Changes of Water and Muscle Content in Paraspinal Muscle Degeneration and Gender Differences During Aging Using Dual-Energy CT

Changes of Water and Muscle Content in Paraspinal Muscle Degeneration and Gender Differences During Aging Using Dual-Energy CT | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Changes of Water and Muscle Content in Paraspinal Muscle Degeneration and Gender Differences During Aging Using Dual-Energy CT Muqing Luo, Huiting Deng, Menqtian Ma, Yinqi Liu, Zeya Zhong, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6237350/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jun, 2025 Read the published version in European Spine Journal → Version 1 posted 11 You are reading this latest preprint version Abstract Objectives To quantitatively assess paraspinal muscle degeneration and gender-related differences during aging in adults using rapid kVp switching dual-energy computed tomography (DECT). Methods A total of 156 healthy adults underwent lumbar DECT scans and were prospectively grouped into young (20–39 years), middle-aged (40–59 years), and elderly (60–79 years) groups. Muscle density (MD), cross-sectional area (CSA), muscle content (MC), and water content (WC) were measured using muscle-water decomposition images for the bilateral erector spinae (ES) at the L1/2 to L4/5 levels and bilateral multifidus (MF) and psoas (PS) at the L2/3 to L5/S1 levels. Results Across age groups, significant differences in paraspinal muscle MD and WC were observed ( P < 0.01), with MD negatively and WC positively correlated with age at lower lumbar levels for both MF and ES ( P < 0.001). In females, except for the L5/S1 PS, WC differences between the middle-aged and elderly groups were significant (P 0.05). In males, multifidus MC at L4/5 decreased with age ( P < 0.05), while in females, multifidus MC at L3/4 and L5/S1 was higher in the middle-aged group and lowest in the elderly group ( P < 0.05). PS CSA at L4/5-L5/S1 showed a moderate negative correlation with age ( P < 0.001). Conclusions The muscle-water decomposition technique using rapid kVp switching DECT provides a noninvasive quantitative assessment of paraspinal muscle degeneration by evaluating changes in muscle and water content, potentially reflecting alterations in the extracellular matrix. This method highlights age- and gender-related differences, aiding in the differentiation between physiological aging and pathological degeneration. Paraspinal muscle Dual-energy computed tomography Aging material decomposition Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The paraspinal muscles play a pivotal role in maintaining spinal stability, and their structural and functional changes are closely associated with overall back health[ 1 , 2 ]. As individuals age, degeneration of the paraspinal muscles significantly increases the risk of vertebral compression fractures, spondylolisthesis, and lumbar disc disease, thereby adversely affecting the quality of life in the elderly population[ 3 , 4 ]. Consequently, a comprehensive assessment of the paraspinal muscles, coupled with the early identification of their physiological changes, is essential for understanding back health in older adults. This understanding is critical for developing effective preventive strategies and guiding appropriate treatment interventions. Muscle imaging evaluation has attracted growing interest in musculoskeletal research, with current imaging methods primarily focused on measuring muscle mass and muscle quality[ 5 ]. However, the relationship between paraspinal muscle mass/quality and aging still remains inconclusive due to the complex nature of muscle aging. Traditional computed tomography (CT) evaluates muscle mass by measuring cross-sectional area (CSA) and assesses muscle quality through CT values (muscle density, MD)[ 6 , 7 ]. However, their measuring accuracy may be interfered by the presence of other components with similar CT values. On the other hand, current radiological studies on muscle physiology primarily focus on assessing fat content within muscles, using techniques such as quantitative