Abstract
The characterization of adnexal masses has been facilitated remarkably by the use of pelvic ultrasound during the last decade. Its ease of use, accessibility, relatively low cost, and the recent introduction of color and duplex scanning has made this modality invaluable. Please see other chapters in this volume for a discussion of the use of ultrasound for differentiating benign from malignant ovarian masses. For patients with advanced ovarian cancer and a known pelvic mass which can be palpated on bimanual exam, however, ultrasonography is rarely helpful other than to confirm the presence of ascites. While magnetic resonance imaging (MRI) provides precise information regarding the location of disease and invasion of tissue planes, such detailed anatomic relationships are generally not clinically relevant for treatment planning in patients with advanced ovarian carcinoma, particularly given the associated costs. This is in contradistinction to cervical cancer, in which MRI has been shown to be sensitive for the detection of parametrial involvement, a parameter which significantly alters the plan of treatment if present (Yu et al. 1998). 18F fluorodeoxyglucose-positron emission tomography (FDG-PET) is highly sensitive for cancerous lesions and may ultimately prove useful for the detection of recurrences, but the cost/benefit ratio is poor for the preoperative evaluation of primary ovarian cancer. Computed tomography (CT) offers advantages over other techniques: relatively low cost, fast scan times, wide availability, and evaluation of the entire abdominal cavity. Furthermore, the use of intravenous and oral contrast improves visualization of retroperitoneal anatomy (Figure 8.1). For these reasons, CT has become a common diagnostic procedure to assess the extent of disease and plan surgical interventions in patients with advanced ovarian cancer. This chapter addresses the use of CT imaging in this cohort of patients and its potential to predict surgical outcome.
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Dowdy, S.C., Cliby, W.A. (2010). Advanced Ovarian Cancer: Prediction of Surgical Outcomes Using Computed Tomography. In: Hayat, M. (eds) Methods of Cancer Diagnosis, Therapy, and Prognosis. Methods of Cancer Diagnosis, Therapy and Prognosis, vol 6. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2918-8_8
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