Digital Twin and Ml-basEd MOdel of TEVAR Interventions

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.

NCT Number	NCT07640828
Lead Sponsor	Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico
Conditions	Aorta Disease, Aorta, Thoracic Pathologies
Enrollment	5,000 participants
Start Date	2026-02-11
Primary Completion	2026-09-30 (estimated)
Study Completion	2026-09-30 (estimated)
Updated on ClinicalTrials.gov	2026-06-11