Collecting ultrasound images to improve DVT detection
Official title: A Multi-center Cohort Study for Conventional Ultrasound Image Set Collection to Create a Training Data Set for Research Purposes (Image Processing and Analysis, AI Model Training).
Run by ThrombUS+ · NCT06989255 · Data updated 2026-11-12
This study is collecting ultrasound images from patients suspected of having deep vein thrombosis to see if using these images can help train an AI to detect DVT more accurately.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 3000 (estimated) |
| Sponsor | ThrombUS+ Academic / other |
| Locations | 5 sites (Montmorency and 4 other locations) |
| Status | Recruiting |
| Started | November 6, 2024 |
| Main results expected | December 31, 2025 |
| Study ends | December 31, 2025 |
| Registry record updated | May 25, 2025 |
| Trial ID | NCT06989255 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are adults aged 18 and older who are suspected of having DVT and require an ultrasound scan as part of their clinical assessment.
✕Probably not a fit
Patients who are not suitable for a standard ultrasound scan or who have conditions that may interrupt the examination will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study aims to gather and create a labeled dataset of ultrasound images and videos from patients undergoing routine scans for suspected deep vein thrombosis (DVT). The collected data will include patient demographics, medical history, and details about the ultrasound equipment used. The primary goal is to anonymize this dataset for research purposes, specifically to train an AI model for automated DVT detection. By improving the accuracy of DVT diagnosis, the study seeks to enhance patient safety and outcomes related to this serious condition.
Why it matters
Potential benefit: If successful, this study could lead to more accurate and timely detection of deep vein thrombosis, potentially reducing the risk of serious complications like pulmonary embolism.
How similar studies have gone: Other studies have shown promise in using AI for medical imaging, suggesting that this approach could be effective in improving DVT detection.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥18 years. * The participant has the capacity to consent, and consent is obtained prior to any study-specific procedures. * The conventional diagnostic DVT algorithm indicates that an ultrasound is needed, or the patient has been referred for a scan on suspicion of DVT. Exclusion Criteria: * Patients with a known condition or reason that may potentially result in interrupting or stopping the ultrasound examination before its completion. * Patients considered by their treating physician or the ultrasound operator as non-suitable for a standard ultrasound scan. * Patients who have not signed the informed consent.
Where it's running
-
Groupement Hospitalier Eaubonne Montmorency Simone Veil
Montmorency, France Recruiting -
University General Hospital of Alexandroupoli
Alexandroupoli, Greece Recruiting -
Papageorgiou General Hospital
Thessaloniki, Greece Recruiting -
Home Relief of Suffering Hospital
San Giovanni Rotondo, Italy Recruiting -
Lithuanian University of Health Science
Kaunas, Lithuania Recruiting
Study contacts
- Principal investigator: Andrius Macas, Prof. Dr. — Lithuanian University of Health Science [Lietuvos Sveikatos Mokslu Universitetas], Lithuania
- Study coordinator: Eleni Kaldoudi, Prof.
- Email: kaldoudi@athenarc.gr
- Phone: +306937124358
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.