computed tomography (QCT) and quantitative magnetic resonance imaging (qMRI)[ 8 – 11 ]. Extensive research has established fat infiltration as a key biomarker of muscle degeneration during aging[ 12 , 13 ]. However, beyond fat infiltration, muscle tissue is also highly water-rich, and changes in water content may impact both muscle quality and function[ 14 ]. Preliminary studies have shown a correlation between paraspinal muscle water content and chronic nonspecific low back pain[ 15 ], but the patterns of water content and associated factors such as muscle inflammation, edema, and fibrotic necrosis in the context of normal paraspinal muscle aging and degeneration remain unexplored. Fast kilovolt peak (kVp) switching dual-energy computed tomography (DECT) with Gemstone Spectral Imaging (GSI) enables precise quantification of a diverse array of materials by utilizing basis material paired images[ 16 ]. The basis material pairs are reconstructed from the two components contained within the mixture, with the attenuation curve corresponding to the specific material's absorption characteristics across varying X-ray energies having been established by physicists[ 17 ]. This capability allows for the quantification of materials such as calcium, hydroxyapatite, iron, uric acid, fat, and water, which has been reported to enhance clinical diagnosis and inform decision-making in the musculoskeletal and endocrine domains[ 15 , 17 – 20 ]. Additionally, DECT offers several advantages over magnetic resonance imaging (MRI), including a reduced risk of contraindications, significantly shorter scan times, and lower costs. Nevertheless, research on the application of DECT for the assessment of paraspinal muscle degeneration, particularly concerning muscle and water-related changes associated with normal aging, remains limited. This study employs DECT muscle-water basis pair images to quantitatively analyze muscle and water content changes in the lumbar paraspinal muscles of healthy individuals across different age groups. The goal is to provide a comprehensive, non-invasive, and objective basis for studying age-related lumbar degenerations. Materials and Methods Participants From August 2021 to February 2023, 156 healthy individuals were prospectively enrolled and underwent prospective lumbar DECT imaging. Inclusion criteria were: (1) healthy adults aged 20–79 years with a normal body mass index (18.5–24.9 kg/m²); (2) absence of any history of low back pain. Exclusion criteria included: (1) history of lumbar trauma or surgery; (2) presence of spinal deformities, lumbar infections, tumors, or tumor-like lesions; (3) history of using medications affecting muscle metabolism or alcohol abuse; (4) presence of muscular system diseases, renal insufficiency, cardiovascular disease, diabetes, neurological deficits, or other systemic diseases; (5) incomplete imaging data or poor image quality. Ultimately, a total of 125 participants were included in this study: 40 in the young group, 42 in the middle-aged group, and 43 in the elderly group. An additional 31 participants were excluded due to incomplete imaging data or the detection of spinal infections, lumbar tumors, or other abnormalities, or poor image quality due to motion artifacts. Figure 1 details the inclusion and exclusion process. This prospective study received approval from the Medical Ethics Committee of the XXX, and all participants provided informed consent before undergoing the examination. DECT Scanning Protocol DECT imaging was performed using a Revolution CT scanner (GE HealthCare, Milwaukee, WI, USA) in GSI mode. Subjects were positioned supine. The scanning range extended from the 12th thoracic vertebra to the 1st sacral vertebra. Scanning parameters were: tube voltage of 80/140 kV, tube current of 230 mA, collimation width of 0.625 mm, pitch of 0.984:1, gantry rotation speed of 0.8 s/r, and CT dose index (CTDIvol) of 9.09 mGy. Standard kernel was utilized with a 30% weight of Adaptive Statistical Iterative Reconstruction-V (ASiR-V30%) to reconstruct images. Image Post-Processing Image data were analyzed