An observational study in Ventricular Arrythmia, sponsored by University of Luebeck. Recruiting at 1 site in Germany. Open to participants aged 18 Years to 100 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-08-29.
Sponsored by University of Luebeck · 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.
This is a prospective, observational, single center, pilot study. Data from preprocedural contrast-enhanced cardiac computed tomography and optically-tracked 3D transthoracic echocardiography of patients receiving catheter ablation for ventricular arrhythmia will be analyzed by means of artificial intelligence in order to better characterize the ventricular arrhythmogenic substrate and to improve the definition methods of the planning target volume during the stereotactic arrhythmia radioablation therapy by integrating the motion data into volume demarcation.
885 studies on the registry are indexed under Arrhythmias, Cardiac; 235 are open to participants now.
This study's planned enrollment of 20 is below the median of 200 across 414 observational studies indexed under Arrhythmias, Cardiac.
Browse Arrhythmias, Cardiac studies →University of Luebeck is the lead sponsor of 74 studies on the registry; 13 are open to participants now.
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A total of 20 patients with indication for catheter ablation of ventricular arrhythmia (VA) (ventricular tachycardia (VT), ventricular fibrillation (VF), premature ventricular contraction (PVC)) and for preprocedural contract-enhanced cardiac computed tomography (CT) for cardiac structure characterization will be prospectively enrolled in the study. The therapeutic approach follows the current clinical standard.
Exclusion Criteria:
Patients with indication for catheter ablation of ventricular arrhythmia and preprocedural contrast-enhanced cardiac computed tomography for cardiac structure characterization.
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.
Time frame: 1 month after complete data collection
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
Time frame: 1 month after complete data collection
Plan to share: No
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University of Luebeck