Return to search

Testing Transvaginal Ultrasound as a Non-Invasive Diagnostic Tool for Endometriosis

Endometriosis is a heterogeneous chronic pain and inflammatory disease associated with negative impacts on quality of life. Among the phenotypes of endometriosis, deep endometriosis (DE) is the most aggressive form of the disease, associated with complex disease states, such as adhesions within the pouch of Douglas (POD) and bowel DE. The most common site of DE is the uterosacral ligaments (USLs), which are bilateral structures between the uterus and sacrum conjoined by the torus uterinus (TU), with a prevalence of 20 to 70%. The USLs have historically been the hardest to visualize using non-invasive modalities, such as transvaginal ultrasound (TVS), resulting in poor identification of endometriosis when present on/within the USLs, contributing to the significant diagnostic delay associated with the disease.

This thesis details a novel diagnostic approach, utilizing TVS within the posterior vaginal fornix as the index test and laparoscopic visualization as the reference standard, aiming to evaluate the diagnostic accuracy of TVS for DE of the USLs and TU. Additionally, the USLs and TU are commonly associated with complex disease presentations, including POD obliteration and bowel DE, though the impact on diagnostic accuracy remains unknown. We theorize that these concurrent complex disease states will lead to the distortion of the anatomical environment and, in turn, negatively alter the diagnostic performance of the novel posterior approach. This thesis further aimed to determine the impact of concurrent complex disease states on diagnostic performance.

We found enhanced diagnostic accuracy in the detection of endometriosis in the left USL, right USL, and TU compared to previous studies, with our sensitivity ranging from 75.0-100%, specificity of 100%, positive predictive values of 100%, and negative predictive value ranging from 88.6-100%. Furthermore, contrary to our hypothesis, diagnostic performance appeared unaffected by the presence of complex disease states. The ability to diagnose USL DE non-invasively can have profound implications for introducing personalized treatment plans in a timely manner, which should improve patient outcomes. With this enhanced diagnostic performance, fewer people will require a surgical diagnosis, which reduces the burden on the health system and decreases surgical complications associated with diagnostic surgery. / Thesis / Master of Science (MSc) / Endometriosis is a common gynecological disease involving the abnormal growth of uterine-like cells outside the uterus, causing significant negative impacts on quality of life and diagnostic delays. Deep endometriosis (DE) is the most aggressive form, infiltrating surrounding tissues and leading to complex disease states. The uterosacral ligaments (USLs; connective structures between the lower spine and uterus) are the most common site for DE, but diagnosing them non-invasively remains challenging, aiding the diagnostic delay. Following updated classification guidelines, the overarching aim of this thesis is to enhance our understanding of transvaginal ultrasound (TVS) as a safe and rapid diagnostic for DE of the USLs and TU. In doing so, this thesis aims to assess the accuracy of a new TVS technique for DE of the USLs and determine how other related health conditions might affect the accuracy of this diagnostic approach. The findings from this study indicate that using TVS could greatly assist in diagnosing DE in the USLs, potentially leading to more personalized treatment approaches by healthcare providers and better outcomes for individuals with endometriosis. In summary, this research contributes significantly to our understanding and management of this complex condition.

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29720
Date January 2024
CreatorsFreger, Shay
ContributorsLeonardi, Mathew, Medical Sciences
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

Page generated in 0.0024 seconds