using Advantage Workstation 4.6 (GE Medical Healthcare, Milwaukee, WI, USA) and processed with GSI volume viewer software to obtain virtual monoenergetic 70keV images (70keV VMI), muscle-water and water-muscle basis pair images. The regions of interest (ROIs) were positioned in the multifidus (MF), erector spinae (ES), and psoas (PS) muscles bilaterally, avoiding surrounding fat, vertebrae, and subcutaneous fat (Fig. 2 ). Firstly, ROIs were manually delineated on 70 keV monochromatic axial images at the L1/2 to L4/5 intervertebral disc levels for ES and L2/3 to L5/S1 intervertebral disc levels for MF and PS, and the CT value was recorded as muscle density (MD, HU), the ROI area was regarded as CSA. Then ROIs were cloned to the water-muscle images and muscle-water images to obtain water content (WC, mg cm − 3 ) and muscle content (MC, mg cm − 3 ), respectively. Two experienced radiologists independently performed these measurements three times for each side, and the mean values were calculated. Statistical Analysis Statistical analysis was performed using SPSS 22.0 software. Data normality was assessed with the Kolmogorov-Smirnov test for continuous data. The Kolmogorov-Smirnov test was used to evaluate the normality of continuous variables. Data following a normal distribution are expressed as mean ± standard deviation, while non-normally distributed data are reported as median (interquartile range). The differences in paraspinal muscle parameters among young (20–39 years), middle-aged (40–59 years), and elderly (60–79 years) groups were analyzed using one-way ANOVA for normally distributed data and Kruskal-Wallis H test for non-normally distributed data. For pairwise comparisons, the Bonferroni method was applied. Categorical variables were presented as frequencies and assessed using the χ² test. Spearman correlation analysis was employed to examine the association between paraspinal muscle parameters and age. A P-value of less than 0.05 was considered statistically significant. Results Clinical Characteristics A total of 125 healthy adults (61 males, 64 females), aged 20–79 years (median 50 years), were included in the study. The participants were divided into three age groups: young (20–39 years, median 29.5, 20 males and 20 females), middle-aged (40–59 years, median 49.5, 20 males and 22 females), and elderly (60–79 years, median 68, 21 males and 22 females). There were no significant differences in baseline characteristics among the groups ( P > 0.05) (Table 1 ). Table 1 Comparison of general clinical data of the subjects Characteristics Young group (n = 40) Middle group(n = 42) Old group (n = 43) P Age (years) 30.40 ± 5.00 50.10 ± 5.13 70.07 ± 8.65 < 0.001 Gender (Male/Female) 20/20 20/22 21/22 0.978 Height (cm) 163.45 ± 7.77 162.33 ± 8.21 163.44 ± 7.99 0.764 Weight (kg) 59.60 ± 8.30 61.16 ± 9.10 60.23 ± 11.64 0.770 BMI (kg/m 2 ) 22.34 ± 2.94 23.14 ± 2.21 22.56 ± 4.10 0.505 Note: The values are given as frequencies or means ± standard deviation. BMI, Body mass index. Comparison of Paraspinal Muscle Parameters Across Age Groups Significant differences were observed in MD across age groups (all P 0.05), MD differences were statistically significant across groups (all P < 0.05). Differences in CSA were significant only for the ES at the L4/5 level, the MF at the L5/S1 level, and the PS at the L4/5 to L5/S1 levels ( P < 0.05). WC differences were significant across age groups (all P < 0.01), showing an increasing trend with aging. The WC of the MF at the L4/5 to L5/S1 levels and the ES at the L4/5 level were significantly different between groups ( P < 0.01). MC differences were statistically significant across age groups only for the MF at the L2/3 to L5/S1 levels (all P < 0.05) (Table 2 – 3 , Fig. 3). Table 2 Comparison of paraspinal muscles parameters at different levels among three age groups Parameters Muscle Level Young group Middle group Old group P MD ES L1/2 56.13(53.35, 59.24) ** 51.30(48.65, 54.43) ### 43.08(33.20, 50.29) §§§ ＜ 0.001 L2/3 55.40(52.61, 58.89) ** 50.70(46.45, 54.65) ### 39.12(29.31, 46.61) §§§ ＜ 0.001 L3/4 54.48(50.39, 