Spinal Navigation and Imaging: History, Trends, and Future

Helm, Patrick A.; Teichman, R.S.; Hartmann, Steven L.; Simon, David A.

doi:10.1109/tmi.2015.2391200

Cited by 92 publications

(58 citation statements)

References 69 publications

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“…2 Several levels can be planned with the same degree of accuracy, without the need for invasive dynamic reference frame positioning and recalibrations. Several other studies have highlighted technical reasons for inaccurate screw placement.…”

Section: Discussionmentioning

confidence: 99%

“…1 Current systems typically consist of an infrared-camera tracking unit linked to an intraoperative computed tomography (CT) and a reference frame attached to the spinous vertebral process for registration and tracking purposes. 2 …”

mentioning

confidence: 99%

“…2 In the thoracic spine, pedicle screw placement accuracy remains a challenge because of the morphology ( e.g. , smaller pedicle size).…”

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confidence: 99%

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Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging

Elmi-Terander

Skúlason

Söderman

et al. 2016

Spine

133

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Study Design.A cadaveric laboratory study.Objective.The aim of this study was to assess the feasibility and accuracy of thoracic pedicle screw placement using augmented reality surgical navigation (ARSN).Summary of Background Data.Recent advances in spinal navigation have shown improved accuracy in lumbosacral pedicle screw placement but limited benefits in the thoracic spine. 3D intraoperative imaging and instrument navigation may allow improved accuracy in pedicle screw placement, without the use of x-ray fluoroscopy, and thus opens the route to image-guided minimally invasive therapy in the thoracic spine.Methods.ARSN encompasses a surgical table, a motorized flat detector C-arm with intraoperative 2D/3D capabilities, integrated optical cameras for augmented reality navigation, and noninvasive patient motion tracking. Two neurosurgeons placed 94 pedicle screws in the thoracic spine of four cadavers using ARSN on one side of the spine (47 screws) and free-hand technique on the contralateral side. X-ray fluoroscopy was not used for either technique. Four independent reviewers assessed the postoperative scans, using the Gertzbein grading. Morphometric measurements of the pedicles axial and sagittal widths and angles, as well as the vertebrae axial and sagittal rotations were performed to identify risk factors for breaches.Results.ARSN was feasible and superior to free-hand technique with respect to overall accuracy (85% vs. 64%, P < 0.05), specifically significant increases of perfectly placed screws (51% vs. 30%, P < 0.05) and reductions in breaches beyond 4 mm (2% vs. 25%, P < 0.05). All morphometric dimensions, except for vertebral body axial rotation, were risk factors for larger breaches when performed with the free-hand method.Conclusion.ARSN without fluoroscopy was feasible and demonstrated higher accuracy than free-hand technique for thoracic pedicle screw placement.Level of Evidence: N/A

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging

Elmi-Terander

Skúlason

Söderman

et al. 2016

Spine

133

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“…Navigation based on optical tracking (Peters, 2006) has been widely applied in neurosurgery (Helm et al, 2015) and orthopaedic surgery – e.g., pelvic screw insertion (Barrick et al, 1998; Xu et al, 2013; Wong et al, 2015). In such procedures, the bone and tool are marked with fiducials to allow the tracker to identify their positions.…”

Section: Introductionmentioning

confidence: 99%

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

et al. 2017

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Percutaneous pelvic screw placement is challenging due to narrow bone corridors surrounded by vulnerable structures and difficult visual interpretation of complex anatomical shapes in 2D x-ray projection images. To address these challenges, a system for planning, guidance, and quality assurance (QA) is presented, providing functionality analogous to surgical navigation, but based on robust 3D-2D image registration techniques using fluoroscopy images already acquired in routine workflow. Two novel aspects of the system are investigated: automatic planning of pelvic screw trajectories and the ability to account for deformation of surgical devices (K-wire deflection). Atlas-based registration is used to calculate a patient-specific plan of screw trajectories in preoperative CT. 3D-2D registration aligns the patient to CT within the projective geometry of intraoperative fluoroscopy. Deformable known-component registration (dKC-Reg) localizes the surgical device, and the combination of plan and device location is used to provide guidance and QA. A leave-one-out analysis evaluated the accuracy of automatic planning, and a cadaver experiment compared the accuracy of dKC-Reg to rigid approaches (e.g., optical tracking). Surgical plans conformed within the bone cortex by 3–4 mm for the narrowest corridor (superior pubic ramus) and >5 mm for the widest corridor (tear drop). The dKC-Reg algorithm localized the K-wire tip within 1.1 mm and 1.4° and was consistently more accurate than rigid-body tracking (errors up to 9 mm). The system was shown to automatically compute reliable screw trajectories and accurately localize deformed surgical devices (K-wires). Such capability could improve guidance and QA in orthopaedic surgery, where workflow is impeded by manual planning, conventional tool trackers add complexity and cost, rigid tool assumptions are often inaccurate, and qualitative interpretation of complex anatomy from 2D projections is prone to trial-and-error with extended fluoroscopy time.

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“…; for instance, the orthopedic surgical navigation systems of Medtronic indicate only the distance between the surgical tools and the positioning system. Moreover, these tools must maintain an appropriate distance from one another [11]. Nonetheless, the distribution of errors in different positions that are equidistant from the positioning system also varies; this distribution is mainly subject to the position where the cameras shoot the marked points as well as to the resolution of these points on the images.…”

Section: Introductionmentioning

confidence: 99%

Synchronization Design and Error Analysis of Near-Infrared Cameras in Surgical Navigation

et al. 2015

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The accuracy of optical tracking systems is important to scientists. With the improvements reported in this regard, such systems have been applied to an increasing number of operations. To enhance the accuracy of these systems further and to reduce the effect of synchronization and visual field errors, this study introduces a field-programmable gate array (FPGA)-based synchronization control method, a method for measuring synchronous errors, and an error distribution map in field of view. Synchronization control maximizes the parallel processing capability of FPGA, and synchronous error measurement can effectively detect the errors caused by synchronization in an optical tracking system. The distribution of positioning errors can be detected in field of view through the aforementioned error distribution map. Therefore, doctors can perform surgeries in areas with few positioning errors, and the accuracy of optical tracking systems is considerably improved. The system is analyzed and validated in this study through experiments that involve the proposed methods, which can eliminate positioning errors attributed to asynchronous cameras and different fields of view.

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Spinal Navigation and Imaging: History, Trends, and Future

Cited by 92 publications

References 69 publications

Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging

Surgical Navigation Technology Based on Augmented Reality and Integrated 3D Intraoperative Imaging

Planning, guidance, and quality assurance of pelvic screw placement using deformable image registration

Synchronization Design and Error Analysis of Near-Infrared Cameras in Surgical Navigation

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