Ovarian Sex Cord-Stromal Tumors: Computed Tomography and Magnetic Resonance Imaging

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Ovarian sex cord-stromal tumors constitute a heterogeneous group of rare tumors that develop from stromal cells and primitive sex cords in the ovary. These tumors comprise 8% of all primary ovarian neoplasms and affect all age groups. Ovarian sex cord-stromal tumors are classified as granulosa-stromal cell tumors, Sertoli-stromal tumors, and steroid cell tumors. These tumors differ from the more common epithelial neoplasms in clinical and radiologic aspects. Sex cord-stromal tumors are primarily treated surgically and have generally good prognosis. In addition, these tumors may have characteristic imaging features and differential points from more common ovarian epithelial tumors. Understanding the clinical and imaging features of ovarian sex cord-stromal tumors is helpful in specific diagnosis of ovarian tumors. Computed tomography (CT) and magnetic resonance (MR) imaging can both provide the valuable information needed to evaluate the ovarian masses. Because MR imaging has high-contrast resolution, it allows confirmation of fat, blood, fluid, or fibrous tissue. Computed tomography is used for staging and treatment planning of ovarian malignancy and is recommended for evaluating peritoneal implants. Recent advances in CT technology, with the use of multiplanar reformatting, improved spatial resolution, and reduced artifact, have increased the accuracy of CT for detection and characterization of ovarian masses. However, the MR image is still used as a problem-solving modality in the assessment of complex adnexal masses because of tumor characterization of MR image over CT and potential risk in patient dose of CT.

Original languageEnglish
Title of host publicationCancer Imaging
PublisherElsevier
Pages523-526
Number of pages4
ISBN (Print)9780123742124
DOIs
StatePublished - 5 Dec 2007

Bibliographical note

Publisher Copyright:
© 2008 Elsevier Inc. All rights reserved.

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