- ICH GCP
- US-Register für klinische Studien
- Klinische Studie NCT07810920
Artificial Intelligence Into Ultrasound Diagnostics in Reproductive Medicine (AUDRIE)
Innovation for Women's Health: the Integration of Artificial Intelligence in the Diagnostic Ultrasound Assessment of Reproductive Medicine
The goal of this observational study is to develop and validate artificial intelligence (AI)-based algorithms that support ultrasound diagnosis of endometriosis, adenomyosis, myometrial masses, uterine malformations, and impaired endometrial receptivity in women aged 18-45 years. The main questions it aims to answer are:
Can AI algorithms, applied to standardized transvaginal ultrasound images, accurately detect and classify endometriosis and adenomyosis in real time during routine examination? Can AI-based ultrasound assessment predict the histological dignity of myometrial masses, and the likelihood of successful assisted reproduction (AR/IVF) outcome from endometrial features?
Participants attending the Department of Obstetrics and Gynecology, Semmelweis University, with clinical suspicion of endometriosis or adenomyosis, a confirmed myometrial mass scheduled for surgery, a suspected uterine anomaly, or scheduled IVF treatment, will undergo standardized transvaginal ultrasound examination (following the IDEA, MUSA, and IETA protocols) alongside collection of clinical, questionnaire, and, where surgery is performed, histopathological data. Imaging and clinical data will be used to build a database supporting the development and validation of the AI algorithms.
Studienübersicht
Status
Studientyp
Einschreibung (Geschätzt)
Kontakte und Standorte
Studienkontakt
- Name: Nandor Acs, PhD
- Telefonnummer: +3620825001
- E-Mail: acs.nandor@semmelweis.hu
Studienorte
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Budapest
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Budapest, Budapest, Ungarn, 1088
- Rekrutierung
- Department of Obstetrics and Gynecology, Semmelweis University
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Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
- Erwachsene
Akzeptiert gesunde Freiwillige
Probenahmeverfahren
Studienpopulation
Beschreibung
Inclusion Criteria:
- Women aged 18-45 years with clinical suspicion of endometriosis or adenomyosis, in whom the diagnosis of endometriosis is subsequently confirmed, including peritoneal, ovarian, and deep infiltrating endometriosis. The diagnosis is established by imaging, laparoscopy, or laparotomy, based on characteristic intraoperative findings and histological analysis (#Enzian classification).
- Women undergoing ultrasound examination for suspected congenital uterine anomaly or other intracavitary uterine pathology.
- Women with previously confirmed leiomyoma scheduled for surgical treatment.
- Women scheduled for IVF treatment or embryo transfer.
- Willingness and capacity to provide written informed consent prior to enrolment.
Exclusion Criteria:
- TVUS is not technically feasible.
- Postmenopausal status.
- Pregnancy.
- Puerperium (up to 3 months postpartum).
- Suspected premalignancy, or presence or history of malignancy.
- Chronic comorbidities, including uncontrolled diabetes mellitus, severe cardiovascular or respiratory disease, systemic autoimmune disease, or uncontrolled thyroid dysfunction.
- Other conditions, including psychiatric illness or substance use, and any circumstance in which study participation could pose a risk to the patient, or in which enrolment could bias the study results.
- For the endometrial receptivity sub-study, confirmed uterine or endometrial pathology other than adenomyosis.
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
Kohorten und Interventionen
Gruppe / Kohorte |
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Endometriosis cohort
Women aged 18-45 years with clinical suspicion of endometriosis, in whom the diagnosis is subsequently confirmed by laparoscopy or laparotomy with histological analysis of the resected specimen (peritoneal, ovarian, or deep infiltrating endometriosis).
No intervention is administered; participants undergo a standardized transvaginal ultrasound examination (IDEA protocol) and complete clinical and quality-of-life questionnaires (NRS, EHP-30) as part of routine care.
