Effect of Paravertebral Muscle Degeneration on Lumbar and Pelvic Sagittal Alignment in Patients With Degenerative Scoliosis

Abstract

Study Design

Retrospective study.

Objectives

To explore the relationship between lumbar spine muscle mass and lumbar pelvic sagittal parameters in patients with degenerative scoliosis.

Methods

This study included ADS patients who were treated in our hospital from 2019 to 2023. The spinal parameters were evaluated through X-rays, and the relative muscle volume (RMV) and fat infiltration (FI) were measured through three-dimensional reconstruction. Patients were categorized into 3 groups based on SRS-Schwab sagittal balance correction (0, +, ++), and into 3 groups based on GAP score (proportioned, moderately dis-proportioned, severely dis-proportioned). Finally, patients were classified into low-quality and high-quality groups based on the FI of Paraspinal muscles (PSM).

Results

The study included a total of 63 patients. Significant statistical differences were observed in the FI and RMV of MF, ES and PS among patients classified by SRS-Schwab PT classification. Additionally, significant statistical differences were found in the RMV of MF and PS among patients classified by SRS-Schwab PI-LL classification and GAP score. Furthermore, a significant correlation was found between the FI and RMV of PSM and lumbopelvic sagittal parameters. The ordinal regression model analysis revealed that FI of ES significantly impacted PT imbalance, while RMV of MF significantly impacted PI-LL imbalance. Moreover, significant differences were noted in PT and PI between the low-quality and high-quality multifidus groups.

Conclusions

As sagittal imbalance worsens, PSM degeneration also intensifies, primarily characterized by an increase in FI and a decrease in RMV. Notably, PT and PI-LL are positively correlated with RMV and negatively correlated with FI.

Keywords

adult degenerative scoliosis paraspinal muscles fat infiltration rate relative muscle volumes sagittal imbalance lumbopelvic parameters

Introduction

Adult degenerative scoliosis (ADS) is a severe disease affecting the spine, characterized by a three-dimensional deformity that includes coronal and sagittal deformities. Over recent years, the incidence of degenerative scoliosis has been steadily increasing, leading to significant physical and mental health issues for patients.¹ While the exact mechanisms behind the development of degenerative scoliosis are still under investigation, factors such as disc degeneration, facet joint degeneration, vertebral mass changes, and degenerative alterations in paraspinal muscles (PSM) are known to play key roles in spinal misalignment.² Recent studies have found that PSM degeneration plays an important role in the progression of ADS patients.

The PSM, including the psoas (PS), erector spinae (ES), and multifidus (MF).³ Some research suggests that retrovertebral muscle tissue is crucial for maintaining spinal balance in patients with deformities. Previous studies have observed that PSM cross-sectional FI in ADS patients is related to coronal plane imbalance, sagittal plane imbalance and postoperative complications. Among them, PSM degeneration is closely related to sagittal imbalance. Nevertheless, there remains some debate regarding the connection between lumbopelvic sagittal parameters and the FI of PSM.

The balance between the lumbar and pelvic sequences is crucial for maintaining body balance.^4,5 Kyphotic deformity in the thoracolumbar segment is a common occurrence, often leading to pelvic retroversion and active extension of kyphosis in adjacent segments as compensatory mechanisms.^6,7 This segment compensation primarily occurs when there is adequate mobility and muscle strength. Therefore, the PSM, including the MF and ES in the lumbar region, plays a significant role in maintaining the sagittal alignment of the spine.⁸ Evaluating spinal sagittal-pelvic parameters can offer novel treatment approaches for spinal conditions.⁹

