Background: Ovarian cancer remains a leading cause of gynecological cancer mortality due to its typically late-stage diagnosis. Current diagnostic methods include ultrasonography (USG) and computed tomography (CT), with CT generally favored for its higher sensitivity and specificity. However, CT's limited availability in resource-poor settings raises the need to assess USG’s diagnostic viability in detecting advanced ovarian malignancies. This study aims to compare the diagnostic accuracy of USG and CT in detecting adnexal masses, ascites, lymph node involvement, omental cake, and distant metastasis in advanced-stage ovarian cancer.Method: A cross-sectional comparative study was conducted at Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia, from January 2021 to December 2023. The study included 70 patients with histologically confirmed advanced ovarian cancer (FIGO stages III and IV) who underwent both USG and CT before surgical intervention. Diagnostic performance measures, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated for each modality, using surgical findings as the gold standard. Statistical analysis was performed using SPSS software, with significance set at p 0.05.Results: Both imaging methods demonstrated high specificity (100%) and PPV for adnexal mass detection, indicating reliability in confirming positive cases. However, CT showed superior sensitivity and accuracy across most parameters, particularly for ascites (sensitivity: 93.94%), lymph node involvement (56%), and distant metastases (36.67%). In comparison, USG had lower sensitivity, especially for distant metastases (6.67%), but maintained high specificity. These findings suggest that while USG is effective for initial assessment, CT is preferred for detailed staging.Conclusion: This study confirms CT’s superiority over USG in comprehensive ovarian cancer staging, particularly for detecting metastatic indicators. However, USG’s accessibility and affordability support its role as an initial diagnostic tool, especially in resource-limited settings. A multimodal approach, integrating USG for preliminary screening with CT for confirmation, may optimize diagnostic outcomes. Further research should focus on enhancing USG’s sensitivity to bridge the diagnostic gap in underserved regions.
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