Determination of A CT Scan Scoring System As A Predictor Of Malignancy in Mucinous Ovarian Tumors With Histopathological Correlation

Abstract

Background: Mucinous ovarian tumors have diverse radiological characteristics and can make it difficult to differentiate benign, borderline, and malignant tumors preoperatively. CT Scan is one of the main modalities in the evaluation of ovarian masses, but its interpretation can be subjective. Therefore, a scoring system based on CT Scan characteristics is needed to help predict the degree of malignancy of mucinous ovarian tumors.

Objective: To determine a scoring system based on CT Scan characteristics as a preoperative diagnostic aid to differentiate mucinous ovarian tumors into benign, borderline, and malignant categories based on correlation with histopathology results.

Methods: This was an observational analytic study with a retrospective cross-sectional design and a diagnostic test. The study involved 120 patients with mucinous ovarian tumors who underwent contrast-enhanced abdominal CT Scan and were confirmed by histopathological examination at RSUD Dr. Soetomo Surabaya from January 2020 to March 2026. The CT Scan characteristics analyzed included morphology, wall thickness, septa, solid component, enhancement pattern, and tumor margin. Analysis was performed using bivariate tests and ordinal logistic regression, and the performance of the scoring system was then evaluated using the Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC), sensitivity, and specificity.

Results: Multivariate analysis showed that solid component, enhancement pattern, and tumor margin were predictors significantly associated with the degree of malignancy based on histopathology. The scoring system assigns 2 points for the presence of a solid component, 1 point for mild, 3 points for moderate and strong enhancement, and 2 points for an irregular tumor margin, with a score range of 0-8. To differentiate malignant from non-malignant tumors, an AUC of 0.933 (95% CI: 0.885-0.982; p < 0.001) was obtained with a cut-off of ≥4 (sensitivity 90.7%, specificity 89.4%). To differentiate borderline from benign tumors, an AUC of 0.908 (95% CI: 0.858-0.959; p < 0.001) was obtained with a cut-off of ≥2 (specificity 100%).

Conclusion: A scoring system based on CT Scan characteristics, comprising solid component, enhancement pattern, and tumor margin, can be used as an aid for stratifying the malignancy of mucinous ovarian tumors in preoperative evaluation. External validation in larger, multicenter cohorts is needed before wider clinical use of the scoring system.