Assessing Ultrasonographic Severity of Adenomyosis

NCT ID: NCT06117410

Last Updated: 2023-11-07

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-02-08

Study Completion Date

2026-02-28

Brief Summary

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The aim of this pilot study is to develop a feasible and quantifiable ultrasonographic method to grade the severity of adenomyosis and to determine the interobserver variation.

Detailed Description

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The investigators will conduct a prospective observational study in premenopausal women visiting the gynaecological outpatient clinic for an ultrasonographic exam. Patients are recruited when the diagnosis adenomyosis was made with transvaginal ultrasound (TVUS). Diagnosis adenomyosis requires at least one direct US feature of adenomyosis (subendometrial lines or buds, hyperechogenic islands or myometrial cysts). The sonographers obtain two-dimensional (2D) images, a grey-scale video-clip, elastography and power-doppler and micro-vascularity flow clips and images, and a three-dimensional (3D) uterine volume. The investigators will evaluate the collected images, clips and 3D-volumes with different methods to assess severity and test the feasibility and inter-observer agreement of these methods.

At the outpatient clinic, all real-time TVUS are assessed in a systematically manner by the sonographers and the presence of MUSA (Morphological Uterus Sonographic Assessment) features (subendometrial lines or buds, hyperechogenic islands or myometrial cysts, asymmetrical myometrium, globular uterus, translesional vascularity, fan-shaped shadowing, interrupted/irregular junctional zone) and an estimation of the affected myometrium, graded in mild (\<25% affected myometrium), moderate (25%-50% affected myometrium) or severe (\>50% affected myometrium) are reported. Clinical data, medical history, reason for visit, pain score in numeric rating scale (NRS), pictorial blood assessment chart (PBAC) score, etc. is collected.

Based on previous research and experience, four experts in gynaecological sonography select multiple offline methods using 5D Viewer software, for the evaluation and quantification of the severity of adenomyosis.

All the ultrasounds will be coded, so the assessors are blinded for patients demographics, medical history, symptomatology and the assessment by the sonographers.

Two experienced gynaecologist and one resident in gynaecology will test these methods for feasibility. Feasibility will be scored regarding technique, time and interpretation of MUSA features. The selected feasible methods will be tested for inter-observer variation. Finally a comparison of the severity evaluation by the assessors done with the new methods and the results of the severity estimation at the outpatient clinic will be made.

The method(s) that obtained a good feasibility score and good inter-observer agreement will consecutively be used in a follow-up study investigating the correlation with symptomatology, e.g. pain (NRS) and PBAC score.

Additionally, a descriptive study using the elastography and micro-vascularity flow images and clips will be performed.

The obtained data will be analysed to determine a total feasibility score, inter-observer variation and inter-test agreement. Inter-observer variation was tested with Fleiss Kappa or Intra Class Correlation Coefficient (ICC), depending on the data used. A kappa-coefficient of 0.41-0.60 or an ICC value of 05.-0.75 was set as moderate, κ0.51-0.80 or ICC 0.75-0.9 as good and κ≥0.80 or ICC ≥0.9 as excellent agreement. A Jonckheere-Terpstra test was used to test the trend of the new severity score and the estimated assessment of MUSA. Inter-test agreement was calculated with Cohens weighted Kappa (κw). For the correlation with NRS and PBAC intraclass correlation and Fleiss kappa were calculated and the mean severity outcomes were correlated with NRS and PBAC.

All women will sign an informed consent.

Conditions

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Adenomyosis Ultrasound

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* at least one direct MUSA feature (lines and buds, hyperechogenic islands, cysts)
* premenopausal, older than18 years

Exclusion Criteria

* hormonal medication
* other reason for gynaecological symptoms, more evident than adenomyosis, e.g. deep infiltrating endometriosis, dominant uterine fibroids (\>5cm, \>5 myoma, intracavitary myoma), cervical or endometrial cancer.
Minimum Eligible Age

18 Years

Maximum Eligible Age

60 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

No

Sponsors

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Amsterdam UMC, location VUmc

OTHER

Sponsor Role lead

Responsible Party

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J.A.F. Huirne

Prof. Dr.

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Amsterdam UMC, location AMC

Amsterdam, , Netherlands

Site Status RECRUITING

Countries

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Netherlands

Facility Contacts

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Judith Huirne, Prof. Dr.

Role: primary

020-5669111

Lisa Trommelen, MD.

Role: backup

0628212618

References

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Van den Bosch T, de Bruijn AM, de Leeuw RA, Dueholm M, Exacoustos C, Valentin L, Bourne T, Timmerman D, Huirne JAF. Sonographic classification and reporting system for diagnosing adenomyosis. Ultrasound Obstet Gynecol. 2019 May;53(5):576-582. doi: 10.1002/uog.19096. No abstract available.

Reference Type BACKGROUND
PMID: 29790217 (View on PubMed)

Harmsen MJ, Van den Bosch T, de Leeuw RA, Dueholm M, Exacoustos C, Valentin L, Hehenkamp WJK, Groenman F, De Bruyn C, Rasmussen C, Lazzeri L, Jokubkiene L, Jurkovic D, Naftalin J, Tellum T, Bourne T, Timmerman D, Huirne JAF. Consensus on revised definitions of Morphological Uterus Sonographic Assessment (MUSA) features of adenomyosis: results of modified Delphi procedure. Ultrasound Obstet Gynecol. 2022 Jul;60(1):118-131. doi: 10.1002/uog.24786.

Reference Type BACKGROUND
PMID: 34587658 (View on PubMed)

Other Identifiers

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2021.0035

Identifier Type: -

Identifier Source: org_study_id

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