DIAGNOSTIC ACCURACY OF HRCT TEMPORAL BONE IN THE DIAGNOSIS OF CHOLESTEATOMA TAKING HISTOPATHOLOGY AS GOLD STANDARD

OBJECTIVE: To find out the diagnostic accuracy of HRCT temporal bone in the diagnoses of cholesteatoma taking histopathology as the gold standard. MATERIALS AND METHODS: A cross-sectional study was done in the department of Diagnostic Radiology, Lahore General Hospital/PGMI Lahore, Pakistan. The duration of the study was six months. 111 was the sample size calculated using the WHO calculator with a sensitivity of 80.67%, specificity of 88%, confidence interval of 95% and 10% margin of error. The sample was collected using the Non-Probability sampling technique. Inclusion criteria included age from 6 months to 60 years; both genders were included, and diagnosed cases of chronic supportive otitis media as per operational definitions. Data analysis was done using SPSS version 22. Data was stratified based on gender, age, BMI and duration off symptoms. Diagnostic performance was calculated post-stratification. RESULTS: This study highlights the significant role of High-Resolution Computed Tomography (HRCT) in diagnosing cholesteatoma, demonstrating an overall diagnostic accuracy of 87.4%. With a sensitivity of 89.5%, HRCT proves to be highly effective in detecting true cases, though its specificity of 75% suggests that histopathological confirmation is still essential in certain cases to rule out false positives. The positive predictive value (95.5%) indicates a strong ability to correctly diagnose cholesteatoma, while the negative predictive value (54.5%) underscores the possibility of missed cases, reinforcing the need for further evaluation in negative HRCT findings. Stratification analysis revealed slightly improved accuracy in males (88.2%) and in patients experiencing symptoms for five or more years (89.1%). CONCLUSION: HRCT significantly aids in the early detection and evaluation of cholesteatoma, it should be used in conjunction with histopathological examination for definitive diagnosis. Further research incorporating larger sample sizes and emerging imaging techniques, such as diffusion-weighted MRI, may enhance diagnostic precision and improve patient management in the future.