Frontiers in Oncology (Aug 2022)

Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors

  • Renwei Liu,
  • Ruifeng Li,
  • Jinzhi Fang,
  • Kan Deng,
  • Cuimei Chen,
  • Jianhua Li,
  • Zhiqing Wu,
  • Xiaoxu Zeng

DOI
https://doi.org/10.3389/fonc.2022.904323
Journal volume & issue
Vol. 12

Abstract

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ObjectiveTo evaluate the utility of apparent diffusion coefficient (ADC) histogram analysis to differentiate between three types of solid ovarian tumors: granulosa cell tumors (GCTs) of the ovary, ovarian fibromas, and high-grade serous ovarian carcinomas (HGSOCs).MethodsThe medical records of 11 patients with GCTs of the ovary (regions of interest [ROI-cs], 137), 61 patients with ovarian fibromas (ROI-cs, 161), and 14 patients with HGSOCs (ROI-cs, 113) confirmed at surgery and histology who underwent diffusion-weighted imaging were retrospectively reviewed. Histogram parameters of ADC maps (ADCmean, ADCmax, ADCmin) were estimated and compared using the Kruskal-WallisH test and Mann-Whitney U test. The area under the curve of receiver operating characteristic curves was used to assess the diagnostic performance of ADC parameters for solid ovarian tumors.ResultsThere were significant differences in ADCmean, ADCmax and ADCmin values between GCTs of the ovary, ovarian fibromas, and HGSOCs. The cutoff ADCmean value for differentiating a GCT of the ovary from an ovarian fibroma was 0.95×10-3 mm2/s, for differentiating a GCT of the ovary from an HGSOC was 0.69×10-3 mm2/s, and for differentiating an ovarian fibroma from an HGSOC was 1.24×10-3 mm2/s.ConclusionADCmean derived from ADC histogram analysis provided quantitative information that allowed accurate differentiation of GCTs of the ovary, ovarian fibromas, and HGSOCs before surgery.

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