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
基本信息
- 批准号:10638497
- 负责人:
- 金额:$ 64.03万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:3-DimensionalAblationAcuteAddressAlgorithmsAnimalsArrhythmiaAtrial FibrillationCardiacCardiac ablationCardiomyopathiesCatheterizationCathetersChronicClinicalComputer softwareElectrophysiology (science)EnsureEnvironmentFamily suidaeFeedbackHeartHeart DiseasesHeart failureHybridsIatrogenesisImageIncidenceInjuryLeftLeft atrial structureLesionLifeLocationMagnetic Resonance ImagingMethodsMonitorMotionNavigation SystemOperative Surgical ProceduresOutcomePathologyPatientsPerforationPersonsPhysiciansPositioning AttributePrevalenceProceduresPulmonary veinsRadiofrequency Interstitial AblationRecurrenceResearchResolutionRiskRobotRoboticsSiteStrokeSystemSystems IntegrationTechniquesTechnologyTimeTissuesTreatment outcomeValidationVisualizationWorkeffective therapyforce feedbackimaging modalityimprovedimproved outcomeinnovationmetallicitymultimodalitynovelpre-clinicalpublic health relevancerobotic systemsensory feedbacktreatment planningvirtual
项目摘要
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:
该建议的目的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,可以在MR引导期间实现精确,连续和永久性病变
用于心房颤动(AF)处理的射频消融(RFA)。这项研究是由高高的动机
美国AF的发病率(100人中有1人)以及传统方法的次优治疗结果(〜30-
50%复发率)。当消融病变之间存在差距时,会发生AF的复发,这可以是
由多种原因引起,包括1)以达到所有人的方式操纵导管的能力有限
所需的消融目标,而2)维持适当的导管组织接触力(CTCF)以有效
消融能量传递。另外,有3)缺乏有效的导航方法,可以准确识别站点
不完整的消融并引导导管完成消融。我们最近开发了MR追踪
导管插入工具集以在MRI扫描仪内部执行RFA和基于MR的成像方法来评估
病变术中。但是,操纵导管向所需位置和
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
启用MR的术中导航反馈框架和机器人硬件系统。来自技术
透视图,提议的平台具有创新性,因为当前系统没有整合准确的导管
通过基于MRI的监测和病变评估来操纵和CTCF反馈,以提供统一系统
用于AF消融计划,治疗和评估。从临床角度来看,提议的平台
启用准确的导管位置和接触力控制,这支持连续的创建
慢性消融病变可减少心律不齐的复发。拟议的工作将通过三个目标来实现。
AIM 1:导航反馈。我们将进一步开发结合多模式感觉的导航软件
反馈(即MR成像,MR-Catheter跟踪,CTCF估计),并在集成的
软件环境为医生提供反馈。目标2:MRI机器人硬件和控制。我们将
推进我们当前的导管机器人硬件,以创建一个同时导管和引导的完整系统
护套操纵。我们将开发混合位置和CTCF控制算法,以实现准确和
稳定的导管放置以有效消融能量输送。特定目标3:实验验证。我们
将集成机器人硬件和导航反馈系统,并首先验证集成系统
在1.5 MRI扫描仪中敲击心脏模仿幻影,然后在16个MR引导的LA消融研究中。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yue Chen其他文献
Yue Chen的其他文献
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10318651 - 财政年份:2020
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$ 64.03万 - 项目类别:
Functional Dissection of Metabolic-Sensing Proline Hydroxylation Pathways
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$ 64.03万 - 项目类别:
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