Recent studies have indicated a notable connection between cross-sectional area (CSA) of the MF and sagittal spinal alignment in individuals with degenerative lumbar scoliosis (DLS).¹⁰ Additionally, research has demonstrated that in patients with adult spinal deformity (ASD), fat infiltration (FI) of the L3 PSM is linked to posterior pelvic tilt (PT). The severity of sagittal modifiers in SRS-Schwab for PT modifiers was found to increase with the degree of FI in L3, although this trend was not observed for pelvic-incidence lumbar lordosis mismatch (PI-LL).¹¹ Conversely, a separate study found no significant correlation between the CSA of the MF, ES, and PS and posterior PT in patients with degenerative spinal kyphosis (DSK).¹² To address the existing debate, further investigation is required to elucidate the associations between lumbopelvic parameters and PSM. Previous studies have primarily utilized cross-sectional measurements to assess PSM. In contrast, our study employs semi-automated software to quantify the volume of PSM. This innovative approach has the potential to enhance our understanding of the correlation between PSM and lumbopelvic sagittal parameters. The SRS-Schwab sagittal classification and GAP score are significant tools in classifying sagittal alignment.^13,14 In our study, we utilized the SRS-Schwab sagittal classification and GAP classification to categorize patients and examine the alterations in their paraspinal muscles. The objective of this study was to investigate the connection between the Relative Muscle volumes (RMV) and Fat infiltration (FI) of PSM and lumbopelvic sagittal plane parameters.

Methods

Patient Selection

This retrospective study analyzed data from 63 ADS patients in a single-center database between January 2019 and June 2023. A total of 98 patients were included, of which 35 patients were excluded. Inclusion criteria included patients over 50 years old at the time of surgery,^15,16 complete preoperative and postoperative data. The Cobb angle (CA) of the curved coronal plane of the lumbar spine in the anteroposterior and posterior position is greater than 10°. Exclusion criteria comprised adolescents with scoliosis, patients with sarcopenia, previous spinal surgery, spinal tumors, and spinal infections. The study was approved by the institutional review board.

Demographic Data Collection

Demographic data including age, gender, height, weight, body mass index (BMI).

Muscle Measurement Method

The patient’s T12 to S2 data was collected using CT imaging. The patient’s CT data was imported into the imaging histology software 3D Slicer, which can be downloaded from https://mipav.cit.nih.gov/free. Using the plug-in, the patient’s muscle area was manually outlined layer by layer (Figure 1), leading to the 3D modeling of the patient’s muscles (Figure 2). Subsequently, the patient’s MV, effective muscle volume (EMV), and FI were calculated. This software enables rapid and precise analysis of the patient’s muscle data.^17,18 The MV was adjusted afterward for the patients’ BMI.¹⁹ Two experienced spine surgeons conducted the measurements, and the final measurements were averaged after 3 repetitions of each sample.

Figure 1.

Measurements of paraspinal muscular parameters on CT. A: multifidus; B: erector spinae; C: psoas;A + B: multifidus and erector spinae.

Figure 2.

Use 3D Slicer to build a 3D model of single-segment lumbar muscles.

The calculation formulas for FI and RMV are as follows:

FI = 1-EMV/MV

RMV = MV/BMI

Radiographic Measurements

Standing full spine anteroposterior and lateral X-rays were utilized to assess the patient’s spinal parameters, including sagittal parameters such as pelvic incidence (PI), lumpar lordosis (LL), PT, sacral slope (SS), and PI-LL.²⁰ All radiological parameters were measured 3 times. Two experienced spine surgeons conducted the measurements, and the final measurements were averaged after 3 repetitions of each sample.

Patients Classification

After enrollment, the patients were divided into 3 levels based on imaging parameters based on SRS-Schwab sagittal balance correction (PI-LL, PT).

Patients were divided into 3 groups according to GAP score.

Patients were categorized into a low-quality group and a high-quality group based on the average value of PSM FI. Individuals with values below the average were placed in the high-quality group, while those with values above the average were placed in the low-quality group.

Statistical Analysis

All data were assessed for normality using the Shapiro-Wilk test. A comparison between the two groups was conducted using the independent samples t test. Correlations between muscle measurements and other parameters were analyzed using the Pearson correlation test. The SRS-Schwab sagittal classification and GAP score grouping were compared using an Analysis of Variance (ANOVA) test and post hoc analysis (Tukey test). Risk factors for PI-LL and PT were analyzed using an ordinal regression model. P value of less than 0.05 was considered statistically significant. Data analysis was performed using SPSS software (Version 26.0; SPSS, Chicago, IL, USA).

