Bicuspid Aortic Valve (BAV)NCT07782918
Research on Aneurysm Growth Prediction in Vascular Dilation Caused by Bicuspid Aortic Valve Based on VDM and CFD
An observational study of Bicuspid Aortic Valve (BAV) and Aortic Aneurysm, run by Second Affiliated Hospital, Zhejiang University, School of Medicine at 2 sites in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 85 years
- Conditions the study is for
- Bicuspid Aortic Valve (BAV), Aortic Aneurysm, TAVR
- What is being tested?
- Transcatheter Aortic Valve Replacement
- Type of treatment
- Surgery or procedure
- How many people
- 1,000 participants
- Where
- 2 sitesChina
- Study dates
- 1 Jan 2020to 1 Feb 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 85 years
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- Patients are eligible for inclusion if they are male or non-pregnant female aged 18 to 85 years, diagnosed with Bicuspid Aortic Valve (BAV) by CTA, and have successfully undergone Transcatheter Aortic Valve Replacement (TAVR) with available pre-operative, post-operative (1-3 months), and follow-up (6-12 months) CTA imaging. The CTA scan range must cover cranially at least the origin of the brachiocephalic trunk, left common carotid artery, and left subclavian artery, and caudally at least the origin of the internal and external iliac arteries.
Who cannot join
- Patients are excluded if they have traumatic or iatrogenic aortic dissection, isolated aortic aneurysm without BAV, connective tissue disorders such as Marfan syndrome or Ehlers-Danlos syndrome, or prior cardiac or aortic surgery including surgical aortic valve replacement or aortic repair. Additional exclusions include insufficient number of CTA scans or inadequate scan range, poor CTA image quality due to motion artifacts or inadequate contrast enhancement precluding accurate segmentation, or image registration failure precluding completion of VDM analysis.
Trial locations and contacts
2 sites in 1 country.
China2 sites
The Second Affiliated Hospital of Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310009
The First Affiliated Hospital of Wenzhou Medical University
Wenzhou, Zhejiang, 325000
About this study
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.
Read the detailed description
This retrospective multi-center study aims to develop an automated AI system integrating Vascular Deformation Mapping (VDM) and Computational Fluid Dynamics (CFD) to predict aortic dilation risk in BAV patients after TAVR. Approximately 1,000 patients with pre-operative, post-operative, and follow-up CTA will be enrolled from two Chinese hospitals. The system automatically segments the aorta using 3D U-Net++, quantifies local deformation via deformable registration, and extracts dynamic, anatomical, and hemodynamic features. An XGBoost model trained on historical data (n=200) with 1-year outcomes outputs risk probability and category. The primary outcome is a validated prediction model; secondary outcomes include deformation pattern quantification and automated report generation. All data are anonymized. The target sample size is 1,000 patients.
- Conditions
- Bicuspid Aortic Valve (BAV), Aortic Aneurysm, TAVR
- Being tested
- Transcatheter Aortic Valve Replacement
- Keywords
- Bicuspid Aortic Valve, Aortic Dilation, Vascular Deformation Mapping, Risk Prediction
- Medical subject headings
- Bicuspid Aortic Valve Disease, Aortic Aneurysm
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Transcatheter Aortic Valve ReplacementProcedure or surgery
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Procedure: Transcatheter Aortic Valve Replacement |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: Post-TAVR 1-year follow-up
Secondary outcomes (3)
Quantification of Aortic Deformation via Vascular Deformation Mapping (VDM)
Aortic deformation is quantified by calculating the 3D displacement field between pre- and post-TAVR CTA images using a highly regularized deformable registration algorithm. The primary metric is the 90th percentile of radial displacement (mm) of the aortic surface. Higher values indicate greater local expansion.
Measured: Post-TAVR 3-month follow-up
Change in Aortic Dimensions Measured by Automated 3D Analysis
Change in maximum aortic diameter, cross-sectional area, and volume, automatically measured from 3D aortic models segmented by a deep learning algorithm. This provides a comprehensive assessment of morphological change beyond the traditional single-diameter measurement.
Measured: Post-TAVR 1-year follow-up (relative to pre-TAVR baseline)
Clinical Utility Assessment of the Automated Reporting System
The clinical utility of the automated system is evaluated by the proportion of successfully generated, structured clinical reports that are interpretable without manual correction. This outcome measures the feasibility of integrating this advanced AI-driven analysis into routine clinical workflow.
