Validation and Optimisation of Ultrasound Diagnosis of Adenomyosis
ConditionAdenomyosis
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexFemale
Age18-60
SponsorIRCCS Azienda Ospedaliero-Universitaria di Bologna
About this trial
Defining ultrasound criteria for normal uterine biometry and assessing the prevalence of repeat abortions in patients with abnormalities of the uterine cavity
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
age between 18 and 60;
obtaining informed consent
Disqualifiers
Hysterectomised patients;
Virgo patients (hymenal integrity);
Patients reporting intolerance to transvaginal ultrasound;
Gynaecological oncology;
Trial population
Patients consecutively attending our ultrasound clinics for routine check-ups or pre-operative examinations will be included, as per regular practice. For the purposes of the analysis, patients will be divided into three groups according to the ultrasound and/or surgical diagnosis of A adenomyosis (presence of at least 2 ultrasound signs compatible with adenomyosis (MUSA) or presence of glands and endometrial stroma in myometrial location), B fibromatosis (uterus with inhomogeneous echostructure lacking 2 or more signs compatible with uterine adenomyosis or histological finding of several benign tumours consisting of smooth muscle tissue and fibrous tissue in varying proportions), C normal uterus (normal echostructure on transvaginal ultrasound)
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Not listed
Trial groups
No trial groups listed
Trial outcomes
Primary outcomes
1
Definition of uterine biometric parameters
Definition of uterine biometric parameters for the diagnosis of adenomyotic uterus (group A), fibromatous uterus (group B) and normal uterus (group C) by means of transvaginal ultrasound, performed as per the care procedure. Evaluation of the diagnostic capacity of 'globular uterus' for the diagnosis of adenomyosis as an additional parameter to those already known in the literature with possible subsequent identification of a biometric cut-off
Time frame
After enrollment on first visit2
Diagnostic capacity of 'globular uterus' for the diagnosis of adenomyosis
Evaluation of the diagnostic capacity of 'globular uterus' for the diagnosis of adenomyosis as an additional parameter to those already known in the literature with possible subsequent identification of a biometric cut-off
Time frame
After enrollment on first visitSecondary outcomes
1
Construction of deep learning models on uterine ultrasound images
Construction of deep learning models trained, validated and tested on uterine ultrasound images for the ultrasound diagnosis of adenomyosis and evaluation of their diagnostic accuracy
Time frame
After enrollment on first visit2
Evaluation of diagnostic accuracy of deep learning validated
Evaluation of diagnostic accuracy of deep learning validated for ultrasound diagnosis of adenomyosis
Time frame
After enrollment on first visit3
Identification of the frequency of finding ultrasound signs of adenomyosis in the cervix
In patients with a diagnosis of adenomyosis made on the basis of ultrasound features at the level of the uterine body and fundus
Time frame
After enrollment on first visit4
Evaluation of diagnostic accuracy
Evaluation of the diagnostic accuracy of trainees when experienced (identifying experienced operators as doctors in specialised training in Gynaecology and Obstetrics for at least four years, with an experience of at least 500 gynaecological ultrasound cases) and moderately experienced (identifying moderately experienced operators as doctors in specialised training in Gynaecology and Obstetrics for at least two years, with an experience of at least 200 gynaecological ultrasound cases
Time frame
After enrollment on first visitSponsors and contacts
Click on the lead sponsor to view all of their trials.
Source ClinicalTrials.gov