Robotic System for Spinal Decompression and Interbody Fusion

总结 该应用程序的目标是开发一个机器人工作站集成，新颖的成像和可视化 在微创脊柱（MIS）手术中执行复杂任务的能力， 使用传统的手术工具和方法进行。这一应用的具体重点将是两个 复杂手术：椎板切除减压术和经椎间孔腰椎椎间融合术（TLIF）。 我们建议开发一个图像引导的原型机器人系统，用于计划，实时术中 监测、导航和更新计划。 全世界每年进行超过500万例脊柱手术，美国有130万例手术。 只有国家。在下背部（腰椎），通常进行减压和融合以治疗 导致椎管狭窄（神经压迫）的各种病理，包括：退行性椎间盘疾病， 脊椎病（脊柱关节炎）、脊椎前移（平移不稳定）和脊柱畸形如脊柱侧凸。 随着美国人口的不断老龄化，脊柱融合手术变得越来越多， 在过去的十年里很常见。 脊柱融合术是一种在两个或多个椎骨之间建立骨性（骨）结合的外科技术 以消除任何节段间的运动。在现代，这是通过放置椎弓根来实现的。 螺钉（单个椎体中的锚）与跨越多个椎骨的杆连接。 另外，经常在椎间盘间隙中放置机械装置以便于直接骨植入。 椎体之间的生长执行此过程的流行方法称为 经椎间孔腰椎椎间融合术或“TLIF”。 螺钉和椎间器械的放置在技术上具有挑战性，因为它们非常接近重要的 神经和血管结构。目前的商业机器人系统仅专注于引导椎弓根螺钉。 这些系统通常依赖于与术中定位数据合并的术前成像， 校准和轨迹规划。计划的螺钉轨迹由外科医生手动执行。 在脊柱手术的复杂任务中，例如TLIF（其中椎间盘被移除，骨终板 准备，并通过过盈配合放置生物力学植入物以促进融合），外科医生 由于解剖结构的限制，它们的可视化和接近受到限制。为了实现他们的目标， 外科医生经常对正常解剖结构造成附带损伤。 提出了一种集成连续体灵巧手的主动手术机器人系统 可提供完成复杂脊柱手术任务的能力，如脊柱减压和TLIF， 对周围组织的破坏更少，因此与传统的， 开放手术和传统MIS脊柱手术。

Summary The goal of this application is to develop a robotic workstation with integrated, novel imaging and visualization capabilities to perform complex tasks in minimally-invasive spine (MIS) surgery that cannot be currently performed with conventional surgical tools and approaches. The specific focus of this application will be two complex surgeries: laminectomy decompression and Transforaminal Lumbar Interbody Fusion (TLIF) Surgery. We propose the development of an image-guided prototype robotic system for planning, real-time intraoperative monitoring, navigation, and updating of the plans. There are over 5 million spinal operations performed worldwide annually, with 1.3 million surgeries in the United States alone. In the low back (lumbar spine), decompression and fusion are commonly performed to treat a variety of pathologies that result in spinal stenosis (compression of nerves), including: degenerative disc disease, spondylosis (spinal arthritis), spondylolisthesis (translational instability) and spinal deformities such as scoliosis. As the population of the United States continues to age, spinal fusion surgery has become increasingly more common over the last decade. Spinal fusion is a surgical technique that creates an osseous (bony) union between two or more vertebral bones to eliminate any intersegmental motion. In the modern era, this is accomplished by placement of pedicle screws (anchors in individual vertebral bodies) connected with rods that span across multiple vertebral bones. Additionally, placement of a mechanical device in the disc space is frequently performed to facilitate direct bone growth between the vertebral bodies. A popular approach to performing this procedure is known as a transforaminal lumbar interbody fusion or “TLIF.” Placement of screws and interbody devices are technically challenging due to their close proximity to vital neural and vascular structures. The current commercial robotic systems focus on guiding pedicle screws only. These systems generally rely on preoperative imaging that is merged with intraoperative positioning data for calibration and trajectory planning. The planned screw trajectory is executed by the surgeon manually. In complex tasks in spinal surgery such as TLIF (where the intervertebral disc is removed, bony end plates are prepared, and biomechanical implants are placed through interference fit to facilitate fusion), surgeons are limited in their visualization and approach by the constraints of the anatomy. In order to accomplish their goals, surgeons frequently create collateral damage on normal anatomical structures. We propose that an active surgical robotic system integrated with continuum dexterous manipulators (CDM) may provide the ability to accomplish complex spinal surgical tasks such as spinal decompression and TLIF with less disruption to surrounding tissues, and thus, result in reduction of collateral damage compared to traditional, open surgery and traditional MIS spinal surgery.