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Updated: Jul 8, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
ADNEX Model-Based Diagnosis of Ovarian Cancer Using MRI Images
Bin Liu1, Jianmei Liao2, Wenli Gu3
1Department of Radiology, Kunming Yan'an Hospital, Kunming 650051, China.
Abstract:
This exploration aims to investigate the important role of magnetic resonance imaging (MRI) in the diagnosis of ovarian cancer under the ADNEX. From March 2017 to December 2019, 84 patients with ovarian cancer confirmed by pathological operation were selected as the research objects. The consistency of ADNEX, MRI, and ADNEX∗MRI in the diagnosis and staging of ovarian cancer was calculated separately. SPSS 26.0 statistical software was used to compare the accuracy, sensitivity, specificity, and diagnostic value of the two diagnostic methods. The results show that the accuracy and sensitivity of ADNEX are 78.6% and 93.2%, respectively. The accuracy and sensitivity of MRI are 81.2% and 89.4%, respectively. There is no significant difference between the two methods (p < 0.05). The overall consistency rates of ADNEX∗MRI, MRI diagnosis, and ADNEX for ovarian cancer staging are 94.2%, 74%, and 65.4%, respectively. There was a significant difference (p < 0.05). ADNEX∗MRI and MRI diagnosis were compared with each stage of ADNEX. There is a significant difference between the second and fourth stages (p < 0.05), and there is also a significant difference in the fourth stage (p < 0.017). It is concluded that MRI diagnosis of ovarian cancer based on ADNEX is superior to ADNEX and MRI examination alone, which provides a certain reference value for clinical staging of ovarian cancer.
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