Results

Patient Statistics

A total of 63 ADS patients (40 females, 23 males) with an average age of 64.27 ± 6.19 years and an average BMI of 25.56 ± 3.80 kg/m2 were included in the study. Radiological parameters can be found in Table 1.

Table 1.

Patient Demographics.

Radiographic parameters	Mean ± SD
LL (°)	29.06 ± 15.40
PI-LL (°)	20.62 ± 16.18
SS(°)	27.35 ± 11.47
PT (°)	22.05 ± 9.30
PI(°)	49.68 ± 10.79
Fat infiltration percentages
MF(%)	18.71 ± 7.17
ES (%)	20.90 ± 8.30
PS(%)	16.46 ± 7.04
Relative muscle volumes
MF(cm3)	7.33 ± 2.16
ES (cm3)	17.65 ± 6.14
PS(cm3)	9.51 ± 3.11

LL:lumpar lordosis;PI-LL: pelvic-incidence lumbar lordosis mismatch; SS:sacral slope;PT:pelvic tilt;PI:pelvic incidence;MF: multifidus; ES: erector spinae; PS: psoas.

Comparison of FI and RMV Between SRS-Schwab Sagittal Classification Groups

Within each SRS-Schwab PT sagittal plane modifier group, the FI of PSM showed a significant increase in MF (P < 0.001) and ES (P < 0.001) with worsening sagittal imbalance. However, there was no significant difference observed in PS. In terms of the RMV of PSM, there was a significant decrease in the RMV of MF (P = 0.010), ES (P = 0.004), and PS (P = 0.001) as the severity of sagittal imbalance increased, with statistically significant findings. (Table 2)

Table 2.

Fat Infiltration and Relative Muscle Volumes by SRS-Schwab PT Modifier.

Parameters	0	+	++	P value
Parameters	0	+	++	0 vs + vs ++	0 vs +	0 vs ++	+ vs ++
FI
MF	15.58 ± 5.20	18.58 ± 7.06	25.87 ± 6.37	<0.001	0.092	<0.001	0.001
ES	16.62 ± 6.39	21.49 ± 6.74	29.50 ± 7.72	<0.001	0.015	<0.001	0.001
PS	14.59 ± 7.22	18.09 ± 6.48	17.96 ± 6.99	0.153	0.083	0.151	0.958
RMV
MF	8.16 ± 2.08	6.86 ± 1.78	6.20 ± 2.27	0.010	0.029	0.005	0.363
ES	20.19 ± 6.85	16.49 ± 4.24	13.87 ± 4.68	0.004	0.027	0.001	0.195
PS	10.98 ± 2.70	8.19 ± 2.20	8.36 ± 3.87	0.001	0.001	0.007	0.862

MF: multifidus; ES: erector spinae; PS: psoas.FI: Fat Infiltration;RMV: Relative Muscle volumes.

Among the SRS-Schwab PI-LL sagittal plane modifier groups, no significant difference was found for the FI of PSM. In terms of the RMV of PSM, the RMV of MF (P = 0.003) and PS (P = 0.002) decreased as sagittal imbalance severity increased, while no significant difference was observed for the ES. (Table 3)

Table 3.

Fat Infiltration and Relative Muscle Volumes by SRS-Schwab PI-LL Modifier.

Parameters	0	+	++	P value
Parameters	0	+	++	0 vs + vs ++	0 vs +	0 vs ++	+ vs ++
FI
MF	16.85 ± 5.65	18.55 ± 6.98	20.23 ± 8.23	0.321	0.461	0.135	0.435
ES	20.47 ± 9.13	20.12 ± 8.10	21.91 ± 8.07	0.749	0.898	0.582	0.477
PS	14.98 ± 7.36	16.73 ± 7.12	17.32 ± 6.85	0.560	0.446	0.293	0.779
RMV
MF	8.59 ± 2.12	7.33 ± 2.06	6.37 ± 1.82	0.003	0.052	0.001	0.111
ES	20.15 ± 6.33	17.06 ± 6.00	16.30 ± 5.80	0.114	0.116	0.045	0.674
PS	11.60 ± 2.92	8.79 ± 3.24	8.57 ± 2.41	0.002	0.003	0.001	0.796

MF: multifidus; ES: erector spinae; PS: psoas;FI: Fat Infiltration;RMV: Relative Muscle volumes.

