Mako Robotic-Arm Assisted Total Knee Arthroplasty: Updated Software.


Journal

Surgical technology international
ISSN: 1090-3941
Titre abrégé: Surg Technol Int
Pays: United States
ID NLM: 9604509

Informations de publication

Date de publication:
07 Oct 2024
Historique:
medline: 8 10 2024
pubmed: 8 10 2024
entrez: 7 10 2024
Statut: aheadofprint

Résumé

Recently, robotic-arm assisted total knee arthroplasties have become popular because of their promise to lead to enhanced accuracy and efficient planning of the procedure, as well as improved radiographic and clinical outcomes. One robotic system is based on computed tomography (CT) to help with preoperative planning, intraoperative adjusting, and bone cutting for these procedures. The purpose of this article is to describe the second-generation iteration of this CT-based robotic technique by describing the new features using an actual total knee arthroplasty case. This article then becomes a step-by-step guide to performing the procedure, as well as describing the new features of this upgraded system.

Identifiants

pubmed: 39374581
pii: sti45/1817
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Robert Marchand (R)

Department of Orthopaedic Surgery, South County Orthopedics, Wakefield, Rhode Island.

Sean B Sequeira (SB)

Department of Orthopaedic Surgery, Medstar Union Memorial Hospital, Baltimore, Maryland.

Daniel Hameed (D)

Department of Orthopaedic Surgery, LifeBridge Health, Sinai Hospital of Baltimore.
The Rubin Institute for Advanced Orthopedics, Baltimore, Maryland.

Nathan Angerett (N)

Department of Orthopaedic Surgery, Orthopaedic Institute of Pennsylvania, Harrisburg, Pennsylvania.

Laura Scholl (L)

Department of Orthopaedic Surgery, Implant and Robotic Research, Stryker, Mahwah, New Jersey.

Michael A Mont (MA)

Department of Orthopaedic Surgery, LifeBridge Health, Sinai Hospital of Baltimore.
The Rubin Institute for Advanced Orthopedics, Baltimore, Maryland.

Classifications MeSH