What to choose and why to use – a critical review on the clinical relevance of rASRM, EFI and Enzian classifications of endometriosis

Abstract

Background: Endometriosis is a common benign gynaecological disease that affects pelvic structures and causes adhesions. Endometriosis outside the pelvis exists but is rarer. Deep endometriosis may affect organs such as the urinary bladder, ureters, bowel and sacral roots. Adenomyosis (growth of endometrium in the myometrium, sometimes explained by disruption of the uterine junctional zone) frequently co-exists with deep endometriosis. Over the past decades, multiple attempts have been made to describe the anatomical extent of endometriosis. Out of approximately 20 classification systems suggested and published so far, three have gained widespread acceptance. These are the rASRM (American Society of Reproductive Medicine) classification, the Endometriosis Fertility Index (EFI) and the Enzian classification. Ideally, a classification system should be useful both for describing disease extent based on surgical findings and results of imaging methods (ultrasound, magnetic resonance imaging). Objectives: To highlight the advantages and disadvantages of the three classification systems. Methods: This is a narrative review based on selected publications and experience of the authors. We discuss the current literature on the use of the rASRM, EFI and Enzian classification systems for describing disease extent with imaging methods and for prediction of fertility, surgical complexity, and risk of surgical complications. We underline the need for one universally acceptable terminology to describe the extent of endometriosis. Conclusions: A useful classification system for endometriosis should describe the sites and extent of the disease, be related to surgical complexity and to disease-associated symptoms, including subfertility and should satisfy needs of both, imaging specialists for pre-operative classification and surgeons. The need for such a system is obvious and is provided by the #Enzian classification. Future research is necessary to test its validity.