DCR. The present study evaluates abnormal findings in CT scans of patients with nasolacrimal duct obstruction (NLDO) and its effect on changing treatment approaches.
Methods: This prospective descriptive cross-sectional study included 162 patients with NLDO. All the patients underwent a supine axial CT scan. Patients with signs of rhinosinusitis, sinus mucositis, nasal septal deviation, nasal polyps or masses, and turbinate deformities were referred to an otolaryngologist. The rest of the patients underwent external DCR. The demographics and radiologic characteristics of the patients undergoing CT scans and their effect on changing treatment approaches were evaluated.
Results: The study participants included 162 patients with a mean±SD age of 62.5±14.0 years (age range of 35-93 years). The percentage of endonasal DCR in cases with an abnormal nasal cavity on CT scan was almost 30% higher compared to those without this problem (59.6% vs. 30.2%). Septum deviation and turbinate deformity led to 3.6-fold and 3.9-fold changes in the surgical approach, respectively.
Conclusion
A significant association existed between the sinonasal pathologies in patients with NLDO and changing surgical approaches. It is believed that a preoperative CT scan is necessary to detect such pathologies and manage them appropriately.

Highlights

Abdolreza medghalchi(google scholar)(pubmed)

Yousef Alizadeh(google scholar)(pubmed)

Maryam Dourandeesh(google scholar)(pubmed)

Sima Fallah Arzpeima(google scholar)(pubmed)

Reza Soltani Moghadami(google scholar)(pubmed)

Mitra Akbari(google scholar)(pubmed)

 Ehsan Kazemnezhad Leyli(google scholar)(pubmed)

 

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