Workflow and performance of intraoperative CT, cone-beam CT, and robotic cone-beam CT for spinal navigation in 503 consecutive patients

OBJECTIVE A direct comparison of intraoperative CT (iCT), cone-beam CT (CBCT), and robotic cone-beam CT (rCBCT) has been necessary to identify the ideal imaging solution for each individual user’s need. Herein, the authors sought to analyze workflow, handling, and performance of iCT, CBCT, and rCBCT imaging for navigated pedicle screw instrumentation across the entire spine performed within the same surgical environment by the same group of surgeons. METHODS Between 2014 and 2018, 503 consecutive patients received 2673 navigated pedicle screws using iCT (n = 1219), CBCT (n = 646), or rCBCT (n = 808) imaging during the first 24 months after the acquisition of each modality. Clinical and demographic data, workflow, handling, and screw assessment and accuracy were analyzed. RESULTS Intraoperative CT showed image quality and workflow advantages for cervicothoracic cases, obese patients, and long-segment instrumentation, whereas CBCT and rCBCT offered independent handling, around-the-clock availability, and the option of performing 2D fluoroscopy. All modalities permitted reliable intraoperative screw assessment. Navigated screw revision was possible with each modality and yielded final accuracy rates > 92% in all groups (iCT 96.2% vs CBCT 92.3%, p < 0.001) without a difference in the accuracy of cervical pedicle screw placement or the rate of secondary screw revision surgeries. CONCLUSIONS Continuous training and an individual setup of iCT, CBCT, and rCBCT has been shown to permit safe and precise navigated posterior instrumentation across the entire spine with reliable screw assessment and the option of immediate revision. The perceived higher image quality and larger scan area of iCT should be weighed against the around-the-clock availability of CBCT and rCBCT technology with the option of single-handed robotic image acquisition.

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Navigated percutaneous versus open pedicle screw implantation using intraoperative CT and robotic cone-beam CT imaging

European Spine Journal ◽

10.1007/s00586-019-06242-4 ◽

2019 ◽

Vol 29 (4) ◽

pp. 803-812 ◽

Cited By ~ 1

Author(s):

Dimitri Tkatschenko ◽

Paul Kendlbacher ◽

Marcus Czabanka ◽

Georg Bohner ◽

Peter Vajkoczy ◽

...

Keyword(s):

Pedicle Screw ◽

Cone Beam Ct ◽

Ct Imaging ◽

Cone Beam ◽

Intraoperative Ct

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Pedicle Screw Placement Using Intraoperative CT and Computer Aided Spinal Navigation Improves Screw Accuracy and Avoids Postoperative Revisions: Single-Center Analysis Of 1400 Pedicle Screws

World Neurosurgery ◽

10.1016/j.wneu.2021.12.112 ◽

2022 ◽

Author(s):

Matthew J. Hagan ◽

Sohail Syed ◽

Owen P. Leary ◽

Elijah M. Persad-Paisley ◽

Yang Lin ◽

...

Keyword(s):

Pedicle Screw ◽

Pedicle Screws ◽

Screw Placement ◽

Single Center ◽

Pedicle Screw Placement ◽

Intraoperative Ct ◽

Spinal Navigation ◽

Computer Aided

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Intraoperative cone beam CT in hybrid operating room set-up as an alternative to postoperative CT for pedicle screw breach detection

10.21203/rs.3.rs-256928/v1 ◽

2021 ◽

Author(s):

Simon Peh ◽

Julian Pfarr ◽

Jost Philipp Schäfer ◽

Jan-Hendrik Christensen ◽

Anindita Chatterjea ◽

...

Keyword(s):

Radiation Dose ◽

Pedicle Screw ◽

Operating Room ◽

Cone Beam Ct ◽

Pedicle Screws ◽

Roc Curves ◽

Cone Beam ◽

Screw Placement ◽

Hybrid Operating Room ◽

Effective Radiation Dose

Abstract Background CT is considered the gold standard for detecting pedicle breach. However, CBCT may be a viable and low radiation dose alternative, to provide intraoperative feedback to surgeons to permit in-room revisions of misplaced screws Methods To assess the ability and reliability of intraoperative cone-beam CT (CBCT) from a robotic C-arm in a hybrid operating room (OR) two hundred forty-one pedicle screws were inserted in cervical, thoracic and lumbar spine of 7 cadavers, followed by CBCT and CT imaging. The CT images served as the standard of reference. Agreement on screw placement between both imaging systems was assessed using Cohen’s Kappa coefficient (κ). Sensitivity, Specificity, Receiver operating characteristic (ROC), area under the empirical and fitted ROC curves (AUC) were computed to assess CBCT as a diagnostic tool compared to CT. The patient effective radiation dose (ED) was calculated for comparison. A systematic literature review was performed to provide perspective to the obtained results. Results Almost perfect agreement in assessing pedicle screw grading between CBCT and CT was observed (κ = 0.84). The sensitivity and specificity of CBCT were 0.84 and 0.98, respectively. The AUC derived from the empirical and fitted ROC curves were 0.95 and 0.96, respectively. Conclusion Intraoperative CBCT by C-arm in a hybrid OR is highly reliable in identification of screw placement at significant dose reduction.

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Machine learning for automated 3-dimensional segmentation of the spine and suggested placement of pedicle screws based on intraoperative cone-beam computer tomography

Journal of Neurosurgery Spine ◽

10.3171/2018.12.spine181397 ◽

2019 ◽

Vol 31 (1) ◽

pp. 147-154 ◽

Cited By ~ 16

Author(s):

Gustav Burström ◽

Christian Buerger ◽

Jurgen Hoppenbrouwers ◽

Rami Nachabe ◽

Cristian Lorenz ◽

...

Keyword(s):

Machine Learning ◽

Pedicle Screw ◽

Surgical Navigation ◽

Cone Beam Ct ◽

Automatic Segmentation ◽

Pedicle Screws ◽

Image Data ◽

Qualitative Evaluation ◽

Cone Beam ◽

Severe Spinal Deformities

OBJECTIVEThe goal of this study was to develop and validate a system for automatic segmentation of the spine, pedicle identification, and screw path suggestion for use with an intraoperative 3D surgical navigation system.METHODSCone-beam CT (CBCT) images of the spines of 21 cadavers were obtained. An automated model-based approach was used for segmentation. Using machine learning methodology, the algorithm was trained and validated on the image data sets. For measuring accuracy, surface area errors of the automatic segmentation were compared to the manually outlined reference surface on CBCT. To further test both technical and clinical accuracy, the algorithm was applied to a set of 20 clinical cases. The authors evaluated the system’s accuracy in pedicle identification by measuring the distance between the user-defined midpoint of each pedicle and the automatically segmented midpoint. Finally, 2 independent surgeons performed a qualitative evaluation of the segmentation to judge whether it was adequate to guide surgical navigation and whether it would have resulted in a clinically acceptable pedicle screw placement.RESULTSThe clinically relevant pedicle identification and automatic pedicle screw planning accuracy was 86.1%. By excluding patients with severe spinal deformities (i.e., Cobb angle > 75° and severe spinal degeneration) and previous surgeries, a success rate of 95.4% was achieved. The mean time (± SD) for automatic segmentation and screw planning in 5 vertebrae was 11 ± 4 seconds.CONCLUSIONSThe technology investigated has the potential to aid surgeons in navigational planning and improve surgical navigation workflow while maintaining patient safety.

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