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Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation

BACKGROUND CONTEXT: Computer-assisted navigation (CAN) may guide spinal instrumentation, and requires alignment of patient anatomy to imaging. Iterative closest-point (ICP) algorithms register anatomical and imaging surface datasets, which may fail in the presence of geometric symmetry (congruence),...

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Autores principales: Guha, Daipayan, Jakubovic, Raphael, Leung, Michael K., Ginsberg, Howard J., Fehlings, Michael G., Mainprize, Todd G., Yee, Albert, Yang, Victor X. D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710030/
https://www.ncbi.nlm.nih.gov/pubmed/31450234
http://dx.doi.org/10.1371/journal.pone.0207137
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author Guha, Daipayan
Jakubovic, Raphael
Leung, Michael K.
Ginsberg, Howard J.
Fehlings, Michael G.
Mainprize, Todd G.
Yee, Albert
Yang, Victor X. D.
author_facet Guha, Daipayan
Jakubovic, Raphael
Leung, Michael K.
Ginsberg, Howard J.
Fehlings, Michael G.
Mainprize, Todd G.
Yee, Albert
Yang, Victor X. D.
author_sort Guha, Daipayan
collection PubMed
description BACKGROUND CONTEXT: Computer-assisted navigation (CAN) may guide spinal instrumentation, and requires alignment of patient anatomy to imaging. Iterative closest-point (ICP) algorithms register anatomical and imaging surface datasets, which may fail in the presence of geometric symmetry (congruence), leading to failed registration or inaccurate navigation. Here we computationally quantify geometric congruence in posterior spinal exposures, and identify predictors of potential navigation inaccuracy. METHODS: Midline posterior exposures were performed from C1-S1 in four human cadavers. An optically-based CAN generated surface maps of the posterior elements at each level. Maps were reconstructed to include bilateral hemilamina, or unilateral hemilamina with/without the base of the spinous process. Maps were fitted to symmetrical geometries (cylindrical/spherical/planar) using computational modelling, and the degree of model fit quantified based on the ratio of model inliers to total points. Geometric congruence was subsequently assessed clinically in 11 patients undergoing midline exposures in the cervical/thoracic/lumbar spine for posterior instrumented fusion. RESULTS: In cadaveric testing, increased cylindrical/spherical/planar symmetry was seen in the high-cervical and subaxial cervical spine relative to the thoracolumbar spine (p<0.001). Extension of unilateral exposures to include the ipsilateral base of the spinous process decreased symmetry independent of spinal level (p<0.001). In clinical testing, increased cylindrical/spherical/planar symmetry was seen in the subaxial cervical relative to the thoracolumbar spine (p<0.001), and in the thoracic relative to the lumbar spine (p<0.001). Symmetry in unilateral exposures was decreased by 20% with inclusion of the ipsilateral base of the spinous process. CONCLUSIONS: Geometric congruence is most evident at C1 and the subaxial cervical spine, warranting greater vigilance in navigation accuracy verification. At all levels, inclusion of the base of the spinous process in unilateral registration decreases the likelihood of geometric symmetry and navigation error. This work is important to allow the extension of line-of-sight based registration techniques to minimally-invasive unilateral approaches.
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spelling pubmed-67100302019-09-10 Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation Guha, Daipayan Jakubovic, Raphael Leung, Michael K. Ginsberg, Howard J. Fehlings, Michael G. Mainprize, Todd G. Yee, Albert Yang, Victor X. D. PLoS One Research Article BACKGROUND CONTEXT: Computer-assisted navigation (CAN) may guide spinal instrumentation, and requires alignment of patient anatomy to imaging. Iterative closest-point (ICP) algorithms register anatomical and imaging surface datasets, which may fail in the presence of geometric symmetry (congruence), leading to failed registration or inaccurate navigation. Here we computationally quantify geometric congruence in posterior spinal exposures, and identify predictors of potential navigation inaccuracy. METHODS: Midline posterior exposures were performed from C1-S1 in four human cadavers. An optically-based CAN generated surface maps of the posterior elements at each level. Maps were reconstructed to include bilateral hemilamina, or unilateral hemilamina with/without the base of the spinous process. Maps were fitted to symmetrical geometries (cylindrical/spherical/planar) using computational modelling, and the degree of model fit quantified based on the ratio of model inliers to total points. Geometric congruence was subsequently assessed clinically in 11 patients undergoing midline exposures in the cervical/thoracic/lumbar spine for posterior instrumented fusion. RESULTS: In cadaveric testing, increased cylindrical/spherical/planar symmetry was seen in the high-cervical and subaxial cervical spine relative to the thoracolumbar spine (p<0.001). Extension of unilateral exposures to include the ipsilateral base of the spinous process decreased symmetry independent of spinal level (p<0.001). In clinical testing, increased cylindrical/spherical/planar symmetry was seen in the subaxial cervical relative to the thoracolumbar spine (p<0.001), and in the thoracic relative to the lumbar spine (p<0.001). Symmetry in unilateral exposures was decreased by 20% with inclusion of the ipsilateral base of the spinous process. CONCLUSIONS: Geometric congruence is most evident at C1 and the subaxial cervical spine, warranting greater vigilance in navigation accuracy verification. At all levels, inclusion of the base of the spinous process in unilateral registration decreases the likelihood of geometric symmetry and navigation error. This work is important to allow the extension of line-of-sight based registration techniques to minimally-invasive unilateral approaches. Public Library of Science 2019-08-26 /pmc/articles/PMC6710030/ /pubmed/31450234 http://dx.doi.org/10.1371/journal.pone.0207137 Text en © 2019 Guha et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Guha, Daipayan
Jakubovic, Raphael
Leung, Michael K.
Ginsberg, Howard J.
Fehlings, Michael G.
Mainprize, Todd G.
Yee, Albert
Yang, Victor X. D.
Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title_full Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title_fullStr Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title_full_unstemmed Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title_short Quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
title_sort quantification of computational geometric congruence in surface-based registration for spinal intra-operative three-dimensional navigation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6710030/
https://www.ncbi.nlm.nih.gov/pubmed/31450234
http://dx.doi.org/10.1371/journal.pone.0207137
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