Autonomous Spinal Robotic System for Transforaminal Lumbar Epidural Injections: A Proof of Concept of Study.

autonomous surgical robot interventional radiology orthopaedic surgery pain management robot-assisted surgery spinal rehabilitation

Journal

Global spine journal
ISSN: 2192-5682
Titre abrégé: Global Spine J
Pays: England
ID NLM: 101596156

Informations de publication

Date de publication:
Jan 2024
Historique:
medline: 26 4 2022
pubmed: 26 4 2022
entrez: 25 4 2022
Statut: ppublish

Résumé

Phantom study. The aim of our study is to demonstrate in a proof-of-concept model whether the use of a marker less autonomous robotic controlled injection delivery system will increase accuracy in the lumbar spine. Ideal transforaminal epidural injection trajectories (bilateral L2/3, L3/4, L4/5, L5/S1 and S1) were planned out on a virtual pre-operative planning software by 1 experienced provider. Twenty transforaminal epidural injections were administered in a lumbar spine phantom model, 10 using a freehand procedure, and 10 using a marker less autonomous spinal robotic system. Procedural accuracy, defined as the difference between pre-operative planning and actual post-operative needle tip distance (mm) and angular orientation (degrees), were assessed between the freehand and robotic procedures. Procedural accuracy for robotically placed transforaminal epidural injections was significantly higher with the difference in pre- and post-operative needle tip distance being 20.1 (±5.0) mm in the freehand procedure and 11.4 (±3.9) mm in the robotically placed procedure ( The robotic system allowed for comparable placement of transforaminal epidural injections as a freehand technique by an experienced provider, with additional benefits of improved accuracy and precision.

Identifiants

pubmed: 35467447
doi: 10.1177/21925682221096625
pmc: PMC10676186
doi:

Types de publication

Journal Article

Langues

eng

Pagination

138-145

Subventions

Organisme : NIAMS NIH HHS
ID : R01 AR080315
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB016703
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB023939
Pays : United States
Organisme : NIAMS NIH HHS
ID : T32 AR067708
Pays : United States

Déclaration de conflit d'intérêts

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Auteurs

Adam Margalit (A)

Department of Orthopaedic Surgery, The Johns Hopkins University, Baltimore, MD, USA.

Henry Phalen (H)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Cong Gao (C)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Justin Ma (J)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Krishna V Suresh (KV)

Department of Orthopaedic Surgery, The Johns Hopkins University, Baltimore, MD, USA.

Punya Jain (P)

Department of Orthopaedic Surgery, The Johns Hopkins University, Baltimore, MD, USA.

Amirhossein Farvardin (A)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Russell H Taylor (RH)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Mehran Armand (M)

Johns Hopkins Whiting School of Engineering, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA.

Akhil Chattre (A)

Department of Orthopaedic Surgery, The Johns Hopkins University, Baltimore, MD, USA.

Amit Jain (A)

Department of Orthopaedic Surgery, The Johns Hopkins University, Baltimore, MD, USA.

Classifications MeSH