Abstract
BackgroundTo assess the validity and accuracy of GI-RADS classification in the prediction of malignancy and in triaging the management protocol in ovarian lesions.ResultsOne hundred fifty-six ovarian lesions were detected in the examined 116 women. The prevalence of malignant tumors was 44%. Overall GI-RADS classification rates were as follows: 41 cases (26.3%) were classified as GI-RADS 1, 26 cases (16 .7%) as GI-RADS 2, 34 cases (21.8%) as GI-RADS 3, 14 cases (8.9%) as GI-RADS 4, and 41 cases (26.3%) as GI-RADS 5. No follow-up was done in GI-RADS 1 patients. A final diagnosis of all GI-RADS 2 ovarian masses such as functional cyst (n = 10), hemorrhagic cysts (n = 8), corpus luteal cysts (n = 6), and some GI-RADS 3 as simple cysts (n = 10) was made by spontaneous resolution of these masses at follow-up after 6 weeks. Fifteen cases of GI-RADS 3 as mature teratoma, serous and mucinous cystadenoma, endometrioma, and ovarian torsion and all GI-RADS 4 and 5 underwent laparoscopic or surgical removal of the ovarian mass with histopathological examination. The diagnostic performance of the GI-RADS in predicting the risk of malignancy in ovarian masses was as follows: 98.11% sensitivity, 95.15% specificity, 91.2% positive predictive value (PPV), 99.2% negative predictive value (NPV), and 20.2 positive likelihood ratio, and the overall accuracy was 96.2% (area under receiver operating curve (AUC) = 0.96, P < 0.001).ConclusionGI-RADS classification performs well as a reporting system of the ovarian masses with high diagnostic performance in the prediction of malignancy, and it seems to be a helpful tool in triaging management in patients with ovarian masses.Trial registrationThe trial was registered in the US National Library of Medicine, under clinical trial number NCT03175991. Also, the ethical committee approval number of the Faculty of Medicine, Assiut University, was 17100016 on February 28, 2017.
Highlights
To assess the validity and accuracy of Gynecology Imaging Reporting and Data System (GI-RADS) classification in the prediction of malignancy and in triaging the management protocol in ovarian lesions
The subjective impression of an experienced radiologist is currently considered to be superior to other methods [4, 12], but its subjective nature affects the performance of the method and the examiner’s confidence in providing a diagnosis [13]
Most referring clinicians managed their patients according to their GI-RADS classification
Summary
To assess the validity and accuracy of GI-RADS classification in the prediction of malignancy and in triaging the management protocol in ovarian lesions. The assessment of an adnexal mass is difficult and meticulous. Ultrasonography (US) is currently considered as the primary imaging modality for the detection and characterization of adnexal masses [4]. Several studies have proposed for the characterization of the ovarian masses, including examiner’s subjective impression [7], mathematically developed scoring systems [8], simple descriptive scoring systems [9], logistic regression models [10], and neural networks [11]. The subjective impression of an experienced radiologist is currently considered to be superior to other methods [4, 12], but its subjective nature affects the performance of the method and the examiner’s confidence in providing a diagnosis [13]
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