Investigator
Beni Suef University
Diagnostic Performance of Gynecologic Imaging Reporting and Data System (GI-RADS) in Preoperative Evaluation of Adnexal Masses
Background and Objectives: Ovarian cancer is a highly lethal gynecological malignancy and the fifth leading cause of cancer-related deaths. Diagnosis mainly involves gynecological examination and transvaginal ultrasonography. To evaluate the diagnostic performance of the Gynecology Imaging Reporting and Data System (GI-RADS) with regard to its ability to evaluate adnexal masses preoperatively, considering a definitive histopathological diagnosis. Materials and Methods: This study was approved by the ethics committee, and informed consent was obtained from all the patients. This research was conducted at Beni-suef University Hospital between June 2021 and January 2023 on 100 women who experienced pelvic pain due to an adnexal mass. Results: Our study results revealed that the combination of IV-V GI-RADS had high specificity (92.2%), sensitivity (87%), and a negative predictive value (95.9%), but moderate other diagnostic characteristics for predicting adnexal mass malignancy. Conclusions: The GI-RADS classification system is a reliable method for reporting ovarian masses, with high diagnostic accuracy for predicting malignancy. It aids in patient triage and clinical decision making. To optimize care, it is essential to inform referring clinicians about the objectives of the GI-RADS before its implementation in a treatment plan.
