The study aims to collect clinical data and pseudonymized CT images of patients undergoing TEVAR in order to create an anatomical digital twin capable of simulating procedural outcomes and training machine learning (ML) algorithms. This approach will support predictive models that may assist physicians in selecting the optimal medical device, improving pre-TEVAR planning, and predicting post-TEVAR complications.
Eligibility
Sex
ALL
Min age
18 Years
Max age
—
Healthy volunteers
No
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)
Primary outcome measure(s)
Determine the accuracy of patient-specific numerical simulations in replicating TEVAR deployment outcomes — up to 1 year Accuracy of the simulations, expressed in terms of the match between simulated and post-operative device-vessel interaction (e.g., configuration, sealing quality, apposition), as assessed via comparison of post-operative CT image with the simulation results
Trial sites (1)
Facility
City
Region
Status
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico
Milan
Italy
Recruiting
More Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico trials in Italy
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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