Innovative Non-Invasive Diagnostics and Personalized Treatment Strategies for Endometriosis Through Advanced Multi-Omics and Ultrasound Integration (ENDO-NOVA)
Innovativa Icke-invasiva Diagnostiska Och Personliga Behandlingsstrategier för Endometrios Genom Avancerad Multi-omik Och Ultraljudsintegration
Endometriosis is a prevalent gynecological condition affecting approximately 10% of women of reproductive age worldwide. It presents with nonspecific but often severe symptoms, including chronic pelvic pain (in 70% of cases) and infertility (in up to 40% of cases), imposing significant physical, psychological, economic, and societal burdens. Despite its widespread occurrence, the exact etiology and pathogenesis of endometriosis remain unclear, and no definitive cure exists. Early diagnosis and management are crucial for improving patient outcomes; however, major diagnostic delays persist. Current imaging techniques such as transvaginal ultrasound (TVUS) examination and magnetic resonance imaging, along with biochemical markers lack sufficient specificity. Consequently, confirmation of diagnosis still requires surgical procedures under general anesthesia, i.e.
laparoscopy ("key-hole surgery") and tissue biopsy. This delay exacerbates the disease burden and healthcare costs, underscoring the urgent need for non-invasive, precise diagnostic strategies. This project proposes a multi-modal approach integrating advanced ultrasound imaging with novel biomarkers identified via comprehensive multi-omics analyses, including proteomics, transcriptomics, and immune profiling, of patient-derived endometrial organoids. It aims to understand the underlying mechanisms of reduced endometrial receptivity of embryos in patients with endometriosis. Additionally, we will explore personalized treatment strategies by utilizing patient-specific organoids for drug screening and evaluation of treatment response.
This project aims to develop a non-invasive diagnostic strategy by integrating:
- AI-enhanced TVUS for improved lesion detection.
- Multi-omics biomarker discovery through proteomics, transcriptomics, and immune profiling.
- Underpinning the mechanisms of reduced endometrial receptivity in endometriosis using an in vitro model of embryo-endometrium interaction.
- Endometrial organoid models to enable precision medicine-based drug testing. The development of a reliable noninvasive or minimally invasive diagnostic test-or a combination of tests-could revolutionize the diagnostic pathway by reducing delays, avoiding the need for surgery, and facilitating disease monitoring and treatment evaluation.
Aperçu de l'étude
Statut
Les conditions
Intervention / Traitement
Type d'étude
Inscription (Estimé)
Contacts et emplacements
Coordonnées de l'étude
- Nom: Stefhanie Romero Andersson, MD, PhD, MSc
- Numéro de téléphone: 0046707822742
- E-mail: stefhanie.romero.andersson@ki.se
Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
- Adulte
Accepte les volontaires sains
Méthode d'échantillonnage
Population étudiée
La description
Inclusion Criteria:
- Women aged 18-45
- Understands and speaks the Swedish language
- Suspected or confirmed endometriosis
Exclusion Criteria:
- Do not have a uterus
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
Cohortes et interventions
Groupe / Cohorte |
Intervention / Traitement |
|---|---|
|
1
Never had treatment
|
Diagnosis using AI-enhanced transvaginal ultrasound, multi-omics, and organoids
|
|
2
Ongoing treatment
|
Diagnosis using AI-enhanced transvaginal ultrasound, multi-omics, and organoids
|
|
3
No actual treatment (has had treatment before)
|
Diagnosis using AI-enhanced transvaginal ultrasound, multi-omics, and organoids
|
Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
|
Diagnostic accuracy of the combined AI-assisted transvaginal ultrasound and multi-omics biomarker model for detection of endometriosis
Délai: At baseline diagnostic evaluation
|
Sensitivity and specificity of a combined diagnostic model integrating AI-assisted interpretation of transvaginal ultrasound images with plasma, saliva, urine, and endometrial-derived biomarkers for the detection of endometriosis, using laparoscopic diagnosis with or without histological confirmation as the reference standard.
|
At baseline diagnostic evaluation
|
Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
|
Diagnostic accuracy of AI-assisted transvaginal ultrasound alone
Délai: Baseline
|
To evaluate the performance of AI-assisted transvaginal ultrasound (TVUS) for detection and classification of endometriosis lesions.
|
Baseline
|
|
Diagnostic performance of plasma and endometrial biomarker panel
Délai: Baseline sample collection
|
To assess the ability of plasma and endometrial-derived biomarkers to detect endometriosis, disease stage, and correlate to clinical symptoms.
|
Baseline sample collection
|
|
Implantation rate in in vitro endometrial models
Délai: Periprocedural/ During in vitro culture period (e.g., up to 5-10 days)
|
To compare the attachment rate of embryo-derived or stem cell-derived embryonic structures (blastoids) to endometrial tissue from women with and without endometriosis.
|
Periprocedural/ During in vitro culture period (e.g., up to 5-10 days)
|
|
Molecular characteristics associated with embryo/blastoid attachment
Délai: Periprocedural/During in vitro experiments
|
To evaluate transcriptomic and hormonal differences between successfully and unsuccessfully attaching embryos or blastoids.
|
Periprocedural/During in vitro experiments
|
|
Organoid drug response variability and association with disease characteristics
Délai: At baseline sample collection and through study completion (around 3 years)
|
To evaluate variability in response to hormonal and immune-targeted therapies in organoids and association with disease severity.
|
At baseline sample collection and through study completion (around 3 years)
|
Collaborateurs et enquêteurs
Parrainer
Collaborateurs
Les enquêteurs
- Chaise d'étude: Ronak Perot, MD, Region Stockholm
- Chaise d'étude: Lars Henningsohn, MD,Prof, Karolinska Institutet
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Estimé)
Achèvement primaire (Estimé)
Achèvement de l'étude (Estimé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Mots clés
Termes MeSH pertinents supplémentaires
Autres numéros d'identification d'étude
- DNR 2025-03336-01
Plan pour les données individuelles des participants (IPD)
Prévoyez-vous de partager les données individuelles des participants (DPI) ?
Informations sur les médicaments et les dispositifs, documents d'étude
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