Ultraschall Med 2018; 39(S 01): S18-S19
DOI: 10.1055/s-0038-1670410
Wissenschaftliche Vortragssitzungen
Wi-Vo 03 Gynäkologie/Geburtshilfe II: Do. 15.11. 10:30 – 12:00 Shanghai 3
Georg Thieme Verlag KG Stuttgart · New York

Estimating risk of malignancy in adnexal masses with ultrasound: a retrospective diagnostic accuracy study

H Reina
1   Gynecology
,
F Vigo
1   Gynecology
,
A Butenschoen
2   Department for gynecologic and prenatal ultrasound/1 – 2 University Women's Hospital Basel
,
J Buechel
2   Department for gynecologic and prenatal ultrasound/1 – 2 University Women's Hospital Basel
,
A Schoetzau
1   Gynecology
,
V Heinzelmann-Schwarz
1   Gynecology
,
G Manegold-Brauer
2   Department for gynecologic and prenatal ultrasound/1 – 2 University Women's Hospital Basel
› Author Affiliations
Further Information

Publication History

Publication Date:
24 October 2018 (online)

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Introduction:

The aim of this study is to evaluate the performance of ultrasound with pattern recognition by experts, Risk of Malignancy Index (RMI) and IOTA ADNEX in the differentiation between benign and malignant adnexal masses.

Material and Methods:

This is a retrospective diagnostic accuracy study, based on data prospectively collected from patients with adnexal masses (Viewpoint data base), who underwent transvaginal and/or transabdominal examination by experienced examiners in our department between December 2016 and December 2017. The risk of malignancy, defined as invasive or borderline tumors, was determined by pattern recognition and the use of two prediction models: the ADNEX model and the Risk of Malignancy Index (RMI, cut off 200). Histological findings were the clinical reference standard.

Results:

In the studied period, we recorded adnexal findings in 426 consecutive examinations. Of these, 122 had surgery and were included in the analysis. 60% of patients were premenopausal and 40% were postmenopausal. Seventy-seven percent of the masses were benign, 6% borderline-tumors, 16% invasive cancers. Expert pattern recognition and RMI had sensitivities of 87% and 80% at a specificity of 93% in differentiating malignant from benign tumors. The ADNEX model showed a sensitivity of 92% at a specificity of 86%.

Conclusions:

Although pattern recognition by experts seems to have the best discriminating power at our center, RMI and IOTA ADNEX help in preoperative planning and are a valuable tool for triage for referral and in teaching settings.