Research on Aneurysm Growth Prediction in Vascular Dilation Caused by Bicuspid Aortic Valve Based on VDM and CFD

NCT07782918 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2026-08-24

No results posted yet for this study

Summary

Bicuspid aortic valve (BAV) is the most common congenital valvular malformation, characterized by heterogeneous phenotypic subtypes that predispose patients to secondary aortic pathologies, including valvular dysfunction and ascending aortic dilation. With approximately 50% of BAV patients developing aortic dilation, a prevalence that continues to rise, accurate assessment of postoperative aortic remodeling remains a critical unmet clinical need for early risk stratification and optimized therapeutic decision-making. Currently, clinical surveillance relies heavily on periodic manual measurement of the maximum aortic diameter on follow-up computed tomography angiography (CTA), yet this approach suffers from several inherent limitations. It is a lagging indicator that detects irreversible wall damage only after significant enlargement has occurred. It oversimplifies complex three-dimensional morphological changes into a single linear dimension. It exhibits substantial intra- and inter-observer variability. It is also inefficient for large-scale longitudinal data management. Although alternative metrics such as computational fluid dynamics (CFD) derived hemodynamic parameters and morphological geometric features have been explored, existing methods remain constrained by static single-time-point analyses that fail to capture the dynamic biomechanical evolution driving aneurysm progression, high technical barriers that preclude routine clinical integration, and a lack of comprehensive models that systematically integrate dynamic deformation, static anatomy, and hemodynamic information. To address these gaps, this study aims to develop a fully automated, quantitative, and dynamic risk prediction system that leverages vascular deformation mapping (VDM) for noninvasive early detection of regional aortic deformation, integrates multiparameter features including dynamic deformational, static anatomical, and hemodynamic characteristics through an artificial intelligence model, and delivers intuitive structured reports to directly support clinical decision-making, thereby enabling earlier intervention and improved patient outcomes.

Conditions

  • Bicuspid Aortic Valve (BAV)
  • Aortic Aneurysm
  • TAVR

Interventions

PROCEDURE

Transcatheter Aortic Valve Replacement

Transcatheter Aortic Valve Replacement (TAVR) is a minimally invasive procedure in which a collapsible replacement valve is inserted via catheter through the femoral artery or other access routes and deployed within the native diseased aortic valve. In this study, TAVR was performed as standard clinical care in BAV patients with severe aortic stenosis or regurgitation. Post-procedural CTA imaging was obtained as part of routine follow-up to monitor aortic remodeling and detect potential dilation. The present study retrospectively analyzes the serial CTA images acquired before and after this procedure; no additional intervention is administered for research purposes.

Sponsors & Collaborators

  • First Affiliated Hospital of Wenzhou Medical University

    collaborator OTHER
  • Second Affiliated Hospital, Zhejiang University, School of Medicine

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-01
Primary Completion
2025-12-31
Completion
2026-02-01

Countries

  • China

Study Locations

More Related Trials

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 NCT07782918 on ClinicalTrials.gov