Analysis on the correlation between paraspinal muscle quality at different levels and spinal pelvic parameters in elderly women with lumbar spinal stenosis

doi:10.3877/cma.j.issn.1673-9450.2025.03.001

Abstract

Abstract:

Objective

To evaluate the correlation between paraspinal muscle cross sectional area，muscle density，and fat fraction at different levels with spinal pelvic parameters in elderly women with lumbar spinal stenosis.

Methods

A retrospective analysis was conducted of the clinical and imaging data of elderly female patients with lumbar spinal stenosis who were hospitalized in the Department of Spine Surgery at Beijing Jishuitan Hospital， Capital Medical University from November 2021 to April 2023.Thoracolumbar kyphosis angle（TLK），lumbar lordosis（LL），sacral slope（SS），pelvic incidence（PI），and pelvic tilt（PT） were measured on preoperative standing lateral lumbar spine X-ray images.The intervertebral disc degeneration and spinal canal stenosis were assessed on MRI images.The paraspinal muscle area（PSMA），muscle density，and fat fraction（FF） at the T12，L3，and L5 levels were measured on quantitative computed tomography（QCT）.Spearman correlation analysis and multiple linear regression models were used to analyze the correlation between paraspinal muscle parameters at different levels and spinal pelvic angles.

Results

A total of 96 elderly women with lumbar spinal stenosis were included，with age of 67.50±4.72 years.Correlation analysis showed significant associations between PSMA，PSMD at T12，L3，and L5 levels，and FF at the L5 level with LL and SS（P＜0.05）.After adjustment for confounding variables，PSMA at the T12 level remained significantly associated with LL and SS（β=-0.740 and 0.529，P＜0.05）.PSMD at the L3 and L5 levels were significantly associated with LL（β=0.608 and 0.494，P＜0.05）.

Conclusion

The study finds that paraspinal muscle cross sectional area， muscle density， and fat fraction are associated with spinopelvic parameters in elderly female patients with lumbar spinal stenosis.Specifically， a decreased PSMA at the T12 level is identified as an independent factor for LL and SS compensation， whereas reduced muscle density at the L3 and L5 levels are independent factors for LL reduction.These findings highlight the need to address the potential risk of sagittal imbalance in patients with reduced thoracolumbar paraspinal muscle mass when diagnosing and treating spinal degenerative diseases.Additionally， in the conservative management of early-stage spinal degeneration，targeted strengthening of the lower lumbar paraspinal muscles and thoracic posterior extensors should be emphasized to help prevent or slow down lumbar curvature regression and the onset of sagittal imbalance.

Key words: Paraspinal muscles, Spinal pelvic parameters, Muscle density, Spinal sagittal imbalance

Wenkai Wu, Fangfang Duan, Ling Wang, Guihe Yang, Chuqi Li, Zhao Lang, Bin Xiao, Da He, Yajun Liu. Analysis on the correlation between paraspinal muscle quality at different levels and spinal pelvic parameters in elderly women with lumbar spinal stenosis[J]. Chinese Journal of Injury Repair and Wound Healing(Electronic Edition), 2025, 20(03): 185-191.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhssyxfzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1673-9450.2025.03.001