58.21) ** 48.75(44.53, 52.05) ### 35.40(22.79, 45.73) §§§ ＜ 0.001 L4/5 50.33(47.79, 53.90) *** 38.85(26.35, 46.13) ### 11.57(-8.86, 28.94) §§§ ＜ 0.001 CSA MF PS ES MF PS L2/3 L3/4 L4/5 L5/S1 L2/3 L3/4 L4/5 L5/S1 L1/2 L2/3 L3/4 L4/5 L2/3 L3/4 L4/5 L5/S1 L2/3 L3/4 L4/5 L5/S1 57.30(54.01, 59.88) * 56.53(50.96, 60.38) * 54.60(51.70, 59.84) ** 54.08(49.58, 57.18) ** 56.38(54.38, 58.39) ** 55.78(54.28, 57.88) *** 56.05(45.34, 58.78) * 57.00(55.36, 59.20) ** 1205.50(1024.73, 1551.50) 1224.75(1091.83, 1569.40) 1114.83(845.11,1452.25) 770.18(633.99, 914.41) 202.30(154.05, 239.81) 324.25(276.61, 406.46) 548.40(434.54, 639.61) 484.98(389.78, 555.99) 368.28(257.70, 584.25) 670.08(458.38, 900.20) 866.90(638.66, 1207.29) * 816.55(578.85, 1058.18) * 53.00 (46.88, 56.80) ### 51.40(48.55, 55.23) ### 46.85(35.85, 52.53) ### 35.70(26.33, 50.60) ### 54.13(51.20, 55.96) ### 51.73(49.56, 54.76) ## 53.48(51.93, 56.46) ## 54.05(51.70, 56.08) ## 1267.70(1085.69,1487.41) 1301.05(1187.66, 1522.66) 1096.70(910.53, 1305.04) 694.23(556.90, 818.23) # 162.00(134.53, 202.15) 286.40(239.38, 359.68) 590.80(450.53, 734.20) 522.95(433.30, 608.95) # 312.70(217.94, 485.69) 540.80(421.60, 734.39) 680.55(532.65, 944.76) 601.25(455.04, 826.41) 37.20(24.53, 45.63) §§§ 37.70(25.24, 45.10) §§§ 24.65(11.59, 33.85) §§§ 9.25(-11.08, 20.23) §§§ 45.55(39.70, 52.25) §§§ 45.70(39.15, 51.25) §§§ 49.75(44.30, 52.95) §§§ 49.05(43.85, 52.55) §§§ 1172.55(950.50, 1399.00) 1290.65(1024.90,1596.00) 1088.10(952.85, 1288.40) 844.95(636.60, 966.60) 165.58(139.05, 219.11) 312.33(262.76, 396.65) 622.15(528.05, 720.25) 600.05(494.81, 736.33) §§§ 294.45(239.30, 521.65) 522.85(413.50, 817.75) 621.75(511.45, 897.10) §§ 561.85(466.80, 773.35) §§ ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 0.576 0.622 0.990 0.026 0.063 0.164 0.107 ＜ 0.000 0.165 0.112 0.004 0.003 Note: The values are given as median (interquartile range) or means ± standard deviation. ES, erector spinae; MF, multifidus; PS, psoas muscle；MD, mean density; CSA, cross sectional area. * Young group vs. Middle Group, # Middle group vs. Old group, § Young group vs. Old group. *, #, § p < 0.05; **, ##, §§ p < 0.01; ***, ###, §§§ p < 0.001. Table 3 Comparison of paraspinal muscles parameters at different levels among three age groups Parameters Muscle Level Young group Middle group Old group P MC ES L1/2 1069.00±254.10 1107.5±279.17 1135.90±326.10 0.574 L2/3 1069.03±258.04 1099.57±321.033 1092.30±335.70 0.876 L3/4 1072.21±324.73 1093.12±256.06 1064.42±399.49 0.078 L4/5 1019.90±340.26 907.47±3305.23 844.83±404.42 0.919 WC MF PS ES MF L2/3 L3/4 L4/5 L5/S1 L2/3 L3/4 L4/5 L5/S1 L1/2 L2/3 L3/4 L4/5 L2/3 L3/4 L4/5 L5/S1 1288.95±284.88 1358.52±344.17 1189.40±283.40 1346.84±332.32 1575.90±304.95 1440.35±339.14 1411.27±311.35 1705.63±291.81 411.73(297.20, 486.28) 422.48(304.88, 559.20) * 480.98(309.83, 592.63) * 592.33(428.63, 822.01) ** 347.33(238.69, 510.51) 363.65(225.69, 571.99) 422.60(233.81, 688.39) ** 462.68(330.84, 602.40) ** 1366.97±355.01 # 1403.95±355.79 ## 1124.32±287.95 # 1343.33±337.14 ## 1700.45±309.11 1426.33±292.43 1558.72±265.05 1807.01±287.68 502.15(353.63, 598.35) ### 524.50(382.43, 724.16) ### 551.45(473.13, 771.03) ### 929.60(718.25, 1321.55) ### 403.25(244.45, 624.83) ### 420.80(283.88, 608.70) ### 775.28(537.03, 1067.09) ### 945.00(550.55, 1262.95) ### 1182.07±378.66 1194.89±387.95 § 991.43±346.01 §§ 1086.79±403.36 §§ 1623.82±410.70 1430.46±418.42 1544.35±405.27 1767.88±384.02 833.05(484.48, 1055.19) §§§ 905.10(640.91 1269.65) §§§ 1104.00(614.78, 1397.13) §§§ 1756.50(1283.75, 2122.25) §§§ 990.73(670.23, 1388.88) §§§ 1002.34(590.29, 1448.25) §§§ 1409.50(1118.00, 1776.50) §§§ 1614.00(1355.38, 2042.45) §§§ 0.048 0.023 0.013 0.001 0.262 0.983 0.093 0.368 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 PS L2/3 L3/4 L4/5 L5/S1 106.42(-70.36, 187.63) 193.98(112.02, 266.74) 171.81(69.65, 275.03) 142.40(12.56, 265.61) 117.94(0.08, 240.00) ### 270.15(158.38, 402.98) ## 166.84(43.24, 286.78) ## 204.13(53.55, 339.18) ## 349.85(178.15, 605.60) §§§ 469.75(275.20, 658.70) §§§ 341.05(143.20, 592.60) §§ 408.95(178.67, 564.60) §§§ ＜ 0.001 ＜ 0.001 ＜ 