Related Experiment Video
Updated: Sep 30, 2025
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Paraspinal Muscle in Chronic Low Back Pain: Comparison Between Standard Parameters and Chemical Shift Encoding-Based
Nico Sollmann1,2,3,4, Noah B Bonnheim5, Gabby B Joseph1
1Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Background:
Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding-based water-fat MRI (CSE-MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP.
Purpose:
To investigate associations between PSM parameters from conventional MRI and CSE-MRI and between PSM parameters and pain.
Study Type:
Prospective, cross-sectional.
Population:
Eighty-four adults with chronic LBP (44.6 ± 13.4 years; 48 males).
Field Strength/Sequence:
3-T, T1-weighted fast spin-echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences.
Assessment:
T1-weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle-fat index, CSE-MRI for FF extraction (L1/2-L5/S1). Pain was self-reported using a visual analogue scale (VAS). Intra- and/or interreader agreement was assessed for MRI-derived parameters.
Statistical Tests:
Mixed-effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra- and/or interreader agreement.
Results:
The FF showed excellent intra- and interreader agreement (ICC range: 0.97-0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P-value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores.
Data Conclusion:
In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE-MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP.
Level Of Evidence:
2 TECHNICAL EFFICACY STAGE: 2.
