Journal of Ovarian Research (Jun 2019)

Magnetic resonance imaging in categorization of ovarian epithelial cancer and survival analysis with focus on apparent diffusion coefficient value: correlation with Ki-67 expression and serum cancer antigen-125 level

  • Guofu Zhang,
  • Weigen Yao,
  • Taotao Sun,
  • Xuefen Liu,
  • Peng Zhang,
  • Jun Jin,
  • Yu Bai,
  • Keqin Hua,
  • He Zhang

DOI
https://doi.org/10.1186/s13048-019-0534-0
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 9

Abstract

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Abstract Background To determine whether magnetic resonance (MR) imaging features combined with apparent diffusion coefficient (ADC) values could be used as a tool for categorizing ovarian epithelial cancer (OEC) and predicting survival, as well as correlating with laboratory tests (serum cancer antigen 125, serum CA-125) and tumor proliferative index (Ki-67 expression). Methods and materials MRI examination was undertaken before invasive procedures. MRI features were interpreted and recorded on the picture archive communication system (PACS). ADC measurements were manually performed on post-process workstation. Clinical characteristics were individually retrieved and recorded through the hospital information system (HIS). Cox hazard model was used to estimate the effects of both clinical and MRI features on overall survival. Results Both clinical and MRI features differed significantly between Type I and Type II cancer groups (p < 0.05). The mean ADC value was inversely correlated with Ki-67 expression in Type I cancer (ρ = − 0.14, p < 0.05). A higher mean ADC value was more likely to suggest Type I ovarian cancer (Odds Ratio (OR) = 16.80, p < 0.01). Old age and an advanced International Federation of Gynecology and Obstetrics (FIGO) stage were significantly related to Type II ovarian cancer (OR = 0.22/0.02, p < 0.05). An advanced FIGO stage, solid components, and old age were significantly associated with poor survival (Hazard Ratio (HR) = 23.54/3.69/2.46, p < 0.05). Clear cell cancer type had a poorer survival than any other pathological subtypes of ovarian cancer (HR = 13.6, p < 0.01). Conclusions MR imaging features combined with ADC value are helpful in categorizing OEC. ADC values can reflect tumor proliferative ability. A solid mass may predict poor prognosis for OEC patients.

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