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Paraspinal Muscle in Chronic Low Back Pain: Comparison Between Standard Parameters and Chemical Shift Encoding‐Based Water–Fat MRI

Published Web Location

https://doi.org/10.1002/jmri.28145
No data is associated with this publication.
Abstract

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.

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