0.001 ＜ 0.001 Note: The values are given as median (interquartile range) or means ± standard deviation. ES, erector spinae; MF, multifidus; PS, psoas muscle；WC, water content; MC, muscle content. * Young group vs. Middle group, # Middle group vs. Old group, § Young group vs. Old group. *, #, § p < 0.05; **, ##, §§ p < 0.01; ***, ###, §§§ p < 0.001. Comparison of Paraspinal Muscle Parameters in Male Subjects Across Age Groups In male subjects, MD differences were significant across age groups (all P < 0.01), with a decreasing trend from young to elderly. WC differences were significant across age groups (all P < 0.01), showing an increasing trend except for the PS at the L3/4 level. MC differences were significant only for the MF at the L4/5 level between the young and elderly groups ( P < 0.05). CSA differences were significant only for the MF at the L2/3 and L5/S1 levels and the PS at the L4/5 to L5/S1 levels ( P < 0.05) (Fig. 4 ). Comparison of Paraspinal Muscle Parameters in Female Subjects Across Age Groups In female subjects, MD differences were significant across age groups (all P < 0.01), with a decreasing trend from young to elderly. WC differences were significant across age groups (all P < 0.01), showing an increasing trend except for the PS at the L2/3, L4/5, and L5/S1 levels and the MF at the L3/4 level. WC differences between the middle-aged and elderly groups were significant for all intervertebral disc levels except for the PS at the L5/S1 level ( P < 0.05). MC differences were significant for the MF at the L3/4 and L5/S1 levels between the middle-aged and elderly groups ( P < 0.05), with higher WC in the middle-aged group. CSA differences were significant for the MF at the L4/5 to L5/S1 levels, the PS at the L4/5 to L5/S1 levels, and the PS at the L1/2 to L2/3 levels (all P < 0.05) (Fig. 5 ). Correlation Between Paraspinal Muscle Parameters and Age The MD of the paraspinal muscles was negatively correlated with age across all levels (all P < 0.05), with the higher correlations for the MF at the L4/5 and L5/S1 levels and the ES at the L4/5 level (r = -0.823, -0.830, -0.833, respectively; P < 0.001). The WC of the paraspinal muscles was positively correlated with age across all levels (all P < 0.05), with the higher correlations for the MF at the L4/5 and L5/S1 levels and the ES at the L4/5 level (r = 0.809, 0.817, 0.783, respectively; P < 0.001). The CSA of the PS at the L4/5 to L5/S1 levels showed a moderate correlation with age (r = -0.490, -0.531, respectively; P < 0.001) (Fig. 6). In male subjects, the MD of the MF at L4/5 and L5/S1, and the ES at L4/5, showed strong negative correlations with age (r = -0.828 to -0.865, P < 0.001), while the WC at these levels had strong positive correlations (r = 0.813 to 0.872, P < 0.001). Similarly, in females, the MD of the MF at L4/5 and L5/S1, and the ES at L4/5, exhibited strong negative correlations with age (r = -0.793 to -0.812, P < 0.001), and the WC at these levels had strong positive correlations (r = 0.784 to 0.826, P < 0.001) (Figure S1 -2). Discussion Currently, the non-invasive imaging evidences for water and muscle content changes in paraspinal muscles with aging and the gender-specific differences are still insufficient. Our findings based on DECT measurements demonstrate a significant decrease in the MD of the paraspinal muscles with advancing age, accompanied by an increase in WC, particularly noted in the MF and ES muscles of the lower lumbar spine. Notably, in males, the increase in WC is more pronounced with age, while in females, this trend becomes significant primarily from middle age onward. Moreover, in males, the MC of the lower lumbar MF shows a decline with age; conversely, in females, MC is observed to be higher in the middle-aged cohort and lowest in the elderly group. These age- and gender-specific parameters are not only essential for developing personalized rehabilitation strategies but also enhance the non-invasive detection of pathological degeneration. By comparing pathological states against age-specific baseline values, these findings provide valuable insights