Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery

Otake, Yoshito; Schäfer, Sebastian; Stayman, J. Webster; Zbijewski, Wojciech; Kleinszig, Gerhard; Graumann, Rainer; Khanna, A. Jay; Siewerdsen, J. H.

doi:10.1088/0031-9155/57/17/5485

Cited by 72 publications

(95 citation statements)

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“…The resulting transformation enables the vertebral labels in the CT image to be accurately projected and overlaid in p . The overall framework illustrated in figure 2 is consistent with that in Otake et al (2012, 2013, 2015) and De Silva et al (2016a).…”

Section: Methodssupporting

confidence: 73%

“…Assuming a nominal magnification factor of 2, the volume was downsampled isotropically to a pix /2. The step length for ray casting was chosen to be 2 voxels (equivalently, a pix ) based on a sensitivity study reported in Otake et al (2012). Consistent with Ketcha et al (2016), a soft tissue threshold of 150 HU (shown previously to be insensitive to the particular threshold choice in the range 50 to 300 HU) was applied to the CT image (setting the value to 0 if below) to remove low attenuation regions in the forward projection, and basic overlap of the DRR with the projection image was ensured by translating the CT volume along the longitudinal direction of the patient, thereby determining an initial value for y r , and resulting in an initial registration error of ~20 – 200 mm.…”

Section: Methodsmentioning

confidence: 99%

“…The chosen SR values reflect the assumption of a coarse estimate longitudinal initialization but fairly accurate rotational initialization that comes from knowledge of patient positioning (e.g., knowing that the image is a lateral radiograph). As detailed in Otake et al (2012, 2013), a rigorous parameter sweep was performed to determine values for MS and lambda that yielded robust performance while minimizing GPU memory and computation time.…”

Section: Methodsmentioning

confidence: 99%

“…A wrong-level error can lead to suboptimal (or failed) surgical product and potentially costly litigation (Mody et al 2008). To prevent such occurrences and potentially improve workflow and confidence in target localization, a 3D-2D registration framework (called LevelCheck) has been shown to automatically overlay relevant target anatomy such as vertebral labels from 3D preoperative imaging (CT or MR) to the intraoperative 2D image as a means of decision support (Otake et al 2012, 2013, 2015, De Silva et al 2016a, b). LevelCheck has been shown to provide robust registration under many challenging scenarios that are commonly encountered in clinical images, including poor image quality and content mismatch (e.g., surgical instrumentation appearing in the radiograph that is not in the 3D image); however, the accuracy of rigid 3D-2D registration may be compromised in the presence of deformation.…”

Section: Introductionmentioning

confidence: 99%

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Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

et al. 2017

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Purpose A multi-stage image-based 3D-2D registration method is presented that maps annotations in a 3D image (e.g., point labels annotating individual vertebrae in preoperative CT) to an intraoperative radiograph in which the patient has undergone non-rigid anatomical deformation due to changes in patient positioning or due to the intervention itself. Methods The proposed method (termed msLevelCheck) extends a previous rigid registration solution (LevelCheck) to provide an accurate mapping of vertebral labels in the presence of spinal deformation. The method employs a multi-stage series of rigid 3D-2D registrations performed on sets of automatically determined and increasingly localized sub-images, with the final stage achieving a rigid mapping for each label to yield a locally rigid yet globally deformable solution. The method was evaluated first in a phantom study in which a CT image of the spine was acquired followed by a series of 7 mobile radiographs with increasing degree of deformation applied. Second, the method was validated using a clinical data set of patients exhibiting strong spinal deformation during thoracolumbar spine surgery. Registration accuracy was assessed using projection distance error (PDE) and failure rate (PDE > 20 mm – i.e., label registered outside vertebra). Results The msLevelCheck method was able to register all vertebrae accurately for all cases of deformation in the phantom study, improving the maximum PDE of the rigid method from 22.4 mm to 3.9 mm. The clinical study demonstrated the feasibility of the approach in real patient data by accurately registering all vertebral labels in each case, eliminating all instances of failure encountered in the conventional rigid method. Conclusion The multi-stage approach demonstrated accurate mapping of vertebral labels in the presence of strong spinal deformation. The msLevelCheck method maintains other advantageous aspects of the original LevelCheck method (e.g., compatibility with standard clinical workflow, large capture range, and robustness against mismatch in image content) and extends capability to cases exhibiting strong changes in spinal curvature.

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Section: Methodssupporting

confidence: 73%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

et al. 2017

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“…Previous work established a method for fast, robust registration of preoperative 3D images to intraoperative radiography/fluoroscopy, 3,4 demonstrating 3D registration accuracy of target registration error (TRE) <2 mm using only two fluoroscopic views acquired at <20° separation (where 90° separation implies biplane acquisition). 5 The current work extends the registration method to iteratively solve for the rigid transformation ( ) such that a digitally reconstructed radiograph (DRR) from a known component ( C ) yields maximum similarity to intraoperative 2D projections ( f , fixed images, acquired with a C-arm).…”

Section: Methodsmentioning

confidence: 99%

Known-component 3D-2D registration for image guidance and quality assurance in spine surgery pedicle screw placement

et al. 2015

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Purpose To extend the functionality of radiographic/fluoroscopic imaging systems already within standard spine surgery workflow to: 1) provide guidance of surgical device analogous to an external tracking system; and 2) provide intraoperative quality assurance (QA) of the surgical product. Methods Using fast, robust 3D-2D registration in combination with 3D models of known components (surgical devices), the 3D pose determination was solved to relate known components to 2D projection images and 3D preoperative CT in near-real-time. Exact and parametric models of the components were used as input to the algorithm to evaluate the effects of model fidelity. The proposed algorithm employs the covariance matrix adaptation evolution strategy (CMA-ES) to maximize gradient correlation (GC) between measured projections and simulated forward projections of components. Geometric accuracy was evaluated in a spine phantom in terms of target registration error at the tool tip (TREx), and angular deviation (TREϕ) from planned trajectory. Results Transpedicle surgical devices (probe tool and spine screws) were successfully guided with TREx <2 mm and TREϕ<0.5° given projection views separated by at least >30° (easily accommodated on a mobile C-arm). QA of the surgical product based on 3D-2D registration demonstrated the detection of pedicle screw breach with TREx <1 mm, demonstrating a trend of improved accuracy correlated to the fidelity of the component model employed. Conclusions 3D-2D registration combined with 3D models of known surgical components provides a novel method for near-real-time guidance and quality assurance using a mobile C-arm without external trackers or fiducial markers. Ongoing work includes determination of optimal views based on component shape and trajectory, improved robustness to anatomical deformation, and expanded preclinical testing in spine and intracranial surgeries.

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Interventions for reducing wrong-site surgery and invasive clinical procedures

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et al. 2015

Cochrane Database of Systematic Reviews

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Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery

Cited by 72 publications

References 50 publications

Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

Multi-stage 3D–2D registration for correction of anatomical deformation in image-guided spine surgery

Known-component 3D-2D registration for image guidance and quality assurance in spine surgery pedicle screw placement

Interventions for reducing wrong-site surgery and invasive clinical procedures

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