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Ademyosis cohort
Women aged 18-45 years with clinical suspicion of adenomyosis, assessed by standardized transvaginal ultrasound (MUSA protocol) for direct and indirect sonographic features, morphological subtype, and severity.
No intervention is administered; assessment occurs as part of routine gynecological care.
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Myometrial mass cohort
Women aged 18-45 years with a previously confirmed uterine leiomyoma scheduled for surgical treatment.
Participants undergo standardized ultrasound assessment of leiomyoma location, size, and sonographic features prior to surgery, with post-surgical histopathological correlation.
No intervention is administered beyond standard-of-care surgical treatment already planned.
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Uterine malformation cohort
Women aged 18-45 years undergoing ultrasound examination for suspected congenital (Müllerian) uterine anomaly or other intracavitary uterine pathology.
Participants undergo standardized ultrasound assessment; no intervention is administered.
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Endometrial receptivity cohort
Women aged 18-45 years scheduled for IVF treatment or embryo transfer, without confirmed uterine or endometrial pathology other than adenomyosis.
Participants undergo standardized ultrasound assessment of endometrial thickness, morphology, and vascularity (IETA protocol) around the window of implantation, linked to subsequent assisted reproduction treatment and pregnancy outcome.
No intervention is administered.
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Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Maßnahmenbeschreibung |
Zeitfenster |
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Diagnostic accuracy of the AI algorithm for detection of endometriosis and adenomyosis on transvaginal ultrasound
Zeitfenster: 3 years
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Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the AI-based detection algorithm for endometriosis and adenomyosis, assessed against the reference standard of surgical findings and histopathological confirmation (for participants undergoing surgery) or, where surgery is not performed, expert consensus review of the standardized ultrasound examination.
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3 years
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Mitarbeiter und Ermittler
Sponsor
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn (Tatsächlich)
Primärer Abschluss (Geschätzt)
Studienabschluss (Geschätzt)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Tatsächlich)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Tatsächlich)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Schlüsselwörter
Zusätzliche relevante MeSH-Bedingungen
- Urogenitale Erkrankungen
- Genitalerkrankungen
- Urogenitale Neoplasmen
- Neubildungen nach Standort
- Neubildungen
- Weibliche Urogenitalerkrankungen
- Weibliche Urogenitalerkrankungen und Schwangerschaftskomplikationen
- Bindegewebserkrankungen
- Neubildungen nach histologischem Typ
- Uteruserkrankungen
- Genitalerkrankungen, weiblich
- Genitale Neubildungen, weiblich
- Neubildungen, Binde- und Weichgewebe
- Neubildungen, Bindegewebe
- Neubildungen, Muskelgewebe
- Unfruchtbarkeit
- Angeborene, erbliche und neonatale Krankheiten und Anomalien
- Haut- und Bindegewebserkrankungen
- Angeborene Anomalien
- Adenomyose
- Unfruchtbarkeit, weiblich
- Endometriose
- Uterusneoplasmen
- Leiomyom
- Myofibrom
Andere Studien-ID-Nummern
- BM/13222-3/2026
Plan für individuelle Teilnehmerdaten (IPD)
Planen Sie, individuelle Teilnehmerdaten (IPD) zu teilen?
Beschreibung des IPD-Plans
The dataset contains transvaginal ultrasound images and linked histopathological and clinical data, which carry a high re-identification risk even after anonymization, particularly given the imaging modality and the relatively narrow, well-defined patient population.
Data processing and storage are governed by a data-sharing agreement between Semmelweis University and GE HealthCare Hungary Ltd., under which anonymized data are accessible only to authorized GE HealthCare personnel on a secure, access-restricted, encrypted server, in compliance with the EU General Data Protection Regulation (GDPR). This arrangement does not extend to third-party researchers outside the collaboration.
Arzneimittel- und Geräteinformationen, Studienunterlagen
Studiert ein von der US-amerikanischen FDA reguliertes Arzneimittelprodukt
Studiert ein von der US-amerikanischen FDA reguliertes Geräteprodukt
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