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Preoperative paraspinal neck muscle characteristics predict early onset adjacent segment degeneration in anterior cervical fusion patients: A machine-learning modeling analysis.

Authors
  • Wong, Arnold Y L1, 2, 3
  • Harada, Garrett1, 2
  • Lee, Remy1, 2
  • Gandhi, Sapan D1, 2
  • Dziedzic, Adam4
  • Espinoza-Orias, Alejandro1, 2
  • Parnianpour, Mohamad5
  • Louie, Philip K1, 2
  • Basques, Bryce1, 2
  • An, Howard S1, 2
  • Samartzis, Dino1, 2
  • 1 Department of Orthopaedic Surgery, Rush University Medical Centre, Chicago, Illinois.
  • 2 Department of Orthopaedic Surgery, International Spine Research and Innovation Initiative, Rush University Medical Centre, Chicago, Illinois.
  • 3 Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR, China. , (China)
  • 4 Department of Computer Science, University of Chicago, Chicago, Illinois.
  • 5 Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran. , (Iran)
Type
Published Article
Journal
Journal of Orthopaedic Research®
Publisher
Wiley (John Wiley & Sons)
Publication Date
Aug 01, 2021
Volume
39
Issue
8
Pages
1732–1744
Identifiers
DOI: 10.1002/jor.24829
PMID: 32816312
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Early onset adjacent segment degeneration (ASD) can be found within six months after anterior cervical discectomy and fusion (ACDF). Deficits in deep paraspinal neck muscles may be related to early onset ASD. This study aimed to determine whether the morphometry of preoperative deep neck muscles (multifidus and semispinalis cervicis) predicted early onset ASD in patients with ACDF. Thirty-two cases of early onset ASD after a two-level ACDF and 30 matched non-ASD cases were identified from a large-scale cohort. The preoperative total cross-sectional area (CSA) of bilateral deep neck muscles and the lean muscle CSAs from C3 to C7 levels were measured manually on T2-weighted magnetic resonance imaging. Paraspinal muscle CSA asymmetry at each level was calculated. A support vector machine (SVM) algorithm was used to identify demographic, radiographic, and/or muscle parameters that predicted proximal/distal ASD development. No significant between-group differences in demographic or preoperative radiographic data were noted (mean age: 52.4 ± 10.9 years). ACDFs comprised C3 to C5 (n = 9), C4 to C6 (n = 20), and C5 to C7 (n = 32) cases. Eighteen, eight, and six patients had proximal, distal, or both ASD, respectively. The SVM model achieved high accuracy (96.7%) and an area under the curve (AUC = 0.97) for predicting early onset ASD. Asymmetry of fat at C5 (coefficient: 0.06), and standardized measures of C7 lean (coefficient: 0.05) and total CSA measures (coefficient: 0.05) were the strongest predictors of early onset ASD. This is the first study to show that preoperative deep neck muscle CSA, composition, and asymmetry at C5 to C7 independently predicted postoperative early onset ASD in patients with ACDF. Paraspinal muscle assessments are recommended to identify high-risk patients for personalized intervention. © 2020 Orthopaedic Research Society. Published by Wiley Periodicals LLC.

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