https://zhssyxfzz.cma-cmc.com.cn/EN/Y2025/V20/I03/185

Figures/Tables 4

References 34

［1］	Ravindra VM，Senglaub SS，Rattani A， et al.Degenerative lumbar spine disease： estimating global incidence and worldwide volum［eJ］.Global Spine J，2018，8（8）： 784-794.
［2］	Roussouly P， Gollogly S， Berthonnaud E，et al.Classification of the normal variation in the sagittal alignment of the human lumbar spine and pelvis in the standing position［J］.Spine （Phila Pa 1976），2005，30（3）： 346-353.
［3］	Liu C， Ge R， Li H，et al.Thoracolumbar/lumbar degenerative kyphosis-the importance of thoracolumbar junction in sagittal alignment and balance［J］.J Pers Med，2023，14（1）：36.
［4］	海涌，潘爱星.脊柱侧凸诊断与治疗的焦点问题［J］.骨科临床与研究杂志，2021，6（4）：193-196.
［5］	李文强.退行性脊柱侧凸患者矢状位失平衡与椎旁肌退变的相关性研究［D］.汕头大学，2022.
［6］	Meakin JR， Fulford J， Seymour R， et al.The relationship between sagittal curvature and extensor muscle volume in the lumbar spine［J］.J Anat，2013，222（6）：608-614.
［7］	杨起坤.腰椎旁肌退变与脊柱-骨盆参数的相关性研究［D］.南昌大学医学部，2021.
［8］	Li Y， Sun J， Wang G.Lumbar lordosis morphology correlates to pelvic incidence and erector spinae muscularity［J］.Sci Rep，2021， 11（1）：802.
［9］	李雅萍，刘红，黄武杰，等.慢性非特异性腰痛患者腰椎椎旁肌脂肪浸润比与腰椎-骨盆参数的相关性［J］.中国脊柱脊髓杂志，2021，31（9）：825-832.
［10］	Han G， Zhou S， Qiu W， et al.Role of the paraspinal muscles in the sagittal imbalance cascade： the effects of their endurance and of their morphology on sagittal spinopelvic alignmen［tJ］.J Bone Joint Surg Am，2023，105（24）：1954-1961.
［11］	Wáng YXJ， Diacinti D， Yu W， et al.Semi-quantitative grading and extended semi-quantitative grading for osteoporotic vertebral deformity： a radiographic image database for education and calibration［J］.Ann Transl Med，2020，8（6）： 398.
［12］	Shafaq N， Suzuki A， Matsumura A， et al.Asymmetric degeneration of paravertebral muscles in patients with degenerative lumbar scoliosis［J］.Spine（ Phila Pa 1976），2012，37（16）： 1398-1406.
［13］	Mii S， Guntani A， Kawakubo E， et al.Barthel index and outcome of open bypass for critical limb ischemia［J］.Circ J，2017，82（1）：251-257.
［14］	Morishita T， Sato M， Katayama T， et al.Cut-off values for skeletal muscle strength and physical functions in Japanese elderly with walking difficulty［J］.J Med Invest，2021，68（1.2）：48-52.
［15］	Geng J，Wang L，Li Q， et al.The association of lumbar disc herniation with lumbar volumetric bone mineral density in a crosssectional chinese stud［yJ］.Diagnostics（ Basel），2021， 11（6）：938.
［16］	Pfirrmann CW， Metzdorf A， Zanetti M， et al.Magnetic resonance classification of lumbar intervertebral disc degeneration［J］.Spine（Phila Pa 1976），2001，26（17）：1873-1878.
［17］	Schizas C， Theumann N， Burn A， et al.Qualitative grading of severity of lumbar spinal stenosis based on the morphology of the dural sac on magnetic resonance images［J］.Spine（ Phila Pa 1976），2010，35（21）：1919-1924.
［18］	Macagno AE， O'Brien MF.Thoracic and thoracolumbar kyphosis in adults［J］.Spine（Phila Pa 1976），2006，31（19 Suppl）：S161-S170.
［19］	Wang L，Yang M，Ge Y， et al.Muscle size and density are independently associated with death after hip fracture：a prospective cohort study［J］.J Cachexia Sarcopenia Muscle，2023，14（4）：1824-1835.
［20］	Kong M，Geng N，Zhou Y，et al.Defining reference values for low skeletal muscle index at the L3 vertebra level based on computed tomography in healthy adults： a multicentre study［J］.Clin Nutr，2022， 41（2）：396-404.
［21］	Wu W， Duan F， Li K， et al.Reference values for paravertebral muscle size and myosteatosis in Chinese adults， a nationwide multicenter study［J］.Acad Radiol，2024，31（7）：2887-2896.
［22］	王兆瀚，王征，吴兵，等.退行性脊柱侧凸患者椎旁肌退变与脊柱-骨盆参数的关系［J］.中国脊柱脊髓杂志，2019，29（2）：103-108.
［23］	Menezes-Reis R， Bonugli GP， Salmon CEG，et al.Relationship of spinal alignment with muscular volume and fat infiltration of lumbar trunk muscles［J］.PLoS One，2018，13（7）： e0200198.
［24］	王伟炎，夏威威，刘海鹰.退变性脊柱后凸畸形患者腰部肌肉退变与脊柱骨盆参数的相关性分析［J］.中国医药，2021，16（3）：412-416.
［25］	Wang W， Sun Z， Li W，et al.Relationships between paraspinal muscle and spinopelvic sagittal balance in patients with lumbar spinal stenosis［J］.Orthop Surg，2022，14（6）：1093-1099.
［26］	Han G， Zhou S， Wang W， et al.Correlations between paraspinal extensor muscle endurance and clinical outcomes in preoperative LSS patients and clinical value of an endurance classification［J］.J Orthop Translat，2022，35：81-86.
［27］	Bae J， Sathe A， Lee SM，et al.Correlation of paraspinal muscle mass with decompensation of sagittal adult spinal deformity after setting of fatigue post 10-minute walk［J］.Neurospine，2021，18（3）：495-503.
［28］	Ignasiak D， Valenzuela W， Reyes M，et al.The effect of muscle ageing and sarcopenia on spinal segmental loads［J］.Eur Spine J，2018，27（10）： 2650-2659.
［29］	Muellner M， Haffer H， Chiapparelli E， et al.Differences in lumbar paraspinal muscle morphology in patients with sagittal malalignment undergoing posterior lumbar fusion surgery［J］.Eur Spine J，2022，31（11）：3109-3118.
［30］	Umezawa H， Daimon K， Fujiwara H， et al.Changes in crosssectional areas of posterior extensor muscles in thoracic spine： a 10-year longitudinal MRI study［J］.Sci Rep，2022，12（1）：14717.
［31］	Fortin M， Videman T， Gibbons LE，et al.Paraspinal muscle morphology and composition：a 15-yr longitudinal magnetic resonance imaging study［J］.Med Sci Sports Exerc，2014，46（5）：893-901.
［32］	Wang L，Yin L，Zhao Y，et al.Muscle density， but not size，correlates well with muscle strength and physical performance［J］.J Am Med Dir Assoc，2021，22（4）：751-759.e2.
［33］	Kalichman L， Hodges P， Li L，et al.Changes in paraspinal muscles and their association with low back pain and spinal degeneration： CT study［J］.Eur Spine J，2010，19（7）：1136-1144.
［34］	Aas SN，Breit M，Karsrud S， et al.Musculoskeletal adaptations to strength training in frail elderly： a matter of quantity or quality？［J］.J Cachexia Sarcopenia Muscle，2020，11（3）：663-677.

