TY - JOUR T1 - EP461 The role of certain morphological and doppler velocimetric ultrasonographic criteria in the prediction of adnexal mass malignancy JF - International Journal of Gynecologic Cancer JO - Int J Gynecol Cancer SP - A293 LP - A293 DO - 10.1136/ijgc-2019-ESGO.520 VL - 29 IS - Suppl 4 AU - M Tanturovski AU - I Aluloski AU - S Stojcevski AU - V Jovanovska Y1 - 2019/11/01 UR - http://ijgc.bmj.com/content/29/Suppl_4/A293.3.abstract N2 - Introduction/Background To evaluate the diagnostic performance of certain morphological and Doppler parameters in the preoperative distinction of benign and malignant adnexal masses.Methodology We recruited patients that had a newly diagnosed unilateral adnexal mass with no previously recorded gynecologic malignancy and were scheduled for surgery at the Department. We recorded the following morphologic characteristics, in accordance with the terms and measurements described by the IOTA group: tumor morphology (cystic, complex, solid), presence of septa, presence of papillary projections, presence of wall irregularities and presence of ascites. After the detailed gray-scale ultrasound evaluation of the morphology of the mass, we created Doppler flow velocity curves to calculate the PSV, TAMXV, RI and PI, in accordance with the IOTA criteria.Results We recruited a total of 216 patients; the pathohistology revealed benign tumors in 77.31% of patients, bordeline tumors in 0.93% and malignant neoplasms in 21.76% of patients. The presence of a unilocular cystic tumor reduced the risk of malignancy by LR+ 0.95. Solid tumor morphology was almost universally associated with malignant neoplasms, increasing the risk of cancer by LR+ 5.04. The presence of septa, wall irregularities and papillary projections were also suggestive of malignancy with LR+ of 8.03, 19.88 and 5.02, respectively. The risk of malignancy was higher in tumors with RI ≤0.4 (specificity 98.8%. LR+ 64.76). Most malignant tumors had PI <1.0 (LR+ 6.63). The criteria based solely on flow velocities performed worse than the indices in our series.Conclusion It is very likely that the set of characteristics that we described could be useful for teaching purposes, particularly for clinicians with limited experience in diagnosing ovarian tumors, a process that is automated for experts. The data suggests that these simple morphological traits can be used to characterize the majority of ovarian tumors with a high degree of accuracy.Disclosure Nothing to disclose. ER -