دورية أكاديمية

Accuracy of Computed Tomography in characterizing the paranasal fungal infection

التفاصيل البيبلوغرافية
العنوان: Accuracy of Computed Tomography in characterizing the paranasal fungal infection
المؤلفون: Irfan Amjad Lutfi, Naresh Maheswari, Deepa Devi, Faisal Iqbal Afridi
المصدر: Pakistan Journal of Medicine and Dentistry, Vol 4, Iss 4 (2024)
بيانات النشر: ziauddin University, 2024.
سنة النشر: 2024
المجموعة: LCC:Biochemistry
LCC:Dentistry
LCC:Therapeutics. Pharmacology
LCC:Medicine (General)
مصطلحات موضوعية: Biochemistry, QD415-436, Dentistry, RK1-715, Therapeutics. Pharmacology, RM1-950, Medicine (General), R5-920
الوصف: Background: To determine the diagnostic accuracy of CT in characterizing the Paranasal fungal Infection Methods: All patients suspected of having Paranasal fungal infection underwent CT scan examination on 4 slice Toshiba Asteion multislice CT scanner. Final diagnosis was based on smear analysis for fungal culture which was done subsequently. Statistical analysis was performed by SPSS version-17. Results: Out of 65 patients, 48 were confirmed having fungal sinusitis and remaining 17 were negative on the gold standard culture analysis. While on CT, 44 patients were positive for fungal sinusitis and four patients had a normal scan (false negative). Out of 17 patients, 14 patients were also negative on CT and three were positive for fungal infection (false positive). Sensitivity of CT was 93.6% and accuracy was 89.2%. Conclusion: CT scan is highly accurate in diagnosing and characterizing paranasal fungal infection. CT scan also guides in defining disease extent as well as aids in deciding the surgical approach to be used. Key Words: Paranasal Sinuses. Computed Tomography. Culture Analysis. Magnetic Resonance Imaging
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2313-7371
2308-2593
Relation: https://ojs.zu.edu.pk/pjmd/article/view/2965; https://doaj.org/toc/2313-7371; https://doaj.org/toc/2308-2593
URL الوصول: https://doaj.org/article/46308311f71a41ed8cddf419be46a137
رقم الأكسشن: edsdoj.46308311f71a41ed8cddf419be46a137
قاعدة البيانات: Directory of Open Access Journals