Improved arrhythmia ablation via MR-guided robotic catheterization and multimodal clinician feedback

通过 MR 引导的机器人导管插入术和多模式临床医生反馈改善心律失常消融

• 批准号: 10638497
• 负责人: Yue Chen
• 金额: $ 64.03万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-26 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10638497
• 关键词: 3-Dimensional; Ablation; Acute; Address; Algorithms; Animals; Arrhythmia; Atrial Fibrillation; Cardiac; Cardiac ablation; Cardiomyopathies; Catheterization; Catheters; Chronic; Clinical; Computer software; Electrophysiology (science); Ensure; Environment; Family suidae; Feedback; Heart; Heart Diseases; Heart failure; Hybrids; Iatrogenesis; Image; Incidence; Injury; Left; Left atrial structure; Lesion; Life; Location; Magnetic Resonance Imaging; Methods; Monitor; Motion; Navigation System; Operative Surgical Procedures; Outcome; Pathology; Patients; Perforation; Persons; Physicians; Positioning Attribute; Prevalence; Procedures; Pulmonary veins; Radiofrequency Interstitial Ablation; Recurrence; Research; Resolution; Risk; Robot; Robotics; Site; Stroke; System; Systems Integration; Techniques; Technology; Time; Tissues; Treatment outcome; Validation; Visualization; Work; effective therapy; force feedback; imaging modality; improved; improved outcome; innovation; metallicity; multimodality; novel; pre-clinical; public health relevance; robotic system; sensory feedback; treatment planning; virtual

Project Summary/Abstract: The objective of this proposal is to create a multi-modal feedback-based navigation system and MR- compatible robotic platform that enables precise, continuous, and permanent lesion creation during MR-guided radiofrequency ablation (RFA) for atrial fibrillation (AF) treatment. This research is motivated by the high incidence of AF in US (1 in 100 people), and the suboptimal treatment outcome of traditional approaches (~30- 50% recurrence rate). Recurrence of AF occurs when there are gaps between ablation lesions, which can be caused by multiple reasons, including 1) limited ability to manipulate the catheter in a manner that reaches all desired ablation targets while also 2) maintaining proper catheter-tissue contact force (CTCF) for effective ablation energy delivery. In addition, there is 3) lack of effective navigation methods that accurately identify sites of incomplete ablation and guide the catheter to complete ablation. We recently developed MR-tracked catheterization toolset to perform RFA inside MRI scanner and the MR-based imaging method to assess the lesion outcome intraoperatively. However, manipulating the catheter towards the desired location and maintaining proper contact remains a challenging task. To address these problems, we propose to develop an MR-enabled intraoperative navigation feedback framework and robotic hardware system. From technical perspective, the proposed platform is innovative since current systems do not integrate accurate catheter manipulation and CTCF feedback with MRI-based monitoring and lesion assessment to provide a unified system for AF ablation planning, treatment, and assessment. From the clinical perspective, the proposed platform enables accurate catheter position and contact force control, which supports the creation of continuous and chronic ablation lesions for reducing arrhythmia recurrence. The proposed work will be achieved via three Aims. Aim 1: Navigation feedback. We will further develop navigation software that combines multi-modal sensory feedback (i.e., MR imaging, MR-catheter tracking, CTCF estimation), and visualizes them in an integrated software environment to provide feedback to the physician. Aim 2: MRI robot hardware and control. We will advance our current catheter robot hardware to create a complete system for simultaneous catheter and guiding sheath manipulation. We will develop hybrid position and CTCF control algorithm that enables accurate and stable catheter placement for effective ablation energy delivery. Specific Aim 3: Experimental validations. We will integrate the robot hardware and navigation feedback system, and validate the integrated system first in a beating heart emulating phantom in a 1.5 MRI scanner, and then in 16 MR-guided LA ablation studies on swine.

项目摘要/摘要： 该提案的目标是创建一个基于多模式反馈的导航系统和 MR- 兼容的机器人平台，可在 MR 引导期间实现精确、连续和永久的病变创建 射频消融（RFA）用于心房颤动（AF）治疗。这项研究的动机是高 美国房颤的发病率（每 100 人中就有 1 人），以及传统方法的次优治疗结果（约 30- 50% 复发率）。当消融病灶之间存在间隙时，房颤会复发，这可能是 由多种原因引起，包括 1）以到达所有部位的方式操纵导管的能力有限 所需的消融目标，同时还 2) 保持适当的导管组织接触力 (CTCF)，以实现有效的消融 消融能量输送。此外，还存在3）缺乏准确识别站点的有效导航方法 并引导导管完成消融。我们最近开发了 MR 追踪 用于在 MRI 扫描仪内执行 RFA 的导管插入工具集和基于 MR 的成像方法来评估 术中病变结果。然而，将导管操纵到所需位置并 保持适当的联系仍然是一项具有挑战性的任务。为了解决这些问题，我们建议开发一个 支持 MR 的术中导航反馈框架和机器人硬件系统。从技术上 从角度来看，所提出的平台是创新的，因为当前系统没有集成精确的导管 操作和 CTCF 反馈以及基于 MRI 的监测和病变评估提供统一的系统 用于 AF 消融计划、治疗和评估。从临床角度来看，所提出的平台 实现精确的导管位置和接触力控制，支持创建连续和 慢性消融病变以减少心律失常复发。拟议的工作将通过三个目标来实现。 目标 1：导航反馈。我们将进一步开发结合多模态感官的导航软件 反馈（即 MR 成像、MR 导管跟踪、CTCF 估计），并以集成的方式将它们可视化 向医生提供反馈的软件环境。目标 2：MRI 机器人硬件和控制。我们将 改进我们当前的导管机器人硬件，以创建同步导管和引导的完整系统 鞘操纵。我们将开发混合位置和 CTCF 控制算法，以实现精确且 稳定的导管放置可实现有效的消融能量输送。具体目标 3：实验验证。我们 将集成机器人硬件和导航反馈系统，并首先在 在 1.5 MRI 扫描仪中模拟跳动的心脏模型，然后在 16 项 MR 引导的猪 LA 消融研究中进行。