Gynacological Imaging Reporting and Data System in Ovarian Masses by Ultrasonography

NCT ID: NCT03175991

Last Updated: 2020-05-12

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 123 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2018-07-05
• Study Completion Date: 2019-07-01

Brief Summary

Ovarian masses are common problems in clinical practice. Sonography is considered the firstline imaging technique for discriminating between malignant and benign lesions, and it has been shown to be useful for determining optimal treatment.

Detailed Description

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.

Currently, there is enough evidence to indicate that when an experienced examiner performs the sonographic examination, such accuracy is achievable for most types of ovarian masses.

Conditions

Ovarian Neoplasms

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

ovarian masses patients

women of different age groups diagnosed as having an ovarian mass or accidentally discovered ovarian mass in non-complaining female by ultrasonography or Patients known to have primary that may give metastasis to the ovaries.

ultrasonography

Intervention Type: DIAGNOSTIC_TEST

A morphologic evaluation will be performed according to International Ovarian Tumor Analysis Group recommendations for the following parameters:

Bilaterality , wall thickness, septations , papillary projections, solid areas, and echogenicity. The presence of ascites also will be recorded. Pattern recognition analysis will be used for ovarian masses highly suggestive of some diseases , then color Doppler will be activated to identify vascular color signals within the lesion.

Interventions

ultrasonography

A morphologic evaluation will be performed according to International Ovarian Tumor Analysis Group recommendations for the following parameters:

Bilaterality , wall thickness, septations , papillary projections, solid areas, and echogenicity. The presence of ascites also will be recorded. Pattern recognition analysis will be used for ovarian masses highly suggestive of some diseases , then color Doppler will be activated to identify vascular color signals within the lesion.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• All women of different age groups diagnosed as having an ovarian mass.
• Accidentally discovered ovarian mass in non-complaining female.
• Patients known to have primary that may give metastasis to the ovaries.

Exclusion Criteria

• Patients receive neo adjuvant chemotherapy
• Recurrent ovarian masses

• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: No

Sponsors

Assiut University

OTHER

Sponsor Role: lead

Responsible Party

Hagar Desoky

Principle investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Lamiaa M Refaat, Lecturer

Role: STUDY_DIRECTOR

south egypt cancer institue,assuit univeristy

hagar HM Desoky, demonstrator

Role: PRINCIPAL_INVESTIGATOR

south egypt cancer institue,assuit univeristy

Locations

Faculty of Medicine-Assuit Univeristy

Asyut, , Egypt

Countries

Egypt

References

Zhang T, Li F, Liu J, Zhang S. Diagnostic performance of the Gynecology Imaging Reporting and Data System for malignant adnexal masses. Int J Gynaecol Obstet. 2017 Jun;137(3):325-331. doi: 10.1002/ijgo.12153. Epub 2017 Apr 12.

Reference Type: BACKGROUND

PMID: 28295272 (View on PubMed)

Other Identifiers

HAGAR098765

Identifier Type: -

Identifier Source: org_study_id