Tricuspid valve assessment by automated deep learning algorithms

Tricuspid valve assessment by automated deep learning algorithms - TriDL

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00032042

Enrollment

150

Registered

2023-06-14

Start date

2022-02-11

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

tricuspid regurgitation

Interventions

Group 1: Patients after interventional therapy of the tricuspid valve

Eligibility

Sex/Gender

All

Age

18 Years to 18 Years

Inclusion criteria

Inclusion criteria: Patients who underwent interventional TR therapy Cardiac CT as part of routine clinical practice Written, informed consent (prospective data collection)

Exclusion criteria

Exclusion criteria: Patients who are not capable of providing consent (prospective data collection).

Design outcomes

Primary

Measure	Time frame
tricuspid valave anatomy, right heart anatomy and function	—

Secondary

Measure	Time frame
Correlation with interventional and clinical outcome Duration of meassurements with manual assesment and deep learning software	—

Countries

Germany

Contacts

Public ContactIsabel Mattig

Deutsches Herzzentrum der Charité

isabel.mattig@dhzc-charite.de+4930450613305

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026