Measured: Upon study completion, up to 36 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Aug 2026
- Study start1 Jan 2020
- Primary completion31 Dec 2025
- Study completion1 Feb 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Bicuspid Aortic Valve (BAV)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- Second Affiliated Hospital, Zhejiang University, School of Medicine
- Sponsor type
- University, hospital or other
- Collaborators
- First Affiliated Hospital of Wenzhou Medical University
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07782918
- Sponsor's protocol ID
- 2026-0975
- Status last verified
- Jul 2026
- First submitted
- 19 Aug 2026
- Last updated
- 24 Aug 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Research on Aneurysm Growth Prediction in Vascular Dilation Caused by Bicuspid Aortic Valve Based on VDM and CFD
- ClinicalTrials.gov ID
- NCT07782918
- Acronym / sponsor ID
- 2026-0975
- Conditions
- Bicuspid Aortic Valve (BAV), Aortic Aneurysm, TAVR
- Keywords
- Bicuspid Aortic Valve, Aortic Dilation, Vascular Deformation Mapping, Risk Prediction
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,000 participants (actual)
- Lead sponsor
- Second Affiliated Hospital, Zhejiang University, School of MedicineUniversity, hospital or other
- Collaborators
- First Affiliated Hospital of Wenzhou Medical University
- Study start
- 1 Jan 2020 (actual)
- Primary completion
- 31 Dec 2025 (actual)
- Study completion
- 1 Feb 2026 (actual)
- First posted
- 24 Aug 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
This retrospective multi-center study aims to develop an automated AI system integrating Vascular Deformation Mapping (VDM) and Computational Fluid Dynamics (CFD) to predict aortic dilation risk in BAV patients after TAVR. Approximately 1,000 patients with pre-operative, post-operative, and follow-up CTA will be enrolled from two Chinese hospitals. The system automatically segments the aorta using 3D U-Net++, quantifies local deformation via deformable registration, and extracts dynamic, anatomical, and hemodynamic features. An XGBoost model trained on historical data (n=200) with 1-year outcomes outputs risk probability and category. The primary outcome is a validated prediction model; secondary outcomes include deformation pattern quantification and automated report generation. All data are anonymized. The target sample size is 1,000 patients.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| BAV with Aortic Dilation Cohort | – | Procedure: Transcatheter Aortic Valve ReplacementBicuspid 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. |
Who may qualify
- Ages
- 18 to 85 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (1 listed)
- Patients are eligible for inclusion if they are male or non-pregnant female aged 18 to 85 years, diagnosed with Bicuspid Aortic Valve (BAV) by CTA, and have successfully undergone Transcatheter Aortic Valve Replacement (TAVR) with available pre-operative, post-operative (1-3 months), and follow-up (6-12 months) CTA imaging. The CTA scan range must cover cranially at least the origin of the brachiocephalic trunk, left common carotid artery, and left subclavian artery, and caudally at least the origin of the internal and external iliac arteries.
Key exclusion criteria (1 listed)
- Patients are excluded if they have traumatic or iatrogenic aortic dissection, isolated aortic aneurysm without BAV, connective tissue disorders such as Marfan syndrome or Ehlers-Danlos syndrome, or prior cardiac or aortic surgery including surgical aortic valve replacement or aortic repair. Additional exclusions include insufficient number of CTA scans or inadequate scan range, poor CTA image quality due to motion artifacts or inadequate contrast enhancement precluding accurate segmentation, or image registration failure precluding completion of VDM analysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Transcatheter Aortic Valve ReplacementTranscatheter 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. | Procedure or surgery | BAV with Aortic Dilation Cohort |
Primary outcome
Development and Validation of a Multi-dimensional Risk Prediction Model for Aortic Dilation
Time frame: Post-TAVR 1-year follow-up
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.
3 secondary outcomes
Quantification of Aortic Deformation via Vascular Deformation Mapping (VDM)
Time frame: Post-TAVR 3-month follow-up
Change in Aortic Dimensions Measured by Automated 3D Analysis
Time frame: Post-TAVR 1-year follow-up (relative to pre-TAVR baseline)
Clinical Utility Assessment of the Automated Reporting System
Time frame: Upon study completion, up to 36 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Aug 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Bicuspid Aortic Valve (BAV) and Aortic Aneurysm, run by Second Affiliated Hospital, Zhejiang University, School of Medicine at 2 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Aug 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Development and Validation of a Multi-dimensional Risk Prediction Model for Aortic Dilation (time frame: Post-TAVR 1-year follow-up). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Aug 2026.