Literature DB >> 29279152

MRI features and score for differentiating borderline from malignant epithelial ovarian tumors.

Yong Ai Li1, Jin Wei Qiang2, Feng Hua Ma3, Hai Ming Li1, Shu Hui Zhao4.   

Abstract

PURPOSE: To identify the MRI features of borderline epithelial ovarian tumors (BEOTs) and to differentiate BEOTs from malignant epithelial ovarian tumors (MEOTs).
MATERIALS AND METHODS: The clinical and MRI data of 89 patients with a BEOT and 109 patients with a MEOT proven by surgery and histopathology were retrospectively reviewed. MRI features, including bilaterality, size, shape, margin, cystic-solid interface, configuration, papillae or nodules, signal intensity, enhancement, presence of an ipsilateral ovary, peritoneal implants and ascites were analyzed and compared. Based on the odds ratio (OR) values, the significant risk features for BEOTs were scored as 3 (OR≈∞), 2 (5≤OR<∞) or 1 (OR<5).
RESULTS: There were 89 BEOT patients with 113 tumors [mean size of (13±6.7)cm], with bilateral ovary involvement in 24 cases. There were 109 MEOT patients with 142 tumors [(9.3±4.2)cm] with bilateral ovary involvement in 33 cases. There were eight significant risk factors for BEOTs, including round or oval shape (OR=2.714), well-defined margins (OR=3.318), clear cystic-solid interfaces (OR=5.593), purely cystic (OR=15.206), predominantly cystic with papillae or nodules (OR=2.579), exophytic papillae or nodules (OR=5.351), branching papilla (OR≈∞) and the presence of an ipsilateral ovary (OR≈∞). Based on the scoring of the eight risk factors, a cut-off score of 3.5 yielded a differential sensitivity, specificity, and accuracy of 82%, 85% and 84%, respectively.
CONCLUSION: In contrast to MEOTs, BEOTs frequently had the following features on MRI: round or oval, with well-defined margins and clear cystic-solid interfaces, purely cystic or predominantly cystic with papillae or nodules, branching or exophytic papillae, with the presence of an ipsilateral ovary. MRI can reveal the distinct morphological features of BEOTs and MEOTs and facilitate their discrimination.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Borderline; Differential diagnosis; Epithelial tumors; Magnetic resonance imaging; Malignant; Ovary

Mesh:

Year:  2017        PMID: 29279152     DOI: 10.1016/j.ejrad.2017.11.014

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  7 in total

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  7 in total

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