Extending Reach, Accuracy, and Therapeutic Capabilities: A Soft Robot for Peripheral Early-Stage Lung Cancer

扩大范围、准确性和治疗能力：用于周围早期肺癌的软机器人

• 批准号: 10637462
• 负责人: Sheila Russo
• 金额: $ 29.7万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10637462
• 关键词: 3-Dimensional; Acceleration; Accidents; Address; Affect; Air; Algorithms; Anatomic Models; Anatomy; Area; Biopsy; Biopsy Specimen; Breathing; Bronchi; Bronchial Tree; Bronchoscopes; Bronchoscopy; Cause of Death; Cessation of life; Collaborations; Colon Carcinoma; Computer Vision Systems; Computer software; Data; Death Rate; Development; Device or Instrument Development; Diagnosis; Diagnostic; Diameter; Distal; Drug Delivery Systems; Drug Targeting; Early Diagnosis; Early treatment; Evaluation; Family suidae; Goals; Health Care Costs; In Vitro; Intervention; Intuition; Learning; Lesion; Location; Lung; Lung nodule; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of prostate; Manuals; Marketing; Mechanics; Medical Device; Movement; Needles; Operative Surgical Procedures; Patients; Performance; Peripheral; Positioning Attribute; Procedures; Pulmonology; Radial; Reaction; Recording of previous events; Research; Risk; Robot; Robotics; Safety; Site; Stroke; Survival Rate; System; Technology; Therapeutic; Time; Tissue Sample; Tissues; United States; Validation; Vision; Visualization; Work; blind; cancer diagnosis; cancer therapy; cancer type; cost effective; design; dexterity; experience; experimental study; fabrication; flexibility; image guided; improved; in vitro testing; instrument; malignant breast neoplasm; miniaturize; novel; preservation; rapid diagnosis; robot assistance; robot control; success; tissue trauma; tool; tumor growth; visual feedback

PROJECT SUMMARY This proposal focuses on the design, development, and validation of a novel soft surgical robot to address critical unmet needs within the world of lung cancer. Lung cancer is the leading cause of death from cancer in the United States and worldwide with an estimated 1.8 million deaths a year, more than breast cancer, prostate cancer, and colon cancer combined. Early diagnosis and therapy are essential to increase the survival rate of lung cancer. Because approximately 70% of lung nodules reside in the deeper peripheral region of the lung, adequate sampling of the tissue is challenging. Traditional manual bronchoscopes are limited in their ability to access small bronchi because of large diameters. Robotic bronchoscopes available on the market are easier and more intuitive to maneuver. However, they still present distal dexterity limitations and deep exploration is still performed without visualization by using semi-flexible needles that are pushed manually by the clinician. This affects biopsy accuracy and precision and ultimately diagnostic yield, causing delays in diagnosis and treatment and increasing the risk for tumor growth and spread. In this proposal, we will leverage our prior pioneering work on the design, fabrication, and preliminary validation of a miniaturized soft robotic bronchoscope for early-stage lung cancer diagnosis and treatment. This air-powered, image-guided robot is the smallest and most flexible and dexterous robotic bronchoscope, allowing navigation in branches deeper in the lung and visual feedback throughout the procedure. The system features two separate working channels to facilitate, for the first time, simultaneous (i.e., within the same bronchoscopy procedure) diagnostic and therapeutic capabilities and hasten early-stage lung cancer treatment. We will optimize the soft robotic bronchoscope navigation and stabilization control based on computer vision algorithms. We will merge pre-operative planning and intra-operative data and evaluate accuracy and precision in registration. We will develop a mechanical stabilization system at the robot tip, that will anchor to the surrounding anatomy and work in concert with software stabilization. This will enhance robot lesion tracking abilities during breathing and other involuntary or accidental movements and counteract tissue reaction forces during biopsy to improve surgical tasks’ accuracy and precision. We will enable robotic actuation control for needle tool deployment and steering via multi-DOF soft robotic micro actuators at the robot tip. Sharp bending angles and large strokes will enable access to hard-to-reach lesions without losing visualization. We will validate the robot in-vitro and ex-vivo and compare metrics with standard bronchoscopy. We anticipate our technology to have better navigational abilities, more accurate instrument placement, reduced procedure times, less tissue trauma, better diagnostic yield, shortened learning curve, and an overall enhanced procedural experience. Our team is uniquely positioned to achieve success of this study, possessing expertise in surgical robotics, soft robotics, medical devices, and interventional pulmonology, and having a long history of close and fruitful collaboration.

项目摘要 该提案重点介绍新型软外科机器人的设计，开发和验证，以解决关键 肺癌世界中未满足的需求。肺癌是癌症死亡的主要原因 美国和全球估计每年死亡180万，比乳腺癌，前列腺多 癌症和结肠癌的总和。早期诊断和治疗对于提高生存率至关重要 肺癌。由于大约70％ 足够的组织采样是挑战。传统手动支气管镜的能力有限 由于直径较大，因此进入小基督。市场上可用的机器人支气管镜很容易 更直观地对机动。但是，它们仍然存在远端的敏捷限制，并且深入探索仍然是 通过使用由临床手动推动的半弹性针，无法可视化。这 影响活检的精度和精度，并最终诊断出产量，从而导致诊断和治疗的延迟 并增加肿瘤生长和扩散的风险。在此提案中，我们将利用我们先前的开创性工作 在设计，制造和初步验证的小型机器人支气管镜的初步验证 肺癌诊断和治疗。这款由图像引导的机器人是最小，最灵活的机器人 和灵巧的机器人支气管镜，使肺部和视觉反馈更深入的分支机构导航 在整个过程中。该系统具有两个独立的工作渠道，以首次促进 同时（即，在相同的支气管镜检查程序中）诊断和治疗能力并加速 早期肺癌治疗。我们将优化软机器人支气管镜导航和稳定 基于计算机视觉算法的控制。我们将合并术前计划和术中数据，以及 评估注册的准确性和精度。我们将在机器人开发机械稳定系统 提示，这将锚定在周围的解剖结构上，并与软件稳定合作。这将增强 机器人病变跟踪能力在呼吸和其他感染或意外运动中的能力并抵消 活检过程中的组织反应力提高手术任务的准确性和精度。我们将启用机器人 针对针线工具部署和通过多功能软机器人微执行器转向的驱动控制机器人 提示。尖锐的弯曲角度和大笔触将使您能够进入难以到达的病变而不会失去可视化。 我们将验证机器人含量和前体体，并将指标与标准支气管镜检查进行比较。我们期待 我们具有更好的航行能力，更准确的仪器位置，减少程序的技术 时间，组织创伤较少，诊断率更好，学习曲线缩短和总体增强程序性 经验。我们的团队在获得这项研究的成功方面拥有独特的位置，拥有手术方面的专业知识 机器人技术，软机器人技术，医疗设备和介入性肺功学，并拥有悠久的历史 富有成果的合作。