Gynecology Imaging Reporting and Data System (GI-RADS): diagnostic performance and inter-reviewer agreement
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To evaluate diagnostic performance and inter-reviewer agreement (IRA) of the Gynecologic Imaging Reporting and Data System (GI-RADS) for diagnosis of adnexal masses (AMs) by pelvic ultrasound (US).
Patients and methods
A prospective multicenter study included 308 women (mean age, 41 ± 12.5 years; range, 15–73 years) with 325 AMs detected by US. All US examinations were analyzed, and AMs were categorized into five categories according to the GI-RADS classification. We used histopathology and US follow-up as the reference standards for calculating diagnostic performance of GI-RADS for detecting malignant AMs. The Fleiss kappa (κ) tests were applied to evaluate the IRA of GI-RADS scoring results for predicting malignant AMs.
A total of 325 AMs were evaluated: 127 (39.1%) were malignant and 198 (60.9%) were benign. Of 95 AMs categorized as GI-RADS 2 (GR2), none was malignant; of 94 AMs categorized as GR3, three were malignant; of 13 AMs categorized as GR4, six were malignant; and of 123 AMs categorized as GR5, 118 were malignant. On a lesion-based analysis, the GI-RADS had a sensitivity, a specificity, and an accuracy of 92.9%, 97.5%, and 95.7%, respectively, when regarding only those AMs classified as GR5 for predicting malignancy. Considering combined GR4 and GR5 as a predictor for malignancy, the sensitivity, specificity, and accuracy of GI-RADS were 97.6%, 93.9%, and 95.4%, respectively. The IRA of the GI-RADS category was very good (κ = 0.896). The best cutoff value for predicting malignant AMs was >GR3.
The GI-RADS is very valuable for improving US structural reports.
• There is still a lack of a standard in the assessment of AMs.
• GI-RADS is very valuable for improving US structural reports of AMs.
• GI-RADS criteria are easy and work at least as well as IOTA.
KeywordsAdnexal diseases Neoplasms Gynecology Ultrasonography
Area under the ROC curve
Breast Imaging Reporting and Data System
Federation of Gynaecology and Obstetrics
Gynecologic Imaging Reporting and Data System
International Ovarian Tumor Analysis
Negative predictive value
Positive predictive value
Receiver operating characteristic
The authors thank all staff members and colleagues in Radiology department-Zagazig University for their helpful cooperation.
The authors state that this work has not received any funding.
Compliance with ethical standards
The scientific guarantor of this publication is Dr. Mohammad Abd Alkhalik Basha.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Institutional Review Board approval was obtained.
Written informed consent was obtained from all patients.
Statistics and biometry
The corresponding author has great statistical expertise.
• Diagnostic or prognostic study
• Multicenter study
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