Pedicle screw navigation using surface digitization on the Microsoft HoloLens.


Journal

International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225

Informations de publication

Date de publication:
Jul 2019
Historique:
received: 30 01 2019
accepted: 04 04 2019
pubmed: 18 4 2019
medline: 29 10 2019
entrez: 18 4 2019
Statut: ppublish

Résumé

In spinal fusion surgery, imprecise placement of pedicle screws can result in poor surgical outcome or may seriously harm a patient. Patient-specific instruments and optical systems have been proposed for improving precision through surgical navigation compared to freehand insertion. However, existing solutions are expensive and cannot provide in situ visualizations. Recent technological advancement enabled the production of more powerful and precise optical see-through head-mounted displays for the mass market. The purpose of this laboratory study was to evaluate whether such a device is sufficiently precise for the navigation of lumbar pedicle screw placement. A novel navigation method, tailored to run on the Microsoft HoloLens, was developed. It comprises capturing of the intraoperatively reachable surface of vertebrae to achieve registration and tool tracking with real-time visualizations without the need of intraoperative imaging. For both surface sampling and navigation, 3D printable parts, equipped with fiducial markers, were employed. Accuracy was evaluated within a self-built setup based on two phantoms of the lumbar spine. Computed tomography (CT) scans of the phantoms were acquired to carry out preoperative planning of screw trajectories in 3D. A surgeon placed the guiding wire for the pedicle screw bilaterally on ten vertebrae guided by the navigation method. Postoperative CT scans were acquired to compare trajectory orientation (3D angle) and screw insertion points (3D distance) with respect to the planning. The mean errors between planned and executed screw insertion were [Formula: see text] for the screw trajectory orientation and 2.77±1.46 mm for the insertion points. The mean time required for surface digitization was 125±27 s. First promising results under laboratory conditions indicate that precise lumbar pedicle screw insertion can be achieved by combining HoloLens with our proposed navigation method. As a next step, cadaver experiments need to be performed to confirm the precision on real patient anatomy.

Identifiants

pubmed: 30993519
doi: 10.1007/s11548-019-01973-7
pii: 10.1007/s11548-019-01973-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1157-1165

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Auteurs

Florentin Liebmann (F)

Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland. florentin.liebmann@balgrist.ch.
Laboratory for Orthopaedic Biomechanics, ETH Zurich, Zurich, Switzerland. florentin.liebmann@balgrist.ch.

Simon Roner (S)

Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Orthopaedic Department, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.

Marco von Atzigen (M)

Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Laboratory for Orthopaedic Biomechanics, ETH Zurich, Zurich, Switzerland.

Davide Scaramuzza (D)

Department of Informatics, University of Zurich, Zurich, Switzerland.
Department of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.

Reto Sutter (R)

Radiology Department, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.

Jess Snedeker (J)

Laboratory for Orthopaedic Biomechanics, ETH Zurich, Zurich, Switzerland.
Orthopaedic Department, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.

Mazda Farshad (M)

Orthopaedic Department, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.

Philipp Fürnstahl (P)

Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.

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Classifications MeSH