Ventricular Arrythmia Clinical Trial
— MATRIX-VTOfficial title:
New 3D-echocardiography-based Motion Integration and mAnagement for subsTrate characteRisation and Stereotactic Arrhythmia radIoablation tX in Ventricular Tachycardias- the MATRIX-VT Study
NCT number | NCT05964660 |
Other study ID # | MATRIX-VT |
Secondary ID | |
Status | Not yet recruiting |
Phase | |
First received | |
Last updated | |
Start date | August 2023 |
Est. completion date | June 2024 |
Verified date | July 2023 |
Source | University of Luebeck |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
Prospective, observational, single center, pilot study to analyze the feasibility of motion and structural data integration in patients with ventricular arrhythmia by means of artificial intelligence for improved arrhythmogenic substrate characterization and motion management during stereotactic arrhythmia radioablation.
Status | Not yet recruiting |
Enrollment | 20 |
Est. completion date | June 2024 |
Est. primary completion date | June 2024 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 100 Years |
Eligibility | Inclusion Criteria: - Age = 18 years - Indication for catheter ablation of ventricular arrhythmias (ventricular fibrillation, ventricular tachycardia, premature ventricular contractions) - Indication for preprocedural contrast-enhanced cardiac computed tomography for cardiac structure characterization Exclusion Criteria: - Platelet count < 100,000 cells/mm3 - BMI > 45 kg/m2 or < 18 kg/m2 |
Country | Name | City | State |
---|---|---|---|
Germany | Klinik für Rhythmologie | Luebeck | Schleswig-Holstein |
Lead Sponsor | Collaborator |
---|---|
University of Luebeck | Institute for Robotics and Cognitive Systems, University of Luebeck |
Germany,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Feasibility of algorithm training to achieve improved arrhythmogenic substrate characterization | The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the ventricular arrhythmogenic substrate in patients exhibiting ventricular arrhythmias. | 1 month after complete data collection | |
Primary | Feasibility of algorithm training to improve the planning target volume definition for stereotactic arrhythmia radioablation therapy | The feasibility of training the artificial intelligence-based algorithm using the preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography data to better define the planning target volume for stereotactic arrhythmia radioablation therapy | 1 month after complete data collection |
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