Robot-Assisted Percutaneous Pedicle Screw Placement: Evaluation of Accuracy of the First 100 Screws and Comparison with Cohort of Fluoroscopy-guided Screws.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
11 2020
Historique:
received: 23 06 2020
revised: 26 07 2020
accepted: 28 07 2020
pubmed: 8 8 2020
medline: 14 5 2021
entrez: 8 8 2020
Statut: ppublish

Résumé

Percutaneous pedicle screws (PPS) are used to stabilize the spine after interbody fusion in minimally invasive approaches. Recently, robotic assistance has been developed to improve the accuracy of PPS. We report our initial experience with ExcelsiusGPS and compare its accuracy with our historical cohort of fluoroscopy-guided PPS. We reviewed prospectively collected data from our first 100 robot-assisted PPS. We graded accuracy of screws on computed tomography imaging and compared it with a previous cohort of 90 PPS placed using fluoroscopy. We also analyzed the effect of various demographic and perioperative metrics on accuracy. We placed 103 PPS in the first 20 consecutive patients with postoperative computed tomography imaging using ExcelsiusGPS. All screws were placed at L2 to S1. Our robot-assisted cohort had 6 breaches, with only 2 breaches >2 mm, yielding an overall breach rate of 5.8% and a significant breach rate of 1.9%. In comparison, our fluoroscopy-guided cohort had a breach rate of 3.3% and a significant breach rate of 1.1%, which was not significantly different. More breaches occurred in the first half of cases, suggesting a learning curve with robotic assistance. No demographic or perioperative metrics had a significant effect on accuracy. Our breach rates with ExcelsiusGPS were low and consistent with others reported in the literature, as well as with other robotic systems. Our series shows equivalent accuracy of placement of PPS with this robotic platform compared with fluoroscopic guidance and suggests a relatively short learning curve.

Identifiants

pubmed: 32758652
pii: S1878-8750(20)31725-3
doi: 10.1016/j.wneu.2020.07.203
pii:
doi:

Types de publication

Comparative Study Evaluation Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e492-e502

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Islam Fayed (I)

Department of Neurosurgery, MedStar Georgetown University Hospital, Washington, DC. Electronic address: islam.f.fayed@gmail.com.

Alexander Tai (A)

Department of Neurosurgery, MedStar Georgetown University Hospital, Washington, DC.

Matthew Triano (M)

Georgetown University School of Medicine, Washington, DC, USA.

Anousheh Sayah (A)

Department of Radiology, MedStar Georgetown University Hospital, Washington, DC.

Erini Makariou (E)

Department of Radiology, MedStar Georgetown University Hospital, Washington, DC.

Jean-Marc Voyadzis (JM)

Department of Neurosurgery, MedStar Georgetown University Hospital, Washington, DC.

Faheem A Sandhu (FA)

Department of Neurosurgery, MedStar Georgetown University Hospital, Washington, DC.

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