A review of more than 2000 cases of site-specific pelvic endometriosis rates by MRI: a guide to minimizing under/overdiagnosis non-invasively

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Abstract

Objectives: To statistically study the incidence of endometrioma and deep infiltrating endometriosis (DIE) in various anatomical sites and to illustrate the significance and potential implications for each site. Furthermore, to improve the knowledge of the community for a non-invasive diagnosis alternative to laparoscopy. Methods: This study includes 2040 patients who had been referred with clinical evidence of pelvic endometriosis. These patients had been examined and undergone transvaginal sonography by the referring gynecologists. The imaging modality used to discover and locate various anatomical locations of involvement was MRI with contrast. Two radiologists with expertise in endometriosis separately assessed the patients' MRIs and highlighted the involved areas. Results: In total, 79.1% were positive for either endometrioma or DIE. We detected both DIE and ovarian endometrioma in 78.2% of positive cases. Isolated endometrioma or DIE was present exclusively in 13.7% and 8.1% of patients, respectively. Uterosacral ligaments were detected as the most common (73.8%) site of DIE involvements and in 2.9% of cases were the sole affected location. Interestingly, very rare independent involvement of the genitourinary tract was seen in two patients. Conclusions: In this study, MRI was used to assess the likely involvement sites of endometrioma and DIE, as well as the frequency of incidences in various places and their relationships over a large dataset. Understanding the possibly involved sites, their statistics, and their co-existence can provide radiologists with a roadmap for non-invasive endometriosis diagnosis and treatment planning. These principles should hopefully assist reduce under- and overdiagnosis.

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Hajati, A., & Hajati, O. (2022). A review of more than 2000 cases of site-specific pelvic endometriosis rates by MRI: a guide to minimizing under/overdiagnosis non-invasively. Insights into Imaging, 13(1). https://doi.org/10.1186/s13244-022-01270-z

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