项目	TLK	LL	SS
年龄	0.166	-0.115	-0.181
BMI	0.033	-0.221^*	-0.192
vBMD	-0.226^*	-0.129	-0.031
Pfirrmann分级	0.058	-0.401^**	-0.325^**
Pfirrmann Ⅳ 数量	0.171	-0.340^**	-0.297^**
Schizas分级	0.073	0.001	0.008
椎管狭窄层面数量	-0.018	-0.193	-0.204
T12 PSMA	-0.186	0.128	0.243^*
T12 PSMD	-0.227^*	0.388^**	0.348^**
T12 FF	0.034	-0.152	-0.104
L3 PSMA	-0.133	0.207^*	0.287^**
L3 PSMD	-0.092	0.317^**	0.353^**
L3 FF	0.175	-0.010	-0.130
L5 PSMA	-0.079	0.222^*	0.352^**
L5 PSMD	-0.160	0.366^**	0.419^**
L5 FF	0.194	-0.252^*	-0.431^**
TLK	1	-0.077	-0.240^*
LL	-0.077	1	0.755^**
SS	-0.240^*	0.755^**	1
PI	-0.200	0.556^**	0.678^**
PT	0.111	-0.302^**	-0.358^**

项目	TLK	LL	SS
年龄	0.166	-0.115	-0.181
BMI	0.033	-0.221^*	-0.192
vBMD	-0.226^*	-0.129	-0.031
Pfirrmann分级	0.058	-0.401^**	-0.325^**
Pfirrmann Ⅳ 数量	0.171	-0.340^**	-0.297^**
Schizas分级	0.073	0.001	0.008
椎管狭窄层面数量	-0.018	-0.193	-0.204
T12 PSMA	-0.186	0.128	0.243^*
T12 PSMD	-0.227^*	0.388^**	0.348^**
T12 FF	0.034	-0.152	-0.104
L3 PSMA	-0.133	0.207^*	0.287^**
L3 PSMD	-0.092	0.317^**	0.353^**
L3 FF	0.175	-0.010	-0.130
L5 PSMA	-0.079	0.222^*	0.352^**
L5 PSMD	-0.160	0.366^**	0.419^**
L5 FF	0.194	-0.252^*	-0.431^**
TLK	1	-0.077	-0.240^*
LL	-0.077	1	0.755^**
SS	-0.240^*	0.755^**	1
PI	-0.200	0.556^**	0.678^**
PT	0.111	-0.302^**	-0.358^**

