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European Spine Journal

, Volume 27, Issue 10, pp 2442–2448 | Cite as

Population-averaged MRI atlases for automated image processing and assessments of lumbar paraspinal muscles

  • Yiming XiaoEmail author
  • Maryse Fortin
  • Michele C. Battié
  • Hassan Rivaz
Original Article

Abstract

Purpose

Growing evidence suggests an association between lumbar paraspinal muscle degeneration and low back pain (LBP). Currently, time-consuming and laborious manual segmentations of paraspinal muscles are commonly performed on magnetic resonance imaging (MRI) axial scans. Automated image analysis algorithms can mitigate these drawbacks, but they often require individual MRIs to be aligned to a standard “reference” atlas. Such atlases are well established in automated neuroimaging analysis. Our aim was to create atlases of similar nature for automated paraspinal muscle measurements.

Methods

Lumbosacral T2-weighted MRIs were acquired from 117 patients who experienced LBP, stratified by gender and age group (30–39, 40–49, and 50–59 years old). Axial MRI slices of the L4–L5 and L5–S1 levels at mid-disc were obtained and aligned using group-wise linear and nonlinear image registration to produce a set of unbiased population-averaged atlases for lumbar paraspinal muscles.

Results

The resulting atlases represent the averaged morphology and MRI intensity features of the corresponding cohorts. Differences in paraspinal muscle shapes and fat infiltration levels with respect to gender and age can be visually identified from the population-averaged data from both linear and nonlinear registrations.

Conclusion

We constructed a set of population-averaged atlases for developing automated algorithms to help analyze paraspinal muscle morphometry from axial MRI scans. Such an advancement could greatly benefit the fields of paraspinal muscle and LBP research.

Graphical abstract

These slides can be retrieved under Electronic Supplementary Material.

Keywords

Lumbar paraspinal muscles MRI atlas Image processing Measurement Multifidus 

Notes

Acknowledgement

This project was partly funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2015-04136.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

586_2018_5704_MOESM1_ESM.pptx (335 kb)
Supplementary material 1 (PPTX 335 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yiming Xiao
    • 1
    Email author
  • Maryse Fortin
    • 2
  • Michele C. Battié
    • 3
    • 4
  • Hassan Rivaz
    • 2
    • 5
  1. 1.Robarts Research InstituteWestern UniversityLondonCanada
  2. 2.PERFORM CentreConcordia UniversityMontrealCanada
  3. 3.School of Physical TherapyWestern UniversityLondonCanada
  4. 4.Bone and Joint InstituteWestern UniversityLondonCanada
  5. 5.Department of Electrical and Computer EngineeringConcordia UniversityMontrealCanada

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