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

NCT07782918 | Completed DMC

• 1 other identifier: 2026-0975
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 2

Brief 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

Keywords

Bicuspid Aortic Valve; Aortic Dilation; Vascular Deformation Mapping; Risk Prediction

Outcome Measures

Primary Outcomes (1)

• Development and Validation of a Multi-dimensional Risk Prediction Model for Aortic Dilation

  The model is developed using machine learning (XGBoost) integrating dynamic deformation features (e.g., radial displacement percentiles from VDM), static anatomical features (e.g., aneurysm volume), and optional hemodynamic features (e.g., wall shear stress from CFD). Model performance (discrimination and calibration) will be assessed using the Area Under the Receiver Operating Characteristic Curve (AUC) and calibration plots. The outcome is the model's predictive accuracy for aortic dilation status.

  Post-TAVR 1-year follow-up

Secondary Outcomes (3)

• Quantification of Aortic Deformation via Vascular Deformation Mapping (VDM)

  Post-TAVR 3-month follow-up

• Change in Aortic Dimensions Measured by Automated 3D Analysis

  Post-TAVR 1-year follow-up (relative to pre-TAVR baseline)

• Clinical Utility Assessment of the Automated Reporting System

  Upon study completion, up to 36 months

Study Arms (1)

BAV with Aortic Dilation Cohort

Bicuspid Aortic Valve (BAV) patients aged 18-85 years who have successfully undergone Transcatheter Aortic Valve Replacement (TAVR) and have available pre-operative, post-operative, and follow-up CTA imaging with scan coverage from supra-aortic branches to iliac arteries. Patients with connective tissue disorders (e.g., Marfan syndrome), prior cardiac/aortic surgery, traumatic or iatrogenic dissection, or insufficient imaging quality will be excluded. All enrolled patients will be retrospectively analyzed as a single observational cohort to develop and validate an AI-based risk prediction model for aortic dilation. No intervention or randomization is applied.

Procedure: Transcatheter Aortic Valve Replacement

Interventions

Transcatheter Aortic Valve Replacement PROCEDURE

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.

BAV with Aortic Dilation Cohort

Eligibility Criteria

• Age: 18 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Approximately 1,000 BAV patients who underwent TAVR will be retrospectively enrolled from two Chinese tertiary hospitals. Eligible patients are aged 18-85 years with serial CTA (pre-op, post-op, follow-up) covering the aorta from supra-aortic branches to iliac arteries. Exclusions: connective tissue disorders, prior aortic surgery, dissection, isolated aneurysm, poor image quality, or registration failure. No additional interventions are administered. All patients are analyzed as a single observational cohort.

Sponsors & Collaborators

• Second Affiliated Hospital, Zhejiang University, School of Medicine: lead
• First Affiliated Hospital of Wenzhou Medical University: collaborator

Study Sites (2)

The Second Affiliated Hospital of Zhejiang University School of Medicine

Hangzhou, Zhejiang, 310009, China

Location

The First Affiliated Hospital of Wenzhou Medical University

Wenzhou, Zhejiang, 325000, China

Location

MeSH Terms

Conditions

Bicuspid Aortic Valve Disease; Aortic Aneurysm

Interventions

Transcatheter Aortic Valve Replacement

Condition Hierarchy (Ancestors)

Heart Defects, Congenital; Cardiovascular Abnormalities; Cardiovascular Diseases; Heart Diseases; Aortic Valve Disease; Heart Valve Diseases; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Aneurysm; Vascular Diseases; Aortic Diseases

Intervention Hierarchy (Ancestors)

Heart Valve Prosthesis Implantation; Cardiac Surgical Procedures; Cardiovascular Surgical Procedures; Surgical Procedures, Operative; Prosthesis Implantation; Thoracic Surgical Procedures

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 19, 2026
• First Posted: August 24, 2026
• Study Start: January 1, 2020
• Primary Completion: December 31, 2025
• Study Completion: February 1, 2026
• Last Updated: August 24, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share

Locations

CN (2)