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Evaluating the Reliability of MRI-Derived Biomechanically-Relevant Measures



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  • Personal Author:
  • Description:
    Human geometric dimensions have been estimated and approximated in several ways, most recently using Magnetic Resonance Imaging (MRI) techniques. The reliability of MRI-based measurement of structures has been shown to be relatively high. However, a limitation of reliability evaluations is that they often only compare assessments of the same MRI image (e.g., "slice" of the back); differences are only a function of analyst dexterity (in tracing or measuring the structures). Ideally, a reliability test should compare estimates of biomechanical structures using different scans analyzed by different analysts. This presents a "worst case" scenario and provides a robust test of the process's repeatability. Existing databases of vertebral and intervertebral dimensions tend to be limited with respect to measures of repeatability/reliability with relatively narrow study populations and/or parameters recorded. The objectives of this study were (1) to provide a more accurate data set of lumbar spinal characteristics from 144 Magnetic Resonance Imaging (MRI) scans which were reviewed and measured using the Osirix software program and (2) to assess inter- and intra-rater reliability of the MRI process itself. Reliability for the entire process was evaluated using the aforementioned worst-case scenario of comparing two distinct scans of the same subject with different researchers performing each MRI scan and different researchers performing measurements of the various aspects of vertebral and intervertebral disc dimensions. Geometric dimensions were consistent with measurements obtained in previous MRI-based studies. As expected, larger discrepancies were observed in the "worst case" scenarios (scanners and analysts both different). However, worst case variation was relatively low with 3.6% average absolute difference for anterior endplate measurements, for example, as compared to 2.6% average absolute difference for analysts re-rating their own scans after 1 month. The process for obtaining MRI-derived biomechanical measures appears to be robust. [Description provided by NIOSH]
  • Subjects:
  • Keywords:
  • ISBN:
    9783319960821
  • ISSN:
    2194-5357
  • Publisher:
    Springer
  • Document Type:
    Text
  • Funding:
    Grant
  • Genre:
    Proceedings
  • Place as Subject:
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Topic:
    Workplace Safety & Health
  • Location:
    North America
  • Volume:
    820
  • NIOSHTIC Number:
    nn:20068836
  • Citation:
    Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018): Volume III: Musculoskeletal Disorders, (Advances in Intelligent Systems and Computing). Bagnara S, Tartaglia R, Albolino S, Alexander T, Fujita Y, eds. Cham, Switzerland: Springer, 2018 Aug; 820:742-749
  • Contact Point Address:
    Menekse Salar Barim, Oak Ridge Institute for Science and Education (ORISE) Research Fellow, Cincinnati, OH, 45202, USA
  • Email:
    mzs0053@auburn.edu
  • Editor(s):
    Bagnara S; Tartaglia R; Albolino S; Alexander T; Fujita Y
  • Federal Fiscal Year:
    2018
  • Performing Organization:
    University of Alabama at Birmingham
  • Peer Reviewed:
    False
  • Start Date:
    20050701
  • Source Full Name:
    Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018): Volume III: Musculoskeletal Disorders, (Advances in Intelligent Systems and Computing)
  • End Date:
    20270630
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:d20438c7f9e28e6b1d3e1f4cafdbb7e9dafa7f1681bd59b034dc7c647fbe5a2f34017e0d14ac19a94b47a5ee521f0c9b2d31cea65f33c2cca05a07a7fe7d5fc7
  • Download URL:
  • File Type:
    Filetype[PDF - 6.59 MB ]
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