Training and implementation of Ovarian-Adnexal Reporting and Data System (O-RADS)  in diagnostic performance of ovarian malignancy for practicing gynecologists. 

Pari Gul,Plawasha Gul -Radiology Department- Bolan Medical Complex Hospital Quetta,Pakistan. 

Objective :

The aim of this study was to explore the performance of gynecologists after undertaking an ultrasound  training based on O-RADS  (Ovarian-Adnexal Reporting and Data System ) which had been designed to improve the capability in detecting an ovarian mass. The O-RADS system provides a lexicon of ultrasound descriptors to characterize and classify ovarian masses.

 

Methods:

A total of 20 consultant gynecologists with different experience level were included in the training conducted in the Radiology department of Quetta, Pakistan. The program was a part of  an early diagnosis of ovarian cancer to reduce the mortality along with the collaboration of Gynecology department. The American College of Radiology  ORADS  training procedure included three thematic lectures (each lasting for 2.0 hours) given by a Radiologist specialized in gynecological imaging diagnosis , with an interval of a month. 

After each session, the gynecologists had a month to adopt the algorithm into their daily work. The diagnostic performances and interobserver agreements of these gynecologists adopting the algorithm of ovarian diagnosis before and after training were compared.

 

Results :

A total of 20 consultant gynecologists with an average experience of  (1-10 years) were enrolled.

After training, the interobserver agreements for the O-RADS  category for all gynecologists (p=0.005) were increased. The sensitivity, specificity, positive predictive value, and negative predictive value, of all gynecologists for ovarian mass diagnosis before and after training were 53% vs. 68%, 82% vs. 90%, 61% vs. 85%, 58% vs.74 %  respectively. The diagnostic performances of all gynecologists  (p<0.001) showed significant improvement after training.

 

Conclusions :

The ultimate goal was to help gynecologists in early diagnosis of ovarian malignancy and optimization of ovarian cancer outcomes. It will help  in minimizing unnecessary interventional procedures in patients at low risk of malignancy and also provide a management recommendation for each risk category.