Comparison of FI and RMV Among Various Groups of GAP Score

In the GAP Score, there was no significant difference observed for the FI of PSM. However, the RMV of MF showed a significant decrease (P < 0.001) along with PS (P = 0.049) as the severity of sagittal imbalance increased. Conversely, there was no significant difference found in ES. (Table 4)

Table 4.

Fat Infiltration and Relative Muscle Volumes by GAP Score.

Parameters	A	B	C	P value
Parameters	A	B	C	A vs B vs C	A vs B	A vs C	B vs C
FI
MF	16.04 ± 3.59	16.75 ± 4.81	19.68 ± 7.98	0.287	0.858	0.333	0.167
ES	20.39 ± 2.50	18.76 ± 8.05	21.74 ± 8.69	0.473	0.727	0.757	0.226
PS	10.79 ± 6.31	18.59 ± 8.06	16.19 ± 6.50	0.127	0.048	0.140	0.241
RMV
MF	10.32 ± 2.16	8.34 ± 1.61	6.67 ± 1.98	<0.001	0.068	0.001	0.004
ES	17.62 ± 5.92	19.08 ± 6.30	17.13 ± 6.16	0.561	0.673	0.880	0.284
PS	12.06 ± 3.68	10.5 ± 2.74	8.91 ± 3.04	0.049	0.356	0.049	0.076

MF: multifidus; ES: erector spinae; PS: psoas; FI: Fat Infiltration; RMV: Relative Muscle volumes; A:Proportioned;B: Moderately dis-proportioned; C:Severely dis-proportioned.

Correlation Between FI and RMV of PSM and Sagittal Parameters

In the correlation analysis, the FI of MF showed a positive correlation with PI-LL (P = 0.027), PT (P < 0.001), and PI (P = 0.003). The FI of ES was also positively correlated with PT (P < 0.001) and PI (P = 0.009). Additionally, the FI of PS demonstrated a positive correlation with PI-LL (P = 0.009). (Table 5)

Table 5.

Correlation Between FI and RMV of PSM and Sagittal Parameters.

Preop Parameter	Fat Infiltration			Relative Muscle volumes
Preop Parameter	MF	ES	PS	MF	ES	PS
LL
R	−0.038	0.102	−0.204	0.324*	0.096	0.295*
P value	0.766	0.427	0.109	0.010	0.453	0.019
PI-LL
R	0.278*	0.122	0.325**	−0.526**	−0.321*	−0.412**
P value	0.027	0.339	0.009	<0.001	0.010	0.001
SS
R	−0.056	0.043	−0.010	0.174	−0.020	0.041
P value	0.662	0.739	0.936	0.173	0.879	0.752
PT
R	0.498**	0.442**	0.167	−0.456**	−0.444**	−0.374**
P value	<0.001	<0.001	0.191	<0.001	<0.001	0.003
PI
R	0.363**	0.329**	0.195	−0.326**	−0.344**	−0.197
P value	0.003	0.009	0.125	0.009	0.006	0.122

LL:lumpar lordosis;PI-LL: pelvic-incidence lumbar lordosis mismatch; SS:sacral slope;PT:pelvic tilt;PI:pelvic incidence;MF: multifidus; ES: erector spinae; PS: psoas;R Pearson correlation coefficient. *. At the 0.05 level, the correlation was significant, **. At the 0.01 level, the correlation was significant.

The research findings indicate a positive correlation between the RMV of MF, ES, and PS with PI-LL (P < 0.001, P = 0.010, P = 0.001) and PT (P < 0.001, P < 0.001, P = 0.003). Additionally, LL shows a positive correlation with RMV of MF and PS (P = 0.010, P = 0.019), while PI is correlated with RMV of MF and ES (P = 0.009, P = 0.006). (Table 5).

Ordinal Regression Model Analysis

The results of the ordinal regression model analysis demonstrated a significant impact of the FI of ES on PT imbalance (OR = 1.1368, P = 0.008). (Table 6) Specifically, an increase in the FI of ES was associated with a gradual increase in PT imbalance. Furthermore, the study found that the RMV of MF had a significant impact on PI-LL imbalance (OR = 0.9997, P = 0.035). (Table 7) In this case, a decrease in the RMV of MF correlated with a gradual increase in PI-LL imbalance.

