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Digital Twin and Ml-basEd MOdel of TEVAR Interventions

NCT07640828 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 5000

Last updated 2026-06-11

No results posted yet for this study

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.

Conditions

  • Aorta Disease
  • Aorta, Thoracic Pathologies

Sponsors & Collaborators

  • Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-02-11
Primary Completion
2026-09-30
Completion
2026-09-30

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07640828 on ClinicalTrials.gov