Abstract

Objectives: To assess the diagnostic accuracy of different risk of malignancy index (RMI) scores and to evaluate the role of a modified RMI (RMI 5) in pre-operative discrimination between benign and malignant ovarian masses. Study Design: Prospective observational study. Patients and methods: Women with a suspicious ovarian mass scheduled for laparotomy or laparoscopy were potentially eligible for inclusion in the current study. Trans-abdominal and trans-vaginal ultrasound with Doppler assessment of the adnexal masses was done. Calculation of the RMI 1, RMI2, RMI 3, RMI 4, and RMI5 was done. We compared RMI to histopathological outcome. In the current study, a new RMI score was created by adding Doppler blood flow of the ovarian mass to the calculation of the previous RMI1. Results: One hundred and fifty women with ovarian masses were included in the current study. Ninety six women (64%) had benign ovarian masses while, malignant ovarian masses were found in 54 women (36%). Comparison between benign and malignant ovarian masses regarding to the risk of malignancy indices revealed that that there was a statistically significant difference between the two groups regarding to the risk of malignancy indices with Pvalue< 0.001. Receiver operator characteristic curve analysis of the 5 RMI indices shows that the best method for prediction of malignant ovarian tumor was RMI 1. Also there was no statistically significant difference between the five methods in prediction of malignant ovarian tumors. RMI5 with cut off value of 250 is reliable tool at a tertiarycenter to discriminate between ovarian cancer and benign ovarian masses with a sensitivity of 90.38% and specificity of 93.88%. There was statistically significant difference between the different stages of ovarian cancer and RMI 5 with (P<0.05). Conclusion: The RMI 1 is the gold standard for preoperative discrimination between benign and malignant ovarian masses. Adding Doppler flow to the parameters of RMI 1 (RMI 5) increased specificity of RMI 1 in detecting malignant ovarian masses.

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