for clinical diagnosis and treatment, paving the way for more tailored interventions in both male and female patients across different age groups. CT values (Hounsfield units, HU) are important for assessing muscle density, reflecting muscle performance and physical function[ 13 ]. Previous research has demonstrated a strong correlation between the decline in paraspinal muscle CT values and increased muscle fat content[ 21 ]. Our study corroborates this by demonstrating a decreasing trend in paraspinal muscle MD with age, indicating increased muscle fat infiltration and decreased muscle function, consistent with Orwoll ES's findings[ 22 ]. The consistency and low variability of CT measurements make it an effective tool for assessing changes in muscle fat content, especially in monitoring sarcopenia and myosteatosis[ 21 , 23 ]. However, CT values represent the average density of various intramuscular components, which alone cannot provide a detailed analysis of the physiological composition changes in paraspinal muscles. DECT basis material pair images provides detailed, high-contrast quantitative images by analyzing the characteristic attenuation curve of specific material in projection domain [ 24 ]. This technique could be facilely used to track content changes (mg cm − 3 ) of specific component. Studies suggest that the balance between intracellular and extracellular water content is key in evaluating muscle aging, with intracellular water (ICW) content closely related to muscle mass, strength, and function[ 14 , 25 ]. Using DECT muscle-water basis material paired technology, our results show an increasing trend in paraspinal muscle WC with age, indicating an increase in water content in muscle interstitial spaces with aging. This finding is supported by a cross-sectional study on adult body composition, which found an increasing ratio of extracellular water (ECW) to ICW with age[ 25 ]. The expansion of the extracellular space and increased ECW content may be due to reduced muscle cell number, reduced function of central body fluid regulation, and diminished kidney concentration ability, leading to a transfer of muscle cell water to the interstitial spaces[ 26 , 27 ]. Additionally, decreased muscle repair capacity with aging may lead to inflammation and edema, increasing extracellular water content[ 28 ]. Thus, changes in paraspinal muscle WC based on muscle-water decomposition images may serve as biomarkers for evaluating muscle aging and degeneration. Furthermore, the study found that changes in paraspinal muscle WC were more pronounced in males, while in females, this change was significant only at older ages. This may be related to the protective effect of estrogen on muscle mass and strength by mediating various estrogen receptors, which contribute to its anti-inflammatory effects, promotion of muscle cell proliferation, and inhibition of muscle atrophy. [ 29 – 31 ]. Moreover, studies show that aquaporins are essential for maintaining intracellular water and muscle function in skeletal muscle[ 32 ]. Sex hormones, including estrogen, regulate aquaporins, and postmenopausal estrogen loss disrupts this regulation, leading to imbalanced intracellular water and accelerated muscle decline[ 33 ]. This finding highlights the importance of exercise plans and nutritional advice for postmenopausal women to slow muscle aging and degeneration, thus improving the quality of life in elderly women. The study also shows that the MC of the lower lumbar MF decreases with age in males, while in females, it is higher in the middle-aged group and lowest in the elderly group, which had not been reported before. This gender difference may be due to various factors, including physiology, hormone levels, lifestyle, and physical activity levels[ 31 , 34 ]. This finding further underscores the importance of gender-specific considerations in developing personalized rehabilitation strategies. Additionally, only the MC of the MF at the lower lumbar levels showed significant changes across age groups, possibly due to the greater stress these muscles endure in spine movement