Endometriosis
Conditions
Keywords
endometriosis, gynaecology, surgery, uterus sacral ligaments
Brief summary
Ultrasound features most indicative of endometriosis of the uterosacral ligaments, which connect the cervix to the sacrum and are part of the uterus support structures, and verify the actual presence of endometriosis of these ligaments during surgery
Detailed description
It is estimated that 1 in 10 women of childbearing age is affected by endometriosis. Objective examination alone is not sufficient to frame the pathology as the anatomic-clinical correspondence is relatively low: symptoms are not lesion specific and there may be asymptomatic women with pictures of severe endometriosis. Accurate diagnosis of all endometriosis by transvaginal ultrasound at the preoperative stage is therefore essential to discriminate patients who need surgery from those who can benefit from medical therapy alone, but also to be able to select a surgeon with adequate experience for this type of surgery. In recent years, moreover, it has been highlighted that ureteral endometriosis is associated with ipsilateral LUS injury. Ureteral damage has a nuanced symptomatology and cases in which the patient manifests signs and symptoms suggestive of renal resentment are rare (flank pain, renal colic, hypertension). Ureteral involvement can therefore lead to a silent loss of renal function, which in some cases requires nephrectomy. Several studies have already shown that there is a correlation between ureteral endometriosis and uterosacral ligaments (LUS) endometriosis, and that the likelihood of ureteral involvement increases with increasing nodule size. In light of this evidence and in order to improve the diagnostic power of the ultrasound method, it is therefore important to find the best combination of ultrasound parameters to predict endometriosis in LUS with sufficient accuracy.
Interventions
None listed
Sponsors
IRCCS Azienda Ospedaliero-Universitaria di Bologna
Study design
Observational model
CASE_CONTROL
Time perspective
OTHER
Eligibility
Sex/Gender
FEMALE
Age
18 Years to 50 Years
Healthy volunteers
No
Inclusion criteria
* Women with a clinical and/or ultrasound diagnosis of endometriosis who are candidates for surgery; * Age between 18 and 50 years; * Signature of informed consent to the study
Exclusion criteria
* Post-menopausal women (spontaneous or iatrogenic); * Virgo patients; * Hysterectomised patients; * Pregnant patients; * Patients undergoing pelvic/vaginal radiotherapy; * Previous LUS surgery; * Clinical diagnosis of pelvic organ prolapse; * Preoperative ultrasound more than 60 days prior to surgery; * Failure at surgery and any subsequent histopathological examination to find pelvic endometriosis
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic ability of anteroposterior LUS thickness | During the first visit after enrollment | Comparison of the average thickness in millimetres of LUS with endometriosis and healthy LUS. The thickness cut-off of the LUS with highest diagnostic accuracy will be calculated by Receiver operating characteristic (ROC) curves |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Learning curve of average experienced operators (Doctors in Specialised Training, MFS) in acquiring the optimal measurement of anteroposterior LUS thickness | During the first visit after enrollment | The agreement between the measurements of the two experienced operators and between those of the average experienced operators will be studied by calculating the measurement error using the Bland-Altman plot. The cumulative sum test for the learning curve (LC-CUSUM) will then be used to evaluate the learning curve |
| Evaluation of ultrasound parameters and differences between the two study groups | During the first visit after enrollment | Comparison of the prevalence of the above-mentioned ultrasound features in the two groups (ratio of the number of sick LUSs with one of the features to the total number of sick LUSs - ratio of the number of healthy LUSs with one of the features to the total number of healthy LUSs), analysing them both individually and in combination until the combination with the best sensitivity and specificity is identified |
Countries
Italy
Outcome results
None listed