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: 10395515
• 负责人: Jayender Jagadeesan
• 金额: $ 41.25万
• 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/10395515
• 关键词: 3-Dimensional; 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; Lead; 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; Robot; Robotics; Roentgen Rays; Surgical Instruments; System; Technology; Thrombus; Time; United States; Universities; Vision; Woman; Work; base; cancer risk; clinical care; convolutional neural network; deep learning algorithm; design; dexterity; image guided; 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.

抽象的 尽管心房颤动的心脏消融术具有广泛的采用率，但它也有较高的应用前景。 心律失常的复发主要是由于次优病变的产生。程序也有关联 并发症包括心脏穿孔、心包填塞、心房食管瘘和血栓。重复 临床医生长时间接触 X 射线也会导致患癌症的风险增加。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，因为 没有电离辐射并且可以实时监测所产生的损伤。然而，ICE- 引导入路存在明显的缺点，包括 ICE 导管灵活性差、困难 在同时操作 ICE 和消融导管时，图像方向不直观且图像有噪声 质量。因此，克服 ICE 引导方法的这些缺点的需求尚未得到满足，以实现 更好的病灶形成并减少与心脏消融手术相关的并发症。长期来看 这项研究的目标是开发机器人技术、控制和机器学习算法，以使 ICE- 引导心脏消融手术。目标是开发一种新型机器人操纵器，即可操纵的 ICE 导管，以及机器学习和控制算法来操纵 ICE 导管并监控所创建的 实时病变。拟议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纵 ICE 和消融 导管。此外，监测治疗的机器学习算法将降低并发症的风险，同时 确保坏死病灶的产生，从而减少房颤的复发。在本提案中，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）设计和开发机器人操纵器和相关控制算法，以实现精确的控制 ICE 导管的操作。 3）开发与机器学习和基于视觉的算法集成 用于跟踪消融导管并监测治疗的导航系统。 4) 验证机器人ICE系统 在心脏模型和猪模型中。拟议的研究意义重大，因为它将提供更好的治疗 通过降低复发率和与心脏消融相关的并发症，并避免 患者和临床护理团队暴露于 X 射线辐射。拟议的研究具有创新性，因为它 以最先进的机器人技术、机器学习和视觉算法为基础，实现无氟 ICE- 引导心脏消融手术。