In:
Diagnostics, MDPI AG, Vol. 12, No. 7 ( 2022-07-21), p. 1767-
Abstract:
(1) Background: Endometriosis is a widespread gynecological condition that causes chronic pelvic discomfort, dysmenorrhea, infertility, and impaired quality of life in women of reproductive age. Clinical examination, transvaginal ultrasonography (TVS), and magnetic resonance imaging (MRI) are significant preoperative non-invasive diagnosis procedures for the accurate assessment of endometriosis. Although TVS is used as the primary line for diagnosis, MRI is commonly utilized to achieve a better anatomical overview of the entire pelvic organs. The aim of this systematic review article is to thoroughly summarize the research on various endometriosis diagnosis methods that are less invasive. (2) Methods: To find relevant studies, we examined electronic databases, such as MEDLINE/PubMed, Cochrane, and Google Scholar, choosing 70 papers as references. (3) Results: The findings indicate that various approaches can contribute to diagnosis in different ways, depending on the type of endometriosis. For patients suspected of having deep pelvic endometriosis, transvaginal sonography should be the first line of diagnosis. Endometriosis cysts are better diagnosed with TVS, whereas torus, uterosacral ligaments, intestine, and bladder endometriosis lesions are best diagnosed using MRI. When it comes to detecting intestine or rectal nodules, as well as rectovaginal septum nodules, MRI should be the imaging tool of choice. (4) Conclusions: When diagnosing DE (deep infiltrative endometriosis), the examiner’s experience is the most important criterion to consider. In the diagnosis of endometriosis, expert-guided TVS is more accurate than routine pelvic ultrasound, especially in the deep infiltrative form. For optimal treatment and surgical planning, accurate preoperative deep infiltrative endometriosis diagnosis is essential, especially because it requires a multidisciplinary approach.
Type of Medium:
Online Resource
ISSN:
2075-4418
DOI:
10.3390/diagnostics12071767
Language:
English
Publisher:
MDPI AG
Publication Date:
2022
detail.hit.zdb_id:
2662336-5
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