OBJECTIVE: To assess the performance of a power doppler vascularity index in the preoperative diagnosis of @entity43 . @entity1 AND METHODS: Two successive series of @entity4134 (N=101 and N=82) were examined prospectively with power Doppler before surgical treatment. A vascularity index, called Power Doppler Index (PDI), based on the number of colored pixels, was estimated on selected frames (defined region of interest covering the entire @entity5 ) of the @entity5 using an in house color-quantifying program. The first study was monocentric to test the inter- and intraobserver reproducibilities and the availability of the parameter. The second was multicentric to validate the first results. The sensitivity and specificity of PDI, resistance index (RI) and subjective visual scoring were compared using receiver operating characteristic (ROC) curves. RESULTS: Histology identified 23 malignant and 78 benign lesions in the first study and 34 malignant and 48 @entity5 in the second. PDI was considerably higher in malignant than in benign lesions (0.34+/-0.04 vs 0.12+/-0.06 (P<0.001)). Intra-observer and interobserver variability of PDI was low (intraclass correlation coefficients estimated at 0.99 and 0.98, respectively). The PDI cut-off value for differential diagnosis was set at 0.265 (26.5% of the @entity5 is colored) in the first study and 0.107 in the second. Sensitivity and specificity were 100% (95% CI [87.8; 100.0]) and 97.4% (95% CI [91.0; 99.7]), respectively, for PDI in the first study compared to 75% (95% CI [72.9; 90.7]) and 60% (95% CI [56.3; 92.5]) in the second study. Using logistic regression, visual Doppler scoring performed best. DISCUSSION AND CONCLUSION: The Power Doppler Index obtained using our color quantifying software has discriminating power for @entity4134 but visual Doppler scoring performs best.

[Power Doppler Index for preoperative XXXX discrimination].

@entity43 :: ('MESH:D010051', 'Disease') :: ['ovarian malignancy'] @entity1 :: ('9606', 'Species') :: ['PATIENTS'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'benign tumors', 'tumors'] @entity4134 :: ('MESH:D000292', 'Disease') :: ['adnexal masses']
@entity43 :: (MESH:D010051,Disease) :: ['ovarian tumors']
