Robot-Assisted 3D ICE Catheter for Cardiac Ablation

用于心脏消融的机器人辅助 3D ICE 导管

• 批准号: 10583562
• 负责人: Jayender Jagadeesan
• 金额: $ 37.03万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10583562
• 关键词: 3-Dimensional; Ablation; Address; Adopted; Adoption; Algorithms; Anatomy; Area; Arrhythmia; Atrial Fibrillation; Canada; Cardiac; Cardiac ablation; Catheters; Computer Vision Systems; Computer software; Coupling; Diagnosis; Early Diagnosis; Echocardiography; Ensure; Esophageal Fistula; Family suidae; Fluoroscopy; Goals; Grant; Heart; Heart Atrium; Hospitals; Image; Intuition; Ionizing radiation; Lesion; Machine Learning; Manuals; Maps; Medical; Microbubbles; Modeling; Monitor; Myocardium; Navigation System; Necrotic Lesion; Ontario; Operative Surgical Procedures; Patient Care; Patients; Perforation; Performance; Positioning Attribute; Procedures; Pulmonary veins; Radial; Recurrence; Research; Research Personnel; Risk Reduction; Robot; Robotics; Roentgen Rays; Surgical Instruments; System; Technology; Thrombus; Time; United States; Universities; Vision; Visualization; Woman; Work; cancer risk; clinical care; convolutional neural network; deep learning algorithm; design; design verification; dexterity; image guided; image registration; innovation; instrument; kinematics; light weight; machine learning algorithm; machine vision; novel; phantom model; porcine model; radio frequency; real time monitoring; robot assistance; therapy outcome; time use; ultrasound

ABSTRACT Although the cardiac ablation procedure for atrial fibrillation has a wide adoption rate, it also has a high recurrence of arrhythmia primarily due to the creation of suboptimal lesions. The procedure is also associated with complications including cardiac perforation, tamponade, atrio-esophageal fistulas and thrombus. Repeated and prolonged X-ray exposure for the clinician can also lead to enhanced risk of cancer. A fluoroless approach using intracardiac echocardiography (ICE) is becoming a more widely adopted imaging option due to the absence of ionizing radiation and the possibility of real-time monitoring of the created lesions. However, the ICE- guided approach suffers from significant shortcomings, which include poor dexterity of the ICE catheter, difficulty in simultaneously manipulating the ICE and ablation catheters, unintuitive image orientation and noisy image quality. There is therefore an unmet need to overcome these shortcomings of the ICE-guided approach to enable better lesion creation and reduced complications associated with the cardiac ablation procedure. The long-term goal of this research is to develop robotic technologies, control and machine learning algorithms to enable ICE- guided cardiac ablation procedures. The objective is to develop a novel robotic manipulator, a steerable ICE catheter, and machine learning and control algorithms to manipulate the ICE catheter and monitor the created lesions in real-time. The rationale that underlies the proposed research is that the robot-assisted steerable ICE catheter with the catheter tracking algorithms will enable simultaneous manipulation of the ICE and ablation catheters. Further, the machine learning algorithms to monitor therapy will reduce the risk of complications, while ensuring the creation of necrotic lesions, thereby reducing the recurrence of AF. In this proposal, we plan to pursue the following specific aims: 1) Design, develop, and model a steerable 3D ICE catheter with enhanced dexterity. 2) Design and develop a robotic manipulator and associated control algorithms to allow for precise manipulation of the ICE catheter. 3) Develop machine-learning and vision-based algorithms integrated with a navigation system for tracking the ablation catheter, and monitoring therapy. 4) Validate the robotic ICE system in heart phantom and porcine models. The proposed research is significant since it will allow for better therapeutic outcomes by reducing recurrence rates and complications associated with cardiac ablation, and avoiding exposure of the patient and clinical care team to X-ray radiation. The proposed research is innovative in that it builds on state-of-the-art robotics technology, machine learning and vision algorithms to enable fluoroless ICE- guided cardiac ablation procedures.

摘要 虽然用于心房颤动的心脏消融术具有广泛的采用率，但是其也具有高的 心律失常的复发主要是由于次优病变的产生。该程序还与 并发症包括心脏穿孔、填塞、心房食管瘘和血栓。重复 临床医生长时间的X射线照射也会增加患癌症的风险。无氟方法 使用心内超声心动图（ICE）正成为一种更广泛采用的成像选择， 不存在电离辐射，并且可以实时监测所产生的损伤。然而，ICE- 引导方法具有显著的缺点，包括ICE导管的灵活性差， 在同时操作ICE和消融导管时，不直观的图像方向和噪声图像 质量.因此，需要克服移民和海关执法局指导的方法的这些缺点， 更好地形成损伤并减少与心脏消融手术相关的并发症。长期 这项研究的目标是开发机器人技术，控制和机器学习算法，使ICE- 引导心脏消融术。目的是开发一种新型的机器人操作器，可转向ICE 导管，以及机器学习和控制算法，以操纵ICE导管并监测所创建的 实时病变。所提出的研究的基本原理是，机器人辅助的可操纵ICE 具有导管跟踪算法的导管将能够同时操作ICE和消融 导尿管此外，用于监测治疗的机器学习算法将降低并发症的风险， 确保坏死病变的产生，从而减少AF的复发。在此建议中，我们计划 追求以下具体目标：1）设计，开发和建模具有增强功能的可操纵3D ICE导管 灵巧2)设计和开发机器人机械手和相关的控制算法，以实现精确的 ICE导管的操作。3)开发机器学习和基于视觉的算法， 用于跟踪消融导管和监测治疗的导航系统。4)机器人ICE系统 在心脏体模和猪模型中。这项拟议中的研究意义重大，因为它将使更好的治疗 通过降低与心脏消融术相关的复发率和并发症， 患者和临床护理团队暴露于X射线辐射。这项研究的创新之处在于， 基于最先进的机器人技术、机器学习和视觉算法，实现无氟ICE- 引导心脏消融术。