Gynacological Imaging Reporting and Data System in Classifying Ovarian Masses on the Basis of Ultrasonography

Transvaginal Ultrasonography has been demonstrated to be the most sensitive and effective technique, being also non-invasive and in-expensive maneuver.Since in early reports, a standardized method for the description of the sonographic appearance of the ovarian masses was not used, the data of different studies are not easily compared.

In addition, there is no consensus on sonographic diagnostic criteria for ovarian cancer, despite many ultrasonography features being considered to be predictive of malignancy, such as presence of septations, internal nodularity, wall thickening, solid areas, free fluid or bilaterality.Usually the clinical management decision is based on data provided in the sonographic report. Many sonographers and sonologists use scoring systems to characterize ovarian masses, whereas others use the so called pattern recognition approach However, sometimes sonographic reports are misleading and confusing for the clinician. Although some groups have made considerable efforts in establishing terms and definitions for sonographic findings in ovarian masses .

In this study, we proposed a new data reporting system for sonographic findings in ovarian masses. This system is based on the concept developed for breast imaging, namely the Breast Imaging Reporting and Data System classification. Originally developed for mammographic findings, it has been successfully applied to breast sonography.

Like its breast sonographic counterpart, the gynacological imaging reporting and data system in ovarian masses by ultrasonography lexicon is intended to provide a unified language for sonographic reporting and for avoiding confusion in communication between the sonographer / sonologist and the clinician..

This system is based on a description of the ovarian mass using the pattern recognition approach and color Doppler blood flow location and the prior risk for malignancy in each group. On this basis, the proposed classification enables the sonologist or sonographer to give the clinician as much information as possible in a summarized way, as well as an estimated risk of malignancy, based only on the sonographic characteristics of the images.