Validation of a patient-specific finite element analysis framework for identification of growing rod-failure regions in early onset scoliosis patients.

Biomechanics Early onset scoliosis Finite element analysis Growing rods Patient-specific modeling Rod failures

Journal

Spine deformity
ISSN: 2212-1358
Titre abrégé: Spine Deform
Pays: England
ID NLM: 101603979

Informations de publication

Date de publication:
27 Mar 2024
Historique:
received: 01 08 2023
accepted: 14 02 2024
medline: 27 3 2024
pubmed: 27 3 2024
entrez: 27 3 2024
Statut: aheadofprint

Résumé

Growing rods are the gold-standard for treatment of early onset scoliosis (EOS). However, these implanted rods experience frequent fractures, requiring additional surgery. A recent study by the U.S. Food and Drug Administration (FDA) identified four common rod fracture locations. Leveraging this data, Agarwal et al. were able to correlate these fractures to high-stress regions using a novel finite element analysis (FEA) framework for one patient. The current study aims to further validate this framework through FEA modeling extended to multiple patients. Three patient-specific FEA models were developed to match the pre-operative patient data taken from both registry and biplanar radiographs. The surgical procedure was then simulated to match the post-operative deformity. Body weight and flexion bending (1 Nm) loads were then applied and the output stress data on the rods were analyzed. Radiographic data showed fracture locations at the mid-construct, adjacent to the distal and tandem connector across the patients. Stress analysis from the FEA showed these failure locations matched local high-stress regions for all fractures observed. These results qualitatively validate the efficacy of the FEA framework by showing a decent correlation between localized high-stress regions and the actual fracture sites in the patients. This patient-specific, in-silico framework has huge potential to be used as a surgical tool to predict sites prone to fracture in growing rod implants. This prospective information would therefore be vital for surgical planning, besides helping optimize implant design for reducing rod failures.

Identifiants

pubmed: 38536653
doi: 10.1007/s43390-024-00846-7
pii: 10.1007/s43390-024-00846-7
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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Auteurs

Daksh Jayaswal (D)

Department of Bioengineering and Orthopaedic Surgery, Engineering Center for Orthopaedic Research Excellence (E-CORE), University of Toledo, 2801 West Bancroft Street, Toledo, OH, 43606, USA.

Manoj Kodigudla (M)

Department of Bioengineering and Orthopaedic Surgery, Engineering Center for Orthopaedic Research Excellence (E-CORE), University of Toledo, 2801 West Bancroft Street, Toledo, OH, 43606, USA.

Amey Kelkar (A)

Department of Bioengineering and Orthopaedic Surgery, Engineering Center for Orthopaedic Research Excellence (E-CORE), University of Toledo, 2801 West Bancroft Street, Toledo, OH, 43606, USA.

Vijay Goel (V)

Department of Bioengineering and Orthopaedic Surgery, Engineering Center for Orthopaedic Research Excellence (E-CORE), University of Toledo, 2801 West Bancroft Street, Toledo, OH, 43606, USA.

Vivek Palepu (V)

Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Building WO 62-2225, Silver Spring, MD, 20993, USA. vivek.palepu@fda.hhs.gov.

Classifications MeSH