Imaging in gynaecology: How good are we in identifying endometriomas?
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Expert sonologists accurately identified endometriomas using ultrasound pattern recognition, but 1% of diagnosed endometriomas were actually malignancies.
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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.
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Cited by (15)
- Reconsidering evidence-based management of endometriosis 2022
- Pathogenesis Based Diagnosis and Treatment of Endometriosis 2021
- Value of sonography in assessing parametrial endometriotic involvement: Preliminary results 2021
- Ultrasound Differential Diagnosis in Deep Infiltrating Endometriosis of the Urinary Tract 2020
- Differential Diagnosis of Endometriosis by Ultrasound: A Rising Challenge 2020
- Applying the Vaginal Approach for Benign Ovarian Cystectomy: Current Evidence and Future Applications 2020
- Ultrasound pattern and diagnostic accuracy of primary ovarian endometrioma and its recurrence: a pictorial essay 2020
- Combination of noninvasive methods in diagnosis of infertile women with minimal or mild endometriosis, a retrospective study in China 2019
- Sonographic Differential Diagnosis in Deep Infiltrating Endometriosis: The Bowel 2019
- Plasma High Mobility Group Box 1 (HMGB1), Osteopontin (OPN), and Hyaluronic Acid (HA) as Admissible Biomarkers for Endometriosis 2019
- Performances et place de l’échographie dans le diagnostic de l’endométriose, RPC Endométriose CNGOF–HAS 2018
- Anatomic Sites and Associated Clinical Factors for Deep Dyspareunia 2017
- Applying a statistical method in transvaginal ultrasound training: lessons from the learning curve cumulative summation test (LC-CUSUM) for endometriosis mapping 2017
- Endometriosis and Imaging 2017
- New paradigms in the diagnosis and management of endometriosis 2016
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