CPS: Synergy: Collaborative Research: MRI Powered & Guided Tetherless Effectors for Localized Therapeutic Interventions

CPS：协同作用：协作研究：MRI 驱动

• 批准号: 1646566
• 负责人: Aaron Becker
• 金额: $ 60.79万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646566&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; MRI

Magnetic Resonance Imaging (MRI) scanners use strong magnetic fields to safely image soft tissues deep inside the body. They offer a unique tool for guiding therapies: images while patient is inside the scanner can localize diseased tissue and guide an intervention with high accuracy. This research controls MRI magnetic fields to wirelessly push millimeter-scale robots through vessels in the body, assemble them into tools, and provide targeted drug delivery or pierce tissue. This will directly impact healthcare, improving patient outcome by enabling unparalleled minimal invasiveness resulting in faster recovery, fewer side effects, and cost-effectiveness. This transformative toolset for multi-agent control will set the foundation for a wealth of medical therapies and surgical interventions. Using magnetic forces of clinical MRI scanners to steer miniature tetherless effectors through human bodies and combining with real-time imaging and operator immersion could transform the practice of minimally invasive interventions. This CPS will seamlessly integrate physical (scanner sensor/actuator, effectors, patient, operator) and cyber (world modeling, combined sensor and effector control, operator immersion). Work entails: (1) Portfolio of parametric effector designs that can be optimized to exploit the constraints of a given clinical procedure. (2) Toolbox of automatic controllers for MRI-based powering and steering of tetherless effectors in the body lumen, self-assembling them into tools, and precision therapy delivery or to pierce tissue. (3) Real-time MRI-based sensing of the physical world for imaging and tracking effectors and tissue. (4) Linked effector and MRI scanner control on-the-fly. (5) Visual/force-feedback human-robot interfacing. The work focuses on two effector classes: an MRI Gauss gun that stores magnetic potential energy released by a chain reaction when robots self-assemble, and an MRI pile-driver that converts kinetic energy from an enclosed sphere into impulses to tunnel into tissue. These approaches will be validated through analytical modeling, scaled hardware experiments, and experiments in clinical MRI scanners.

磁共振成像（MRI）扫描仪使用强磁场安全地成像身体深处的软组织。他们为指导治疗提供了一种独特的工具：患者在扫描仪内的图像可以定位病变组织并以高精度指导干预。这项研究控制核磁共振磁场，以无线方式推动毫米级的机器人穿过体内的血管，将它们组装成工具，并提供靶向药物输送或刺穿组织。这将直接影响医疗保健，通过实现无与伦比的最小侵入性，从而实现更快的恢复、更少的副作用和成本效益，从而改善患者的治疗效果。这种多智能体控制的变革性工具集将为丰富的医学治疗和手术干预奠定基础。利用临床MRI扫描仪的磁力引导微型无系绳效应器穿过人体，并结合实时成像和操作员沉浸式操作，可以改变微创干预的实践。该CPS将无缝集成物理（扫描仪传感器/执行器，效应器，患者，操作员）和网络（世界建模，结合传感器和效应器控制，操作员沉浸）。工作需要：(1)可以优化利用给定临床程序约束的参数效应设计组合。(2)自动控制器工具箱，用于基于核磁共振的身体腔内无系绳效应器的供电和转向，将其自组装成工具，并精确治疗递送或刺穿组织。(3)基于实时核磁共振的物理世界感知，用于成像和跟踪效应器和组织。(4)联动效应器和MRI扫描仪实时控制。(5)视觉/力反馈人机界面。这项工作主要集中在两类效应器上：一种是MRI高斯枪，它存储机器人自组装时链式反应释放的磁势能；另一种是MRI打桩机，它将封闭球体的动能转化为脉冲，进入组织。这些方法将通过分析建模、缩放硬件实验和临床MRI扫描仪实验进行验证。

项目成果

BNU-Net: A Novel Deep Learning Approach for LV MRI Analysis in Short-Axis MRI

• DOI: 10.1109/bibe.2019.00137
• 发表时间: 2019-10
• 期刊: 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE)
• 作者: Wenhui Chu;Giovanni Molina;N. Navkar;Christoph F. Eick;Aaron T. Becker;P. Tsiamyrtzis;N. Tsekos

3D Reconstruction of Tubular Structure Using Radially Deployed Projections

使用径向部署投影对管状结构进行 3D 重建

• DOI: 10.1109/mipr.2019.00064
• 发表时间: 2019
• 期刊: 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR
• 作者: Unan, Mahmut;An, Junmo;Seimenis, Ionnis;Shah, Dipan J.;Tsekos, Nikolaos V.
• 通讯作者: Tsekos, Nikolaos V.

Exploiting Nonslip Wall Contacts to Position Two Particles Using the Same Control Input

• DOI: 10.1109/tro.2019.2891487
• 发表时间: 2019-02
• 期刊: IEEE Transactions on Robotics
• 影响因子: 7.8
• 作者: Shiva Shahrokhi;Jing-Xin Shi;B. Isichei;Aaron T. Becker

Interactive and Immersive Image-Guided Control of Interventional Manipulators with a Prototype Holographic Interface

具有原型全息界面的介入机械手的交互式和沉浸式图像引导控制

• DOI: 10.1109/bibe.2019.00186
• 发表时间: 2019
• 期刊: 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE
• 作者: Morales Mojica, Cristina Marie;Tsekos, Nikolaos V.;Velazco-Garcia, Jose Daniel;Zhao, Haoran;Seimenis, Ioannis;Leiss, Ernst L.;Shah, Dipan;Webb, Andrew;Becker, Aaron T.;Tsiamyrtzis, Panagiotis
• 通讯作者: Tsiamyrtzis, Panagiotis

Towards MRI-guided and actuated tetherless milli-robots: Preoperative planning and modeling of control

迈向 MRI 引导和驱动的无绳微型机器人：术前规划和控制建模

• DOI: 10.1109/iros.2017.8206550
• 发表时间: 2017
• 期刊: 2017 IEEE/RSJ International Conference on
• 作者: Kensicher, Thibault;Leclerc, Julien;Biediger, Daniel;Shah, Dipan J.;Seimenis, Ioannis;Becker, Aaron T.;Tsekos, Nikolaos V.
• 通讯作者: Tsekos, Nikolaos V.