Facts, Views & Vision
in ObGyn

Journal of the European Society for Gynaecological Endoscopy

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Imaging in gynaecology: How good are we in identifying endometriomas?

Caroline Van Holsbeke, Ben Van Calster, Stefano Guerriero, Luca Savelli, Francesco Leone, Daniela Fischerova, Artur Czekierdowski, Robert Fruscio, Joan Veldman, Gregg Van De Putte, Antonia C. Testa, Tom Bourne, Lil Valentin, Dirk Timmerman

  • Department of Obstetrics and Gynaecology, University Hospitals Leuven, Belgium (CVH, JV, TB, DT).
  • Department of Obstetrics and Gynaecology, Ziekenhuis Oost-Limburg, Genk, Belgium (CVH, GVDP).
  • Early Pregnancy and Gynaecological Ultrasound Unit, Imperial College, Hammersmith Campus, London, UK (TB).
  • Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Belgium (BVC).
  • Reproductive Medicine Unit, Department of Obstetrics and Gynaecology Policlinico S. Orsola-Malpighi, Bologna, Italy (LS).
  • Department of Obstetrics and Gynaecoloy, Clinical Sciences Institute L. Sacco, University of Milan, Milan, Italy (FL).
  • Department of Obstetrics and Gynaecology, Oncogynaecological Centre, Charles University, Prague, Czech Republic (DF).
  • 1st Department of Gynaecological Oncology and Gynaecology of the Medical University in Lublin, Poland (AC).
  • Clinica Ostetrica e Ginecologica, Università degli Studi Milano-Bicocca, Ospedale S. Gerardo dei Tintori, Monza, Italy (RF).
  • Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Roma, Italy (ACT).
  • Department of Obstetrics and Gynaecology, Malmö University Hospital, Lund University, Sweden (LV).
  • Correspondence at: Caroline Van Holsbeke, Department of Obstetrics and Gynaecology, Z.O.L. Genk, Schiepse Bos 6, B-3600 Genk, Belgium.
  • Tel.: + 32 89 327547 (office); fax: + 32 89 327920 (office); tel.: + 32 89 327524 (secretary);
  • e-mail: caroline.van.holsbeke@skynet.be
Keywords:

Ultrasonography, endometriosis, endometrioma, adnexal tumours, pattern recognition, subjective evaluation.


Published online: Jun 03 2009

Abstract

Aim: To evaluate the performance of subjective evaluation of ultrasound findings (pattern recognition) to discriminate endometriomas from other types of adnexal masses and to compare the demographic and ultrasound characteristics of the true positive cases with those cases that were presumed to be an endometrioma but proved to have a different histology (false positive cases) and the endometriomas missed by pattern recognition (false negative cases).

Methods: All patients in the International Ovarian Tumor Analysis (IOTA ) studies were included for analysis. In the IOTA studies, patients with an adnexal mass that were preoperatively examined by expert sonologists following the same standardized ultrasound protocol were prospectively included in 21 international centres. Sensitivity and specificity to discriminate endometriomas from other types of adnexal masses using pattern recognition were calculated. Ultrasound and some demographic variables of the masses presumed to be an endometrioma were analysed (true positives and false positives) and compared with the variables of the endometriomas missed by pattern recognition (false negatives) as well as the true negatives.

Results: IOTA phase 1, 1b and 2 included 3511 patients of which 2560 were benign (73%) and 951 malignant (27%). The dataset included 713 endometriomas. Sensitivity and specificity for pattern recognition were 81% (577/713) and 97% (2723/2798). The true positives were more often unilocular with ground glass echogenicity than the masses in any other category. Among the 75 false positive cases, 66 were benign but 9 were malignant (5 borderline tumours, 1 rare primary invasive tumour and 3 endometrioid adenocarcinomas). The presumed diagnosis suggested by the sonologist in case of a missed endometrioma was mostly functional cyst or cystadenoma.

Conclusion: Expert sonologists can quite accurately discriminate endometriomas from other types of adnexal masses, but in this dataset 1% of the masses that were classified as endometrioma by pattern recognition proved to be malignancies.