Table 6.

Ordinal Regression Analysis of PT.

	Univariate Analysis
Variables	OR	Lower95%	Upper95%	P-value
MF RMV	0.9999	−0.0004	0.0003	0.688
ES RMV	1.0000	−0.0001	0.0001	0.951
PS RMV	0.9998	−0.0005	0.0001	0.134
MF FI	1.0623	−0.0468	0.1676	0.269
ES FI	1.1368	0.0333	0.2232	0.008

Fat Infiltration; RMV: Relative Muscle volumes.

Table 7.

Ordinal Regression Analysis of PI-LL.

	Univariate Analysis
Variables	OR	Lower95%	Upper95%	P-value
MF RMV	0.9997	−0.0006	0.0000	0.035
PS RMV	0.9999	−0.0003	0.0001	0.160

Fat Infiltration; RMV: Relative Muscle volumes.

Effect of Muscle Mass on Sagittal Parameters

In terms of MF, the group with higher quality had lower PT (18.77 ± 6.64 vs 25.22 ± 10.45, P = 0.005) and PI (46.77 ± 7.59 vs 52.50 ± 12.67, P = 0.034). In terms of PS, the high-quality group exhibited significantly lower PI-LL values compared to the low-quality group (15.15 ± 16.61 vs 26.63 ± 13.55, P = 0.004). However, here were no significant differences observed in other parameters among the MF, ES, and PS groups. (Table 8)

Table 8.

Comparison of Imaging Parameters Among Muscle Groups.

Preop Parameter	LL	PI-LL	SS	PT	PI
MF
High quality	29.55 ± 13.59	17.23 ± 12.40	28.00 ± 10.67	18.77 ± 6.64	46.77 ± 7.59
Poor quality	28.59 ± 17.18	23.91 ± 18.76	26.72 ± 12.33	25.22 ± 10.45	52.50 ± 12.67
P value	0.807	0.102	0.661	0.005	0.034
ES
High quality	28.61 ± 13.08	19.78 ± 14.11	27.11 ± 8.69	20.08 ± 7.16	48.39 ± 7.84
Poor quality	29.67 ± 18.29	21.74 ± 18.81	27.67 ± 14.55	24.67 ± 11.16	51.41 ± 13.77
P value	0.790	0.651	0.851	0.052	0.275
PS
High quality	32.21 ± 15.63	15.15 ± 16.61	27.88 ± 11.45	20.76 ± 9.54	47.36 ± 10.56
Poor quality	25.60 ± 14.63	26.63 ± 13.55	26.77 ± 11.66	23.47 ± 8.97	52.23 ± 10.63
P value	0.088	0.004	0.704	0.250	0.074

LL:lumpar lordosis;PI-LL: pelvic-incidence lumbar lordosis mismatch; SS:sacral slope;PT:pelvic tilt;PI:pelvic incidence.

Discussion

ADS, a severe degenerative disease of the spine, is often associated with coronal and sagittal imbalances. The primary curve in ADS patients typically occurs in the lumbar region, making lumbopelvic parameters essential for maintaining body balance. The role of PSM in sagittal balance in patients with ADS has been increasingly recognized. Han et al ²¹ suggest that PSM degeneration is not only a contributing factor to posterior PT, but also a potential risk factor for the transition from the compensation phase to the decompensation phase. Elysee et al ¹¹ found that global sagittal malalignment was linked to FI of lumbar and thoracic PSM in individuals with ASD. Han et al ²² showed that the role of the lower lumbar PSM may be mainly focused on maintaining local alignment rather than global alignment. However, these studies were limited to assessment of muscle cross-sections in patients. Compared with previous methods that only measured the cross-sectional area of the PSM, our measurement of RMV can better reflect the muscle. To avoid individual differences among patients, we used BMI-modified RMV. However, it is still unclear whether the RMV and FI of PSM are related to the pelvic sagittal parameters. To further explore this issue, we divided patients into SRS-Schwab groups based on their PT and PI-LL.

