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. 2022 Dec;22(12):2006-2016.
doi: 10.1016/j.spinee.2022.07.103. Epub 2022 Aug 6.

Paraspinal musculature impairment is associated with spinopelvic and spinal malalignment in patients undergoing lumbar fusion surgery

Affiliations

Paraspinal musculature impairment is associated with spinopelvic and spinal malalignment in patients undergoing lumbar fusion surgery

Maximilian Muellner et al. Spine J. 2022 Dec.

Abstract

Background context: The concept of sagittal spinal malalignment is well established in spinal surgery. However, the effect of musculature on its development has not been fully considered and the position of the pelvis is mostly seen as compensatory and not necessarily a possible cause of sagittal imbalance.

Purpose: This study aimed to investigate the influence of the posterior paraspinal muscles (PPM, erector spinae, and multifidus) and the psoas muscle on spinopelvic and spinal alignment.

Study design/setting: Retrospective cross-sectional study.

Patient sample: Patients undergoing posterior lumbar fusion between 2014 and 2021 for degenerative conditions at a tertiary care center, with preoperative lumbar magnetic resonance imaging (MRI) within 12 months prior the surgery and a preoperative whole spine radiograph were included.

Outcome measures: PPM and psoas muscle measurements including the cross-sectional area (CSA), the functional cross-sectional area (fCSA), the amount of intramuscular fat (FAT), and the percentage of fat infiltration (FI). Spinopelvic measurements including lumbar lordosis (LL), pelvic tilt (PT), sacral slope (SS), pelvic incidence (PI), and sagittal vertical axis (SVA).

Methods: A T2-weighted MRI-based quantitative assessment of the CSA, the fCSA and the amount FAT was conducted, and FI was further calculated. The regions of interest included the psoas muscle and the PPM on both sides at the L4 level that were summarized and normalized by the patient's height (cm2/m2). LL, PT, SS, PI, and SVA were determined on standing lateral radiographs. Spearman correlation was used to calculate the crude relationship between spinopelvic and muscle parameters. Multiple linear regression models with age, sex, LL, PT, SS, and SVA set as independent variables were established to determine the association with spinal muscle outcome measures.

Results: A total of 150 patients (53.3% female) were included in the final analysis with a median age of 65.6 years and a median BMI of 28.2 kg/m2. Significant positive correlations were observed between PT (ρ=0.327), SVA (ρ=0.256) and PI (ρ=0.202) and the FIPPM. Significant negative correlations were detected for the PT and the fCSAPPM (ρ=-0.202) and PT and the fCSAPsoas (ρ=-0.191). Furthermore, a negative correlation was seen for PI and SVA and FIPsoas. PT (β=0.187; p=.006), SVA (β=0.155; p=.035), age (β=0.468; p<.001) and sex (β=0.235; p<.001) significantly predict FIPPM (corrected R2=0.393) as independent variables.

Conclusions: This study demonstrated the potential role of posterior paraspinal muscles and psoas muscle on pelvic retroversion and elucidated the relation to sagittal spinal malalignment. Although we cannot establish causality, we propose that increasing FIPPM, representing loss of muscular strength, may lead to increased pelvic retroversion and thus might be the initiating point for the development of the sagittal imbalance. These findings might challenge the well-known theory of increased pelvic retroversion being a compensatory mechanism for sagittal spinal balance. Thus, muscular weakness might be a factor involved in the development of sagittal spinal malalignment.

Keywords: Aging; Connective tissue; Fat infiltration; Muscle; Muscle quality; Pelvic tilt; Sagittal imbalance; Sagittal vertical axis; Sarcopenia; Spinal fusion; Spine.

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Conflict of interest statement

Declarations of competing interests The Authors declare that there is no conflict of interest regarding this work.

Figures

Fig. 1.
Fig. 1.
Study flow of patient inclusion and exclusion.
Fig. 2.
Fig. 2.
Measurement method of muscle parameters. Image A and B demonstrate the use of the segmentation software. Image B shows in red & green the psoas muscles and in blue and yellow the posterior paraspinal muscles (combined erector spinae and multifidus). Image C and D illustrate the pixel intensity thresholds whereas the green area in the previous segmented areas is interpreted as fat.
Fig. 3.
Fig. 3.
Measurement of the spinopelvic parameters. Fig. A demonstrates the measurement method of the Sacral Slope (SS, °) and Pelvic Incidence (PI, °). Fig. B shows the measurement of the Pelvic Tilt (PT, °) and the Lumbar Lordosis (LL, °). Fig. C illustrates how the C7 sagittal vertical axis (SVA, mm) was obtained.
Fig. 4.
Fig. 4.
Histograms displaying the association between spinopelvic parameters and posterior paraspinal muscle parameters. The left column (A–E) Displays on the x-axis the fat infiltration of the posterior paraspinal muscles. The right column (F–J) Illustrates on the x-axis the functional cross-sectional area (fCSA) of the posterior paraspinal muscles. A and F Pelvic tilt shown on y-axis. B and G Pelvic incidence shown on y-axis. C and H Sacral slope shown on y-axis. D and I Lumbar lordosis shown on y-axis. E and J C7 sagittal vertical axis shown on y-axis.
Fig. 5.
Fig. 5.
Illustration of the pelvis tilted anteriorly through the contraction of the posterior paraspinal muscles (PPM) attached to the sacrum and the ilium. PT= Pelvic Tilt.

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