Association of paraspinal muscle water-fat MRI-based measurements with isometric strength measurements.

OBJECTIVES: Chemical shift encoding-based water-fat MRI derived proton density fat fraction (PDFF) of the paraspinal muscles has been emerging as a surrogate marker in subjects with sarcopenia, lower back pain, injuries and neuromuscular disorders. The present study investigates the performance of paraspinal muscle PDFF and cross-sectional area (CSA) in predicting isometric muscle strength.

METHODS: Twenty-six healthy subjects (57.7% women; age: 30 ± 6 years) underwent 3T axial MRI of the lumbar spine using a six-echo 3D spoiled gradient echo sequence for chemical shift encoding-based water-fat separation. Erector spinae and psoas muscles were segmented bilaterally from L2 level to L5 level to determine CSA and PDFF. Muscle flexion and extension maximum isometric torque values [Nm] at the back were measured with an isokinetic dynamometer.

RESULTS: Significant correlations between CSA and muscle strength measurements were observed for erector spinae muscle CSA (r = 0.40; p = 0.044) and psoas muscle CSA (r = 0.61; p = 0.001) with relative flexion strength. Erector spinae muscle PDFF correlated significantly with relative muscle strength (extension: r = -0.51; p = 0.008; flexion: r = -0.54; p = 0.005). Erector spinae muscle PDFF, but not CSA, remained a statistically significant (p < 0.05) predictor of relative extensor strength in multivariate regression models (R2 adj = 0.34; p = 0.002).

CONCLUSIONS: PDFF measurements improved the prediction of paraspinal muscle strength beyond CSA. Therefore, chemical shift encoding-based water-fat MRI may be used to detect subtle changes in the paraspinal muscle composition.

KEY POINTS: • We investigated the association of paraspinal muscle fat fraction based on chemical shift encoding-based water-fat MRI with isometric strength measurements in healthy subjects. • Erector spinae muscle PDFF correlated significantly with relative muscle strength. • PDFF measurements improved prediction of paraspinal muscle strength beyond CSA.