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.

项目概要/摘要 全球每年进行超过 2.32 亿例手术和介入治疗，其中 5140 万例在 我们。尽管手术技术和技巧有所改进，但据报道并发症发生率高达 20%。 图像引导是改善手术结果和减少并发症的关键因素。虽然成像是 常规用于手术前的诊断和分期，数以百万计的手术和介入治疗中的大多数 病例的执行仍然没有直接链接到术前图像，而是依赖于手术医生的 基于经验的决策。正在研究图像引导机器人干预（IGRI）以解决 这些挑战。基本假设是图像引导和机器人辅助相结合 增强医生以最小的侵入看到和物理接触病变的能力，从而获得更好的治疗结果 临床结果。然而，IGRI系统中图像信息的使用仅遵循当前传统的非 机器人程序；这些机器人仅根据从系统获得的几何信息进行控制 由于各种原因导致平面图与体内实际物理空间存在差异 不确定性，包括患者运动、异质组织特性以及之间的通信延迟 系统组件（例如传感器、机器人硬件和软件）。因此，IGRI 并未给出明确的 在临床结果方面优于传统的非机器人手术。 IGRI 数量不断增加 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 以追求机械精度为中心的方法转向“数据驱动”的方法，其中治疗是 根据从成像扫描仪、传感器和医疗记录获得的数据进行建模，以进行个性化规划 和控制以获得更好的临床结果。数据驱动方法需要大量的工程资源 因为涉及的软件组件范围广泛。特别是软件组件的集成 由于缺乏鲁棒性，在机器人和医学图像计算等不同领域开发的技术具有挑战性 与所使用的每个组件兼容的软件平台。为了应对这一挑战，我们将整合 流行的医学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 Slicer 集成到一个平台中。这个名为 SlicerROS 的新平台将作为插件分发 用于 3D 切片器。 SlicerROS 将允许整合最先进的机器人技术和医学图像计算工具， 它们在机器人和医学图像计算社区中开发和验证，集成到单个 IGRI 中 系统。我们将致力于以下目标：（目标1）扩展3D Slicer/ROS集成以实现无缝 用于数据驱动的 IGRI 的医学图像计算和机器人工具的集成； （目标 2）传播 SlicerROS 在医学图像计算和机器人社区中建立一个活跃的用户/开发者社区 可持续的开源软件开发和维护。