In our study of patients with ADS, we observed that as the degree of sagittal imbalance increased in the PT classification, the FI of the MF and ES gradually increased, while the RMV of ES and PS decreased. These findings are in line with previous research by Elysee et al,¹¹ who reported a similar increase in FI of PS at the L3 level with sagittal imbalance. Additionally, in the PI-LL classification, we noted a decrease in RMV of the MF and PS with increasing imbalance, showing significant statistical differences. Although the FI of the imbalanced group was higher than the balanced group, this difference was not statistically significant. Furthermore, our analysis of the GAP score revealed no significant difference in FI of the PSM, but a gradual decrease in RMV of the MF and PS with increasing imbalance, supporting our PI-LL classification results and reinforcing our research finding. Therefore, we think patients with severe muscle degeneration may struggle to maintain a normal PT, requiring an effective compensatory mechanism to prevent sagittal imbalance. As the patient’s compensatory mechanism weakens, the patient’s LL also decreases. This leads to a further increase in PT as the patient tries to uphold proper posture. Ultimately, if the compensatory mechanism fails, sagittal imbalance will manifest.

There is an interactive relationship between PSM fatty degeneration and spinal imbalance. We observed that the FI and RMV of PSM are associated with various lumbar and pelvic parameters. Specifically, the FI of the MF and PS correlates with PI-LL, while the FI of the MF and ES correlates with PT. Our findings align with prior research, such as the study by Elysee et al,¹¹ which demonstrated a relationship between lumbar PSM’s FI and sagittal imbalance parameters. This reinforces the connection between PSM FI and sagittal malalignment. Furthermore, we discovered a significant negative correlation between the RMV of PSM and PI-LL as well as PT. A smaller muscle volume may limit the patient’s ability to adapt to changes in bony structures, potentially leading to poor sagittal alignment. These results support our conclusion.

An ordinal regression model was utilized to investigate the impact of PSM on local sagittal imbalance. The experimental data were fed into the model, revealing that the FI of the ES significantly influenced PT imbalance, while the relative volume of the MF had a notable effect on PI-LL imbalance. Han et al. ²² identified MF relative gross cross-sectional area (rGCSA) as an independent factor for LL loss. Guo et al²³ highlighted that a higher average degree of MF degeneration poses a significant risk for PI-LL mismatch. Lee et al.²⁴ suggested that volume reduction in the lumbar PSM and increased FI in the PSM could contribute to spinopelvic deformities. Furthermore, Menezes-Reis²⁵ reported a substantial correlation between spinopelvic parameters and lumbar PSM volume, further supporting our findings.

Our study confirmed the important relationship between PT and PI-LL and PSM. Muellner et al and Hiyama et al.^26,27 reported concordant results, finding that paraspinal extensor and flexor muscle parameters were significantly correlated with PT. To further investigate this protective effect, patients were categorized into high-quality muscle group and low-quality group based on the relationship between FI and mean. Our study revealed that PI and PT values were significantly higher in the low-quality MF group compared to the high-quality group. Our results further confirm the relationship between PSM and PT.

This study is limited by its single-center design and small sample size. Additionally, Our study focused on examining the correlation between RMV, FI, and lumbopelvic parameters. However, we were unable to establish a causal relationship between muscle degeneration and sagittal imbalance in our research. Furthermore, while our measurement method can assess muscle volume, there may be inaccuracies due to human factors, preventing a completely accurate three-dimensional muscle model reconstruction. In the future, we believe that our point of view can be further verified by increasing the intervention of paravertebral muscles.

Conclusion

This study demonstrates a notable association between PSM degeneration and sagittal parameters. As sagittal imbalance worsens, PSM degeneration also intensifies, primarily characterized by an increase in FI and a decrease in RMV. Notably, PT and PI-LL have an important relationship with lumbar spinal muscle degeneration.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Tianjin Union Medical Center (2022JZXK05, 2022JZXK02, 2023YJZD002, 2022JZXK06), Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-064B).

Ethical Statement

ORCID iDs

Linyan Liu

Rusen Zhu

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