Digital Twin and Ml-basEd MOdel of TEVAR Interventions
Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
5,000 participants
Feb 11, 2026
OBSERVATIONAL
Conditions
Summary
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
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07640828