3D-Nanoprinted Soft Robotic Microcatheters with Integrated Microfluidic Circuitry for Cerebrovascular Surgery

用于脑血管手术的具有集成微流体电路的 3D 纳米打印软机器人微导管

• 批准号: 10654054
• 负责人: Ryan Daniel Sochol
• 金额: $ 66.74万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10654054
• 关键词: 3-Dimensional; 3D Print; Address; Anatomy; Aneurysm; Angiography; Animal Model; Blood Vessels; Canis familiaris; Catheterization; Catheters; Cerebral Aneurysm; Cerebrovascular system; Cerebrum; Cessation of life; Childhood; Clinical; Complex; Complication; Congenital Heart Defects; Craniotomy; Devices; Dissection; Distal; Engineering; General Population; Geometry; Goals; In Vitro; Infrastructure; Intervention; Intracranial Hemorrhages; Ischemia; Lasers; Length of Stay; Location; Machine Learning; Measures; Medical; Methods; Microfluidics; Morbidity - disease rate; Nanomanufacturing; Neurologic; Neurosurgical Procedures; Operative Surgical Procedures; Outcome; Patients; Perforation; Performance; Printing; Procedures; Reporting; Research; Resolution; Risk; Robot; Robotics; Running; Rupture; Safety; Scheme; Side; Specialist; Stents; Subarachnoid Hemorrhage; Surgical Clips; System; Techniques; Technology; Testing; Time; Transistors; Tube; Vasospasm; Writing; cerebrovascular; cerebrovascular surgery; clinically relevant; design; high risk; improved; improved outcome; in vitro Model; in vivo; innovation; machine learning framework; manufacture; microrobot; minimally invasive; mortality; neurosurgery; novel; operation; predictive modeling; procedure safety; safety and feasibility; two-photon; 3-Dimensional; 3D Print; Address; Anatomy; Aneurysm; Angiography; Animal Model; Blood Vessels; Canis familiaris; Catheterization; Catheters; Cerebral Aneurysm; Cerebrovascular system; Cerebrum; Cessation of life; Childhood; Clinical; Complex; Complication; Congenital Heart Defects; Craniotomy; Devices; Dissection; Distal; Engineering; General Population; Geometry; Goals; In Vitro; Infrastructure; Intervention; Intracranial Hemorrhages; Ischemia; Lasers; Length of Stay; Location; Machine Learning; Measures; Medical; Methods; Microfluidics; Morbidity - disease rate; Nanomanufacturing; Neurologic; Neurosurgical Procedures; Operative Surgical Procedures; Outcome; Patients; Perforation; Performance; Printing; Procedures; Reporting; Research; Resolution; Risk; Robot; Robotics; Running; Rupture; Safety; Scheme; Side; Specialist; Stents; Subarachnoid Hemorrhage; Surgical Clips; System; Techniques; Technology; Testing; Time; Transistors; Tube; Vasospasm; Writing; cerebrovascular; cerebrovascular surgery; clinically relevant; design; high risk; improved; improved outcome; in vitro Model; in vivo; innovation; machine learning framework; manufacture; microrobot; minimally invasive; mortality; neurosurgery; novel; operation; predictive modeling; procedure safety; safety and feasibility; two-photon

