CT Prediction for Transcatheter Tricuspid Interventions

NCT06951126 | Recruiting

• 1 other identifier: HDZ-KA CESAR-TR
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of this study is to enhance the predictability of therapeutic success in transcatheter tricuspid valve intervention (TTVI) for patients with severe tricuspid regurgitation (TR). This will be achieved through automated analyses of pre-interventional computed tomography (CT) scans. Severe tricuspid regurgitation is associated with poor patient outcomes. In advanced stages, pharmacological therapy becomes ineffective, and surgical intervention carries a high mortality risk. Given this clinical challenge, catheter-based treatment of the tricuspid valve has become a focal point of research. One well-established treatment strategy is percutaneous tricuspid valve intervention, which aims to reduce regurgitation either through annuloplasty, leaflet-based edge-to-edge repair or valve replacement. This approach has been shown to significantly decrease the severity of regurgitation, leading to a dramatic reduction in symptom burden and a marked improvement in quality of life. However, predicting which patients will benefit most from TTVI and determining the optimal technique for each individual remain largely unresolved challenges. Artificial intelligence (AI)-powered software, such as heart.ai by LARALAB (Munich), enables automated measurement of anatomical structures captured via CT imaging. This technology already allows for rapid and precise assessment of cardiac chambers and the tricuspid annulus throughout the entire cardiac cycle, facilitating a comprehensive three-dimensional evaluation of right heart anatomy. To refine patient selection and optimize procedural strategies for TR treatment, the researcher work a multi-center collaboration to analyze treatment outcomes and patient response to specific therapeutic approaches.

Conditions

Tricuspid Regurgitation; Computed Tomography

Keywords

transcatheter tricuspid valve intervention; TTVI; TR; MSCT; Tricuspid regurgitation

Outcome Measures

Primary Outcomes (1)

• Mortality

  Detection of mortality after transcatheter tricuspid intervention

  1 year

Secondary Outcomes (5)

• Residual Tricuspid Regurgitation

  At discharge, 30 days and 1 year

• rehospitalization rate

  1 year

• reintervention rate

  1 year

• NYHA Class

  30 days and 1 year

• Intraprocedural success

  30 days

Eligibility Criteria

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

Study Population

The study includes patients with \>moderate tricuspid regurgitation who underwent cardiac computed tomography and transcatheter tricupid valve intervention.

You may qualify if:

• the patient underwent full cycle cardiac computed tomography for analysis of valvular heart disease
• a transcatheter tricuspid valve intervention is performed
• the patient is 18 years or older

You may not qualify if:

• none

Sponsors & Collaborators

• Heart and Diabetes Center North-Rhine Westfalia: lead
• Ludwig-Maximilians - University of Munich: collaborator
• University Hospital Schleswig-Holstein: collaborator
• University of Cologne: collaborator
• Heart Center Leipzig - University Hospital: collaborator
• Charite University, Berlin, Germany: collaborator
• University of Bern: collaborator
• University Medical Center Mainz: collaborator

Study Sites (1)

Herz- und Diabeteszentrum

Bad Oeynhausen, North Rhine-Westphalia, 32545, Germany

RECRUITING

MeSH Terms

Conditions

Tricuspid Valve Insufficiency

Condition Hierarchy (Ancestors)

Heart Valve Diseases; Heart Diseases; Cardiovascular Diseases

Central Study Contacts

Johannes Kirchner, Dr. med.

CONTACT

0405731971258; jkirchner@hdz-nrw.de

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Dr. med.

Study Record Dates

• First Submitted: April 16, 2025
• First Posted: April 30, 2025
• Study Start: July 19, 2023
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 1, 2030
• Last Updated: April 30, 2025

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will not share

Locations

DE (1)