Open Software Platform for Data-Driven Image-Guided Robotic Interventions

用于数据驱动图像引导机器人干预的开放软件平台

• 批准号: 10608711
• 负责人: Mark Fuge
• 金额: $ 28.72万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10608711
• 关键词: 3-Dimensional; Address; Administrative Supplement; Algorithms; Anatomic Models; Anatomy; Area; Catheters; Clinical; Communication; Communities; Complication; Computer software; Data; Decision Making; Development; Diagnosis; Disease; Documentation; Engineering; Event; Excision; Funding; Goals; Graph; Image; Intervention; Learning; Lesion; Link; Magnetic Resonance Imaging; Maintenance; Mechanics; Medial; Medical; Medical Imaging; Medical Records; Modeling; Motion; Names; Needles; Operating System; Operative Surgical Procedures; Outcome; Participant; Patients; Physicians; Physiological; Plug-in; Positron-Emission Tomography; Procedures; Property; Prostate; Quality Control; Reporting; Research; Research Personnel; Resolution; Resources; Robot; Robotics; Source Code; Speed; Staging; Students; System; Technology; Testing; Tissues; Training; Uncertainty; Work; base; bench-to-bedside translation; data tools; experience; image guided; image processing; imaging platform; improved; in vivo; interest; multiparametric imaging; open source; parent grant; parent project; prototype; repository; robot assistance; sensor; software development; software systems; surgery outcome; technology/technique; tool; tumor; ultrasound

Project Summary/Abstract More than 232 million surgeries and interventions are performed each year worldwide, and 51.4 million in the US. Despite improvements in surgical technology and techniques, complication rates of up to 20% are reported. Image guidance is a key factor in improving surgical outcomes and reducing complications. While imaging is routinely used for diagnosis and staging prior to surgery, the majority of the millions of surgical and interventional cases are still performed without a direct link to pre-operative images, instead relying on the operating physician’s decisions based on experience. Image-guided robotic interventions (IGRIs) are being investigated to address those challenges. The underlying hypothesis is that the combined image-guidance and robot-assistance enhance the physician’s ability to see and physically access the lesion with minimal invasion resulting in a better clinical outcome. However, usage of image information in IGRI systems merely follow current conventional non- robotic procedures; those robots are controlled simply based on the geometric information obtained from the image, which leads to a discrepancy between the plan and the actual physical space in vivo due to various uncertainties, including patient motion, heterogenous tissue properties, and communication latencies between system components (e.g., sensors, robot hardware, and software). As a result, IGRI has not shown a clear advantage over conventional non-robotic procedures in terms of clinical outcome. The growing number of IGRI applications and the recognition of the real-world challenge led to a shift of research interest from a hardware- centric approach, which pursues mechanical precision, to a “data-driven” approach, where the treatment is modeled based on data obtained from imaging scanners, sensors, and medical records for personalized planning and control for better clinical outcomes. The data-driven approach requires sizable engineering resources because of the wide range of software components involved. Particularly, integration of software components developed in different fields, i.e., robotics and medical image computing, is challenging due to the lack of robust software platforms that are compatible with every component used. To address this challenge, we will integrate popular medical image computing and robotics software packages, namely Robot Operating System version 2 (ROS2) and 3D Slicer into a single platform. This new platform, called SlicerROS, will be distributed as a plug- in for 3D Slicer. SlicerROS will allow incorporating state-of-the-art robotics and medical image computing tools, which are developed and validated in the robotics and medical image computing communities, into a single IGRI system. We will work on the following aims: (Aim 1) Extend 3D Slicer/ROS integration to achieve seamless integration of medial image computing and robotics tools for data-driven IGRI; (Aim 2) Disseminate SlicerROS in the medical image computing and robotics communities to build an active user/developer community for sustainable open-source software development and maintenance.

项目摘要/摘要 全球每年进行超过2.32亿次手术和干预措施，其中5,140万 我们。尽管手术技术和技术有所改善，但报告的并发症发生率最高为20％。 图像引导是改善手术结果和减少并发症的关键因素。而成像是 在手术前通常用于诊断和分期，大多数手术和介入中的大多数 案件仍然是在没有与术前图像的直接链接的情况下执行的，而是依靠操作医师的 基于经验的决定。正在研究图像引导的机器人干预措施（IGRIS）以解决 这些挑战。基本的假设是组合图像指标和机器人辅助 增强物理性观察和物理访问病变，并以最小的侵袭，从而获得更好的状态 临床结果。但是，IGRI系统中图像信息的使用仅遵循当前的常规非 - 机器人程序；这些机器人仅根据从 图像，由于各种 不确定性，包括患者运动，异源组织特性和之间的通讯潜伏期 系统组件（例如，传感器，机器人硬件和软件）。结果，IGRI尚未显示出明确的 就临床结局而言，优于常规的非无骨手术的优势。 IGRI的数量越来越多 应用程序和对现实世界挑战的认识导致研究兴趣从硬件转移 以机械精度为基础的方法，采用了一种“数据驱动”方法，该方法是治疗 根据从成像扫描仪，传感器和医疗记录获得的个性化计划的数据建模 并控制更好的临床结果。数据驱动的方法需要相当大的工程资源 由于涉及的软件组件范围很广。特别是软件组件的集成 由于缺乏强大的功能，在不同领域（即机器人技术和医学图像计算）开发 与所使用的每个组件兼容的软件平台。为了应对这一挑战，我们将集成 流行的医疗图像计算和机器人软件包，即机器人操作系统版本2 （ROS2）和3D切片机进入一个平台。这个称为Slicerros的新平台将作为插件分发 用于3D切片机。 Slicerros将允许合并最先进的机器人技术和医学图像计算工具， 在机器人技术和医学图像计算社区中已开发和验证的，将其分为一个IGRI 系统。我们将以以下目的进行工作：（目标1）扩展3D切片机/ROS集成以实现无缝 用于数据驱动的IGRI的媒体图像计算和机器人技术工具的集成； （AIM 2）传播Slicerros 在医学图像计算和机器人技术社区中，建立了一个活跃的用户/开发人员社区 可持续的开源软件开发和维护。