and stability, making them more prone to degeneration[ 35 ]. Therefore, measuring the MC of the lower lumbar MF may better reflect changes in muscle fiber quantity during aging, aiding in early identification and intervention of muscle function changes. The impact of age on the CSA of most paraspinal muscles was not significant, likely because total CSA represents the entire muscle area within the fascia, which can be replaced by adipose tissue as muscle content decreases, resulting in no significant change in total CSA[ 36 ]. However, the CSA of the lower-level PS decreased significantly with age, suggesting that the CSA of the psoas muscle, being a low-fat muscle[ 37 ], may more accurately reflect changes in muscle fiber quantity during aging. Notably, the high correlations between age and the WD and WC of MF and ES at the lower lumbar levels indicate that paraspinal muscles in these areas are more prone to atrophy and degeneration, leading to reduced muscle function. This may be due to the greater mechanical load that the ES and MF at lower lumbar levels endure during spinal movements, making them more susceptible to degeneration with aging[ 38 , 39 ]. Therefore, it is essential to focus on the functional recovery and strengthening of the MF and ES, using specific training methods such as suspension core training. Limitations This study has several limitations. First, the sample size across different age groups was relatively small, introducing potential selection bias. Larger sample sizes are required to further explore the underlying mechanisms of age-related changes in muscle composition and their relationship with muscle function. Second, unmeasured or residual confounding factors, such as exercise or dietary habits, may exist. Third, the selection of ROI is subjective, and this study only extracted paraspinal muscles at the intervertebral disc level for analysis. Future research could employ automatic segmentation technology to perform comprehensive studies on paraspinal muscles. Conclusion DECT material separation with rapid kVp switching effectively quantifies age-related physiological changes in paraspinal muscles. Notably, paraspinal muscle water content, as measured through muscle-water separation, shows significant age- and gender-dependent differences. This method supports personalized prevention and intervention strategies for age- and gender-related musculoskeletal diseases and provides valuable clinical references for distinguishing pathological degeneration. Declarations Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Muqing Luo, Huiting Deng, Zeya Zhong, Jianyu Li and Yinqi Liu. The first draft of the manuscript was written by Muqing Luo and all authors commented on previous versions of the manuscript. Revision and final version of the manuscript were written by Mengtian Ma and Kun Zhang. All authors read and approved the final manuscript. Acknowledgement We would like to express our sincere appreciation to Dr. Suping Chen from GE HealthCare for her invaluable technical guidance and support during the manuscript revision process, which significantly contributed to the success of this study. References Wesselink EO, Pool-Goudzwaard A, De Leener B, Law CSW, Fenyo MB, Ello GM, Coppieters MW, Elliott JM, Mackey S, Weber KA, 2nd (2024) Investigating the associations between lumbar paraspinal muscle health and age, BMI, sex, physical activity, and back pain using an automated computer-vision model: A UK Biobank study. Spine J. doi: 10.1016/j.spinee.2024.02.013 Chen X, Cui P, Li Y, Wang Y, Lu S (2024) Links among MRI features in paraspinal muscles, inflammatory processes, and related back pain in patients with lumbar disc herniation. JOR Spine 7:e1310. doi: 10.1002/jsp2.1310 Huang YL, Zhou JL, Jiang YM, Zhang ZG, Zhao W, Han D, He B (2020) Assessment of lumbar paraspinal muscle activation using fMRI BOLD imaging and T2 mapping. Quant Imaging Med Surg 10:106-115. doi: 10.21037/qims.2019.10.20 Seyedhoseinpoor T, Taghipour M, Dadgoo M, Sanjari MA, Takamjani IE, Kazemnejad A, Khoshamooz Y, Hides J (2022) Alteration of lumbar muscle