Echocardiography-based Motion Integration and Management for Substrate Characterization and STAR Therapy in Ventricular Tachycardias

University of Luebeck20 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Ventricular Arrythmia

Eligibility

Sex: ALLMin age: 18 YearsMax age: 100 YearsHealthy volunteers:

Medical Language ↔ Plain English

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

Locations (1)

Klinik für Rhythmologie

Lübeck, Schleswig-Holstein, Germany

RECRUITING

Outcomes

Primary Outcomes

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

Data from ClinicalTrials.gov

This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.