Diagnostic Accuracy of Whole-Body Computed Tomography for Incidental Ovarian Tumors in Patients with Prior Breast Cancer

Pei Ching Huang, Ren Chin Wu, Yu Hsiang Juan, Hui Yu Ho, Yung-Chang Lin, Yi Ting Huang, Shu Hang Ng, Chyong-Huey Lai, Angel Chao, Gigin Lin*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

Abstract

Whole-body computed tomography (WBCT) serves as the first-line imaging modality for breast cancer follow-up. To investigate the imaging characteristics and diagnostic accuracy of WBCT for incidental ovarian tumors in patients with prior breast cancer, we retrospectively reviewed a consecutive cohort of 13,845 patients with breast cancer, of whom 149 had pathologically-proven ovarian lesions. We excluded patients with ovarian diagnosis before breast cancer, CT scan not including ovary, CT-pathology interval >30 days, and severe CT artifact. Among our 60 breast cancer patients (median age, 46 years) with pathologically proven ovarian lesions, 49 patients had benign diseases, seven had primary ovarian cancer and four had ovarian metastasis from breast cancer. The histologic types of breast cancer with ovarian metastases included invasive ductal carcinoma, lobular carcinoma and angiosarcoma. Cystic ovarian lesions identified on WBCT during the breast cancer follow-up are more likely to be benign, while solid-cystic lesions are likely to be primary ovarian cancers, and solid lesions may indicate ovarian metastasis. The diagnostic accuracy, sensitivity, specificity, and areas under the receiver operating characteristic curve of WBCT were 98.3%, 100.0%, 98.0%, and 0.99 (malignant vs. benign); 90.0%, 100.0%, 85.7%, and 0.93 (metastasis vs. primary ovarian cancer), respectively. The only false positive solid lesion was a Sertoli–Leydig tumor. In conclusion, WBCT may help diagnose incidental ovarian tumors in patients with prior breast cancers and guide disease management.

Original languageEnglish
Article number347
JournalDiagnostics
Volume12
Issue number2
DOIs
StatePublished - 02 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Breast neoplasms
  • Computed tomography
  • Metastasis
  • Ovarian neoplasms

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