title: Gynecologic imaging reporting and data system: a new proposal for classifying adnexal masses on the basis of sonographic findings.
abstract: OBJECTIVE
  The purpose of this study was to describe a new reporting system called the Gynecologic Imaging Reporting and Data System (GI-RADS) for reporting findings in adnexal masses based on transvaginal sonography.
  
  
  METHODS
  A total of 171 women (mean age, 39 years; range, 16-77 years) suspected of having an adnexal mass were evaluated by transvaginal sonography before treatment. Pattern recognition analysis and color Doppler blood flow location were used for determining the presumptive diagnosis. Then the GI-RADS was used, with the following classifications: GI-RADS 1, definitively benign; GI-RADS 2, very probably benign; GI-RADS 3, probably benign; GI-RADS 4, probably malignant; and GI-RADS 5, very probably malignant. Patients with GI-RADS 1 and 2 tumors were treated expectantly. All GI-RADS 3, 4, and 5 tumors were removed surgically, and a definitive histologic diagnosis was obtained. The GI-RADS classification was compared with final histologic diagnosis.
  
  
  RESULTS
  A total of 187 masses were evaluated. The prevalence rate for malignant tumors was 13.4%. Overall GI-RADS classification rates were as follows: GI-RADS 1, 4 cases (2.1%); GI-RADS 2, 52 cases (27.8%); GI-RADS 3, 90 cases (48.1%); GI-RADS 4, 13 cases (7%); and GI-RADS 5, 28 cases (15%). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 92%, 97%, 85%, 99%, and 96%, respectively.
  
  
  CONCLUSIONS
  Our proposed reporting system showed good diagnostic performance. It is simple and could facilitate communication between sonographers/sonologists and clinicians.
authors.affiliation: Centro Ecografico Ultrasonic Panoramico, Santiago, Chile.
authors.forename: Fernando
authors.initials: F
authors.lastname: Amor
authors.forename: Humberto
authors.initials: H
authors.lastname: Vaccaro
authors.forename: Juan Luis
authors.initials: JL
authors.lastname: Alcázar
authors.forename: Mauricio
authors.initials: M
authors.lastname: León
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Craig
authors.forename: Jaime
authors.initials: J
authors.lastname: Martinez
mesh_terms: D000293:Adolescent; D000328:Adult; D001185:Artificial Intelligence; D003628:Database Management Systems; D005260:Female; D006176:Gynecology / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011873:Radiology Information Systems; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography; D055815:Young Adult