New 3D-echocardiography-based Motion Integration and mAnagement for subsTrate characteRisation and Stereotactic Arrhythmia radIoablation tX in Ventricular Tachycardias- the MATRIX-VT Study
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 20
- 试验地点
- 1
- 主要终点
- Feasibility of algorithm training to improve the planning target volume definition for stereotactic arrhythmia radioablation therapy
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •Platelet count < 100,000 cells/mm3
- •BMI > 45 kg/m2 or < 18 kg/m2
结局指标
主要结局
Feasibility of algorithm training to improve the planning target volume definition for stereotactic arrhythmia radioablation therapy
时间窗: 1 month after complete data collection
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
Feasibility of algorithm training to achieve improved arrhythmogenic substrate characterization
时间窗: 1 month after complete data collection
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.
次要结局
未报告次要终点
研究者
Prof. Roland Richard Tilz
Professor Dr. med.univ.
University of Luebeck