The Clinical Value Of Color Doppler Sonographic Prediction Of Malignancy In Adnexal Masses Using Multivariate Logistic Regression Analysis

Objective:The aim of the study was to assign a probability of malignancy for any patient with an adnexal mass by the application of multivariate logistic regression analysis to variables recorded at the time of transvaginal and transabdominal ultrasonography.Methods: One hundred and eleven women with known adnexal masses were examined using transabdominal B-mode and color Doppler imaging. For each patient the variables included:⑴age, ⑵menstruation status,⑶resistance index (RI),⑷pulsatility index (PI),⑸highest peak systolic (PSV),⑹time-averaged maximum velocity (TAMVX),⑺maximum tumor diameter, ⑻tumor volume, ⑼tumor morphology, ⑽the presence or absence of tumor membrane, ⑾tumor echogenicity, ⑿the location of blood flow, ⒀ascite. These 13 independent variables and the final histological diagnosis for each patient (the dependent variable) were used for the regression analysis.Result In the entire dataset there were 49 women with benign ovarian tumors, 11 with inflammation mass, two with borderline and 41 with primary invasive ovarian tumors , 6 with metastatic invasive tumor , 1 with fallopian sarcoma. The mean age of the patients with benign tumors was 39 years compared with 52 years for those malignant or borderline tumors(P＝0.417),there was no significant difference .Of the postmenopausal women, 20% is the benign tumor and 70% is the malignant tumor. There was significant difference(P﹤0.001). For the entire dataset the irregular morphology of the tumor (P﹤0.001) ,the unentire membrane of the tumor (P﹤0.001) and the tumor with low or strong echo (P﹤0.001) were significantly higher in the malignant tumors. In contrast, there were no significant difference in the largest diameter and the volume for each lesion among the benign and malignant tumors(p=0.867 and 0.632 respectively). There was significant difference of the presence or absence of the ascite between the benign and malignant tumors (P﹤0.001). The 98 percent of the malignant tumors were checked with the central blood flow, while 18 (30%) benign tumors were checked with the central blood stream, the others of the benign tumors had peripheral blood stream, there was significant difference (P﹤0.001).Both impedance parameters (RI and PI) were significant lower in malignant tumors(p=0.011 and <0.0001,respectively).While both velocity parameters (PSV and TAMVX) were not significant (p=0.829 and 0.139 respectively).Regression analysis on the 13 variables resulted in the retention of only "RI", "tumor morphology score", "flow score" and "ascite" as significantly contributing to predicting the presence and absence of malignancy. The probability of malignancy for any patient was given by solving the equation:1/(1+e-z),where e is the base value for natural logarithms and z=(-15.034×RI)+(4.423×tumor morphology score)+(3.040×tumor flow score)+(2.456×ascite)+0.531.Through the ROC curve , the optimum cut-off of the continuous variables can be made and the character that the multivariate logistic regression compare with the univariable. Multivariable logistic regression model discriminates between benign and malignant tumors better than univariable (RI, tumor morphology score , flow score ,ascite) from the area of ROC curve. With this model ,a probability greater than 25% gave a sensitivity and specificity of 98% and 91.7%,postivie prediction value 100%,negetive prediction value 97%,accurancy 95.4%. A probability greater than 50% gave a sensitivity and specificity of 92% and 95%, positive prediction value 97.9%,negetive prediction value 93.4%,accurancy 93.6%.Of the entire patients, 57 women were diagnosed exactly ,of the whole 61 women diagnosed as the benign tumor, diagnosis coincidence ratio 96.7%. 46 women were diagnosed exactly as malignant tumor of the whole 49 women diagnosed malignant tumor, the diagnosis coincidence ratio 95%.Conclusion The diagnosis value of multivariable logistic regression model appears to be better than independently use gray ultrasound and color Doppler ultrasound .Th...