Contribution of morphological assessment of the vessel tree by three-dimensional ultrasound to a correct diagnosis of malignancy in ovarian masses.

• Objective To determine whether subjective evaluation of the morphology of the vessel tree of ovarian tumors, as depicted by three-dimensional (3D) power Doppler ultrasound, can discriminate between benign and malignant ovarian tumors, and whether it improves characterization compared with using gray-scale ultrasound imaging alone. Methods A consecutive series of 104 women scheduled for surgical removal of an ovarian mass were examined with transvaginal two-dimensional (2D) gray-scale and 3D power Doppler ultrasound. Predetermined vessel characteristics, e.g. density of vessels, branching, caliber changes and tortuosity, were evaluated in 360° rotating 3D images of the vessel tree of the tumor. Ultrasound results were compared with those of the histology of the surgical specimens. Univariate and multivariate logistic regression were used. Results There were 77 benign tumors, six borderline tumors and 21 invasive malignancies. All vascular features differed significantly between benign and malignant tumors. The areas under their receiver-operating characteristics (ROC) curves (AUCs) were in the range 0.61-0.83. The AUC of a logistic regression model containing three gray-scale ultrasound variables was 0.98. This model correctly classified all malignancies, with a false-positive rate of 10% (8/77). Adding branching of vessels in the whole tumor to the gray-scale model yielded an AUC of 0.99 and resulted in all malignancies and an additional four benign tumors being correctly classified. Conclusions Subjective evaluation of the morphology of the vessel tree, as depicted by 3D power Doppler ultrasound, can be used to discriminate between benign and malignant ovarian tumors, but adds little to gray-scale ultrasound imaging in an ordinary population of tumors.

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MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

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