Transitional cell tumor of the ovary: Computed tomographic and magnetic resonance imaging features with pathological correlation

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

OBJECTIVE: To describe computed tomographic (CT) and magnetic resonance (MR) imaging findings of transitional cell tumors, including newly established transitional cell carcinoma, according to tumor type with pathological correlation. METHODS: We retrospectively reviewed the CT and MR images of 22 patients with transitional cell tumors of ovary (14 benign Brenner, 2 borderline Brenner, 2 malignant Brenner, and 4 transitional cell carcinomas) for the following factors: size, location, configuration, signal intensity, staging, and accompanying ovarian tumors. RESULTS: Sixteen tumors were detected on CT or MRI (8 benign, 2 borderline, and 6 malignant tumors), and the mean size of measurable tumors was 8.8 cm. Benign Brenner tumors were homogeneous solid (n = 6) or unilocular cystic (n = 2). Two borderline Brenner tumors were multilocular cystic. Malignant tumors, including malignant Brenner tumors and transitional cell carcinomas, were heterogeneous solid (n = 3) or multilocular cystic (n = 3). The signal intensity of solid components on T2-weighted images was isointense compared with that of muscle in benign and borderline Brenner tumors and hyperintense in malignant tumors. CONCLUSIONS: The CT and MR appearance of transitional cell tumors varied according to tumor type. Benign Brenner tumors were homogeneous solid or unilocular cystic pattern, and malignant tumors were heterogeneous solid or multilocular cystic.

Original languageEnglish
Pages (from-to)106-112
Number of pages7
JournalJournal of Computer Assisted Tomography
Volume33
Issue number1
DOIs
StatePublished - 2009

Keywords

  • Brenner tumor
  • Computed tomography
  • MR imaging
  • Ovarian neoplasm
  • Transitional cell tumor

Fingerprint

Dive into the research topics of 'Transitional cell tumor of the ovary: Computed tomographic and magnetic resonance imaging features with pathological correlation'. Together they form a unique fingerprint.

Cite this