Robotic System for Spinal Decompression and Interbody Fusion

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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.