A level-wise spine registration framework to account for large pose changes

A review of advances in image-guided orthopedic surgery

Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.

Accuracy of Stereovision-Updated Versus Preoperative CT-Based Image Guidance in Multilevel Lumbar Pedicle Screw Placement: A Cadaveric Swine Study

Change in vertebral position between preoperative imaging and the surgical procedure reduces the accuracy of image-guided spinal surgery, requiring repeated imaging and surgical field registration, a process that takes time and exposes patients to additional radiation. We developed a handheld, camera-based, deformable registration system (intraoperative stereovision, iSV) to register the surgical field automatically and compensate for spinal motion during surgery without further radiation exposure.

Methods

We measured motion-induced errors in image-guided lumbar pedicle screw placement in 6 whole-pig cadavers using state-of-the-art commercial spine navigation (StealthStation; Medtronic) and iSV registration that compensates for intraoperative vertebral motion. We induced spinal motion by using preoperative computed tomography (pCT) of the lumbar spine performed in the supine position with accentuated lordosis and performing surgery with the animal in the prone position. StealthStation registration of pCT occurred using metallic fiducial markers implanted in each vertebra, and iSV data were acquired to perform a deformable registration between pCT and the surgical field. Sixty-eight pedicle screws were placed in 6 whole-pig cadavers using iSV and StealthStation registrations in random order of vertebral level, relying only on image guidance without invoking the surgeon's judgment. The position of each pedicle screw was assessed with post-procedure CT and confirmed via anatomical dissection. Registration errors were assessed on the basis of implanted fiducials.

Results

The frequency and severity of pedicle screw perforation were lower for iSV registration compared with StealthStation (97% versus 68% with Grade 0 medial perforation for iSV and StealthStation, respectively). Severe perforation occurred only with StealthStation (18% versus 0% for iSV). The overall time required for iSV registration (computational efficiency) was ∼10 to 15 minutes and was comparable with StealthStation registration (∼10 min). The mean target registration error was smaller for iSV relative to StealthStation (2.81 ± 0.91 versus 8.37 ± 1.76 mm).

Conclusions

Pedicle screw placement was more accurate with iSV registration compared with state-of-the-art commercial navigation based on preoperative CT when alignment of the spine changed during surgery.

Clinical Relevance

The iSV system compensated for intervertebral motion, which obviated the need for repeated vertebral registration while providing efficient, accurate, radiation-free navigation during open spinal surgery.