Digital Twin and ML-Driven Modeling of TEVAR Procedures
Official title: Digital Twin and Ml-basEd MOdel of TEVAR Interventions
Run by Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico · NCT07640828 · Data updated 2026-11-12
Aims to collect anonymized patient data and CT scans from people undergoing TEVAR to build a digital twin that can simulate results and help doctors choose devices and plan procedures.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 5000 (estimated) |
| Sponsor | Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico Academic / other |
| Locations | 1 site (Milan) |
| Status | Recruiting |
| Started | February 11, 2026 |
| Main results expected | March 31, 2027 |
| Study ends | March 31, 2027 |
| Registry record updated | November 4, 2026 |
| Trial ID | NCT07640828 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (18+) undergoing TEVAR for chronic or acute dissection, aneurysm, penetrating aortic ulcer, aortic thrombus, intramural hematoma, or traumatic injury.
✕Probably not a fit
Patients with poor CT image quality or anatomy unsuitable for high-fidelity 3D modeling may not benefit from the approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study collects clinical data and pseudonymized CT images from TEVAR patients to create an anatomical digital twin. The digital twin will be used to run simulations and train machine learning models for predicting procedural outcomes and complications. The goal is to improve preoperative planning, device selection, and risk prediction for TEVAR across aortic pathologies. The study builds on computational methods like finite element analysis and may inform future planning tools and training resources.
Why it matters
Potential benefit: If successful, clinicians may have improved ability to predict outcomes and tailor TEVAR choices to individual patients.
How similar studies have gone: There is prior evidence that computational modeling and machine learning can aid planning and risk prediction in TEVAR, though this digital twin approach is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * ≥18 Years and older (Adult, Older Adult) * Female and male * Received TEVAR for: Chronic or acute dissection, Aneurysm, Penetrating aortic ulcer, aortic thrombus, intramural hematoma or traumatic injury Exclusion Criteria: * Younger than 18 years old * Received TEVAR in surgical graft that replaced native aorta * Poor CT image quality that leads to failure in generating a high-fidelity 3D FE model of patient anatomy (no preoperative multidetector contrast-enhanced CT-scan available, preoperative CTscan slice thickness greater than 1mm, preoperative CT-scan with artifacts, motion artifacts due to the presence of other implanted devices affecting the region of interest)
Where it's running
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Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico
Milan, Italy Recruiting
Study contacts
- Study coordinator: Santi Trimarchi, Md, Phd
- Email: santi.trimarchi@policlinico.mi.it
- Phone: +390255032438
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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.