Imaging Evaluation of Ovarian Masses
Yong-Yeon Jeong, MD ; Eric K. Outwater, MD ; Heoun Keun Kang, MD

1 From the Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, Pa (E.K.O.); and the Department of Diagnostic Radiology, Chonham University Medical School, Kwangju, South Korea (Y.Y.J., H.K.K.). Presented as a refresher course at the 1998 RSNA scientific assembly. Received August 24, 1999; revision requested November 8 and received December 14; accepted December 22. Address correspondence to E.K.O., Department of Radiology, University of Arizona, 1501 N Campbell Ave, Tucson, AZ 85724-5067.

Adnexal masses present a special diagnostic challenge, in part because benign adnexal masses greatly outnumber malignant ones. Determination of a degree of suspicion for malignancy is critical and is based largely on imaging appearance. Endovaginal ultrasonography (US) is the most practical modality for assessment of ovarian tumors because it is readily available and has a high negative predictive value. Morphologic analysis of adnexal masses is accurate for identifying masses as either low risk or high risk. The most important morphologic features are non-fatty solid (vascularized) tissue, thick septations, and papillary projections. Color Doppler US helps identify solid, vascularized components in a mass. Spectral Doppler waveform characteristics (eg, resistive index, pulsatility index) correlate well with malignancy but generally add little information to morphologic considerations. Computed tomography can help assess the extent of disease in patients before and after primary cytoreductive surgery. Magnetic resonance (MR) imaging is better reserved for problem solving when US findings are nondiagnostic or equivocal because, although it is more accurate for diagnosis, it is also more expensive. The signal intensity characteristics of ovarian masses make possible a systematic approach to diagnosis. Mature cystic teratomas, cysts, endometriomas, leiomyomas, fibromas, and other lesions can be accurately diagnosed on the basis of T1-weighted, T2-weighted, and fat-saturated T1-weighted MR imaging findings.