morphology and composition in relation to low back pain: a systematic review and meta-analysis. Spine J 22:660-676. doi: 10.1016/j.spinee.2021.10.018 Engelke K, Chaudry O, Gast L, Eldib MA, Wang L, Laredo JD, Schett G, Nagel AM (2023) Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translat 42:57-72. doi: 10.1016/j.jot.2023.07.005 Urakawa H, Sato K, Vaishnav AS, Lee R, Chaudhary C, Mok JK, Virk S, Sheha E, Katsuura Y, Kaito T, Gang CH, Qureshi SA (2023) Preoperative cross-sectional area of psoas muscle correlates with short-term functional outcomes after posterior lumbar surgery. Eur Spine J 32:2326-2335. doi: 10.1007/s00586-023-07533-7 Amini B, Boyle SP, Boutin RD, Lenchik L (2019) Approaches to Assessment of Muscle Mass and Myosteatosis on Computed Tomography: A Systematic Review. J Gerontol A Biol Sci Med Sci 74:1671-1678. doi: 10.1093/gerona/glz034 Peng X, Li X, Xu Z, Wang L, Cai W, Yang S, Liao W, Cheng X (2020) Age-related fatty infiltration of lumbar paraspinal muscles: a normative reference database study in 516 Chinese females. Quant Imaging Med Surg 10:1590-1601. doi: 10.21037/qims-19-835 Krkoska P, Kokosova V, Dostal M, Vlazna D, Kerkovsky M, Straka M, Gerstberger R, Matulova K, Ovesna P, Adamova B (2024) Assessment of lumbar paraspinal muscle morphology using mDixon Quant magnetic resonance imaging (MRI): a cross-sectional study in healthy subjects. Quant Imaging Med Surg 14:6015-6035. doi: 10.21037/qims-23-1796 Gao Y, Jiang H, Gao R, Zhou X (2024) Evaluation of lumbar paraspinal muscles degeneration and fatty infiltration in dynamic sagittal imbalance based on magnetic resonance imaging. Eur Spine J 33:1840-1849. doi: 10.1007/s00586-023-08033-4 Eck BL, Yang M, Elias JJ, Winalski CS, Altahawi F, Subhas N, Li X (2023) Quantitative MRI for Evaluation of Musculoskeletal Disease: Cartilage and Muscle Composition, Joint Inflammation, and Biomechanics in Osteoarthritis. Invest Radiol 58:60-75. doi: 10.1097/RLI.0000000000000909 Marcus RL, Addison O, Kidde JP, Dibble LE, Lastayo PC (2010) Skeletal muscle fat infiltration: impact of age, inactivity, and exercise. J Nutr Health Aging 14:362-366. doi: 10.1007/s12603-010-0081-2 Lee SH, Park SW, Kim YB, Nam TK, Lee YS (2017) The fatty degeneration of lumbar paraspinal muscles on computed tomography scan according to age and disc level. Spine J 17:81-87. doi: 10.1016/j.spinee.2016.08.001 Serra-Prat M, Lorenzo I, Palomera E, Yebenes JC, Campins L, Cabre M (2019) Intracellular Water Content in Lean Mass is Associated with Muscle Strength, Functional Capacity, and Frailty in Community-Dwelling Elderly Individuals. A Cross-Sectional Study. Nutrients 11. doi: 10.3390/nu11030661 Zhou X, Liu Y, Chen S, Xiang J, Li J, Li J, You T, Zhong Z, Zhang K (2024) Increased water content in multifidus muscles of young adults with chronic nonspecific low back pain detected by dual-energy CT and MRI. Eur J Radiol 176:111515. doi: 10.1016/j.ejrad.2024.111515 Goo HW, Goo JM (2017) Dual-Energy CT: New Horizon in Medical Imaging. Korean J Radiol 18:555-569. doi: 10.3348/kjr.2017.18.4.555 Molwitz I, Leiderer M, McDonough R, Fischer R, Ozga AK, Ozden C, Tahir E, Koehler D, Adam G, Yamamura J (2021) Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging. Eur Radiol 31:7529-7539. doi: 10.1007/s00330-021-07820-1 Li B, Hua N, Li J, Andreu-Arasa VC, LeBedis C, Anderson SW (2023) Quantification of spinal bone marrow fat fraction using three-material decomposition technique on dual-energy CT: A phantom study. Med Phys 50:4105-4111. doi: 10.1002/mp.16442 Sullivan J, Pillinger MH, Toprover M (2021) Chondrocalcinosis: Advances in Diagnostic Imaging. Curr Rheumatol Rep 23:77. doi: 10.1007/s11926-021-01044-4 Borges AP, Antunes C, Caseiro-Alves F (2023) Spectral CT: Current Liver Applications. Diagnostics (Basel) 13. doi: 10.3390/diagnostics13101673 Engelke K, Museyko O, Wang L, Laredo JD (2018) Quantitative analysis of skeletal muscle by computed tomography imaging-State of the art. J Orthop Translat 15:91-103. doi: 10.1016/j.jot.2018.10.004 Orwoll ES, Blackwell T, Cummings SR, Cauley JA, Lane NE, Hoffman AR, Burghardt AJ, Evans WJ, Cