[The use of 2-dimensional and 3-dimensional color and power-Doppler in the diagnosis of blood flow indices of adnexal tumors].

OBJECTIVES

The purpose of this study was to compare 2-dimensional and 3-dimensional color and power-Doppler as measured with blood flow indices for the prediction of malignancy in complex adnexal masses.

METHODS

Two hundred eighty women with complex adnexal masses (mean age, 46,3 years (range, 13-83 years) were evaluated by 2-dimensional and 3-dimensional power-Doppler imaging. Complex adnexal mass was defined as the presence of at least one of the following features: solid areas, thick papillary projections, thick septa, or purely solid echogenicity. Tumor volume, sonomorphology and Doppler indices (PI, RI), as well 3-dimensional power-Doppler assessment (VI, FI, VFI) were calculated. All tumors were surgically removed and definitive histological diagnosis was obtained in each case. Diagnostic accuracy and areas under ROC curve (AUROC's) were calculated for each test.

RESULTS

Seventy one tumors (25.3%) were proved to be malignant, and 209 tumors (74.7%) were proved to be benign. Statistically significant differences between benign and malignant tumors were found for PI (1.06 vs 0.76; p = 0.001), RI (0.62 vs 0.51; p = 0.002), VI (0.55 vs 1.52; p = 0.002) oraz VFI (0.18 vs 0.49; p = 0.001). However, the highest sensitivity of 3D indices for malignant tumor detection was found for FI (42.9%). Specificity of 2D and 3D indices was between 93.6% for VI to 98.2% for RI. Accuracy and positive and negative predictive values were fund to be between 66.8% to 79.8%, respectively. AUROC's analysis indicated that the most useful test for the discrimination between benign and malignant tumors was VI followed by VFI and PI with RI.

CONCLUSION

Three-dimensional power-Doppler imaging has diagnostic potential for the discrimination of benign and malignant complex adnexal masses, but specific, possibly most vascularised areas of each tumor have to be examined in detail to improve not yet satisfactory predictive values of this method.