Learning curve in the detection of ovarian and deep endometriosis by using Magnetic Resonance: comparison with surgical results
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Updated: Jun 16, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Luca Saba1, Stefano Guerriero, Rosa Sulis
1Department of Science of the Images, Azienda Ospedaliero Universitaria di Cagliari, s.s. 554 Monserrato (Cagliari) 09045, Italy. lucasaba@tiscali.it
Purpose:
Determining if Magnetic Resonance Imaging (MRI) accuracy in diagnosing endometriosis is related to radiologist's expertise.
Methods And Materials:
Written informed consent was obtained from all patients. This study is compliant to STARD method. Thirty patients (mean age 34; range 21-45 years) who had undergone MRI study for suspected endometriosis underwent surgery were retrospectively evaluated. MRI at 1.5T was performed with SE and TSE sequences, T1 and T2-weighted with and without fat suppression. Four localizations were analyzed: ovary, uterosacral ligaments (USL), vaginal fornix and Rectum\Sigma\Douglas (R.S.D.). One radiologist evaluated each dataset; sensitivity, specificity, PPV and NPV, accuracy, LR+ and LR- were calculated according to the surgical results (first analysis). Dataset were then re-analyzed 12 months (second analysis) and 24 months (third analysis) later. McNemar test was applied to determine differences between the three analysis.
Results:
Sensitivity, specificity and accuracy for the ovary at the first analysis were 88.9%, 87% and 88%, at the second 92.6%, 87% and 90% whereas at the third 92.6%, 91.3% and 92%. Sensitivity, specificity and accuracy for the USLs at the first analysis were 62.5%, 76.9% and 70%, at the second 72%, 80.8% and 76% whereas at the third 80%, 84.6% and 82%. Sensitivity, specificity and accuracy for the vaginal fornix at the first analysis were 63.2%, 64.5% and 64%, at the second 73.7%, 77.4% and 76% whereas at the third 73.7%, 83.9% and 80%. Sensitivity, specificity and accuracy for the R.S.D. at the first analysis were 39.1%, 81.5% and 62%, at the second 62.5%, 85.2% and 76% whereas at the third 73.9%, 88.9% and 82%. McNemar test indicated a significant statistical difference in sensitivity in detecting nodules of endometriosis in R.S.D. between first and third analysis (p=0.0215). The mean review time decreased (p=0.0001).
Conclusions:
Accuracy of MRI in diagnosing endometriosis increased with radiologist's expertise and the improvement was statistically significant in determining RSD involvement.
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