因变量：LL	未标准化系数		标准化系数β	t值	P值	B的95%置信区间		共线性统计
因变量：LL	B	标准误差	标准化系数β	t值	P值	下限	上限	容差	VIF
T12 PSMA	-0.740	0.287	-0.284	-2.58	0.013	-1.317	-0.164	0.365	2.74
T12 PSMD	0.468	0.271	0.26	1.726	0.09	-0.076	1.012	0.195	5.126
T12 FF	-25.746	35.463	-0.102	-0.726	0.471	-96.94	45.448	0.222	4.505
L3 PSMA	-0.068	0.237	-0.031	-0.287	0.775	-0.543	0.407	0.426	2.346
L3 PSMD	0.608	0.273	0.278	2.227	0.03	0.06	1.156	0.314	3.19
L3 FF	99.253	44.414	0.269	2.235	0.03	10.088	188.418	0.338	2.958
L5 PSMA	-0.073	0.306	-0.03	-0.238	0.813	-0.687	0.541	0.318	3.142
L5 PSMD	0.494	0.245	0.253	2.013	0.049	0.001	0.987	0.316	3.166
L5 FF	30.566	21.264	0.233	1.437	0.157	-12.124	73.256	0.191	5.248

因变量：LL	未标准化系数		标准化系数β	t值	P值	B的95%置信区间		共线性统计
因变量：LL	B	标准误差	标准化系数β	t值	P值	下限	上限	容差	VIF
T12 PSMA	-0.740	0.287	-0.284	-2.58	0.013	-1.317	-0.164	0.365	2.74
T12 PSMD	0.468	0.271	0.26	1.726	0.09	-0.076	1.012	0.195	5.126
T12 FF	-25.746	35.463	-0.102	-0.726	0.471	-96.94	45.448	0.222	4.505
L3 PSMA	-0.068	0.237	-0.031	-0.287	0.775	-0.543	0.407	0.426	2.346
L3 PSMD	0.608	0.273	0.278	2.227	0.03	0.06	1.156	0.314	3.19
L3 FF	99.253	44.414	0.269	2.235	0.03	10.088	188.418	0.338	2.958
L5 PSMA	-0.073	0.306	-0.03	-0.238	0.813	-0.687	0.541	0.318	3.142
L5 PSMD	0.494	0.245	0.253	2.013	0.049	0.001	0.987	0.316	3.166
L5 FF	30.566	21.264	0.233	1.437	0.157	-12.124	73.256	0.191	5.248

因变量：SS	未标准化系数		标准化系数β	t值	P值	B的95%置信区间		共线性统计
因变量：SS	B	标准误差	标准化系数β	t值	P值	下限	上限	容差	VIF
T12 PSMA	0.529	0.18	0.278	2.933	0.005	0.167	0.891	0.377	2.65
T12 PSMD	-0.281	0.174	-0.214	-1.616	0.112	-0.63	0.068	0.194	5.161
T12 FF	-11.67	22.721	-0.064	-0.514	0.61	-57.284	33.944	0.221	4.528
L3 PSMA	0.167	0.151	0.104	1.105	0.274	-0.137	0.471	0.436	2.295
L3 PSMD	-0.026	0.185	-0.017	-0.143	0.887	-0.397	0.344	0.286	3.498
L3 FF	-25.988	29.836	-0.097	-0.871	0.388	-85.887	33.911	0.313	3.2
L5 PSMA	0.264	0.189	0.149	1.401	0.167	-0.114	0.643	0.33	3.029
L5 PSMD	-0.077	0.16	-0.054	-0.48	0.634	-0.397	0.244	0.294	3.402
L5 FF	-7.258	13.587	-0.076	-0.534	0.596	-34.535	20.018	0.184	5.43

Please choose a citation manager

Content to export