Project Summary: Cerebral aneurysms are estimated to be prevalent in 3–7% of the general population—with cases increasing by more than 5% each year—resulting in ~500,000 deaths annually. Minimally invasive neurosurgery typically represents the best surgical option for treating unruptured aneurysms due to benefits including reduced length of stay and complications compared to invasive surgical clipping. Endovascular neurointerventions rely on microcatheters to traverse cerebral anatomy safely to deliver embolic devices or stents for aneurysm treatment. In many cases, however, tortuous vasculature and geometrically complex aneurysms pose substantial navigation challenges for neurointerventionalists due to an inability to maneuver conventional microcatheters safely. These difficulties in navigating such cerebrovascular anatomies contribute to longer procedural times, unsuccessful catheterization attempts, and increased risks of complications. To address the clinical need for neurosurgical microcatheters that overcome these maneuverability-associated barriers, we propose to engineer and evaluate 3D-nanoprinted soft robotic microcatheters with integrated microfluidic circuitry as a means to enable on-demand, multi-directional steering and navigation control during endovascular neurointerventions. Our overarching hypothesis is that, by leveraging and extending recent advances at the intersection of machine learning-based design, additive nanomanufacturing, integrated microfluidic circuitry, and soft microrobotics, novel classes of remotely steerable neurosurgical microcatheters can be realized at unprecedented scales to surmount current maneuverability-based deficits, and ultimately, improve catheterization efficacy, safety, and outcomes in the treatment of cerebral aneurysms. We will investigate the clinical feasibility of this hypothesis through four specific aims. In Aim 1, we will create machine learning-based design techniques for predicting and informing the operational performance of the soft robotic microcatheter. In Aim 2, we will examine the manu- facturing efficacy for 3D nanoprinting multi-actuator tips and integrated microfluidic circuits both independently and as fully unified soft robotic microcatheters capable of on-demand, multi-directional deformations with minimal infrastructure and external control scheme-associated requirements. In Aim 3, we will develop a handheld controller for the neurointerventionalist and compare the maneuverability efficacy of the soft robotic micro- catheter to that of standard clinical microcatheters using in vitro models of cerebrovascular anatomy based on patient-specific clinical 3D angiography images. In Aim 4, we will assess the feasibility and safety of the soft robotic microcatheter (i.e., with respect to standard clinical microcatheters) by performing minimally invasive endovascular neurointerventions in animal models (canine, n=8). If successful, the proposed 3D-nanoprinted soft robotic microcatheters hold unique promise to be transformative not only for treating cerebral aneurysms, but also for wide-ranging endovascular interventions currently considered challenging or high risk due to small, complex, tortuous, and/or delicate vasculature, such as for the treatment of pediatric congenital heart defects.

项目摘要： 据估计，脑动脉瘤在3-7％的一般人群中很普遍 - 病例增加 每年超过5％，每年约有500,000人死亡。最少侵入性神经外科手术 由于益处包括长度，这是治疗未破裂动脉瘤的最佳外科手术选择 与侵入性手术剪切相比，住院和并发症。血管内神经介入依赖 微心会员可以安全地遍历大脑解剖结构，以提供栓塞设备或支架进行动脉瘤治疗。 然而，在许多情况下，曲折的脉管系统和几何复杂的动脉瘤构成了很大的 由于无法操纵传统的微心会员，神经介入主义者的导航挑战 安全。导航这种脑血管解剖学的这些困难导致了更长的程序时间， 失败的导管插入术，并增加并发症的风险。满足临床需求 克服这些可操作性相关的障碍的神经外科微心会员，我们建议设计 并用集成的微流体电路评估3D-Nanoprint的软机器人微心会员 在血管内神经间隔期间，启用按需，多方向转向和导航控制。 我们的总体假设是，通过利用和扩展机器交集的最新进展 基于学习的设计，加性纳米制造，集成的微流体电路和柔软的微型机器人， 可以在前所未有的尺度上实现新颖的遥控神经外科微心会员 克服目前基于机动性的缺陷，并最终提高导管插入效率，安全性和 治疗脑动脉瘤的结果。我们将研究该假设的临床可行性 通过四个特定目标。在AIM 1中，我们将创建基于机器学习的设计技术，以预测和 告知软机器人微型导仪的运行性能。在AIM 2中，我们将检查Manu- 3D纳米刺激尖端和集成的微流体电路的验证效率均独立 并且作为能够按需的完全统一的软机器人微心精神，多方向变形，最小 基础架构和外部控制方案相关的要求。在AIM 3中，我们将开发一个手持式 神经介入主义者的控制器，并比较软机器人微型的机动性效率 使用基于脑血管解剖学的体外模型的标准临床显微心精神的导管 患者特异性临床3D血管造影图像。在AIM 4中，我们将评估软软的可行性和安全性 机器人微量导线（即，关于标准临床微心会员），通过执​​行微创 动物模型中的血管内神经干扰（犬，n = 8）。如果成功，则建议的3D-Nanoprint 软机器人的微心会员具有独特的承诺，不仅可以对治疗脑动脉瘤进行变革， 但对于宽范围内血管内干预措施，目前被视为挑战或高风险，原因很小 复杂，曲折和/或精致的脉管系统，例如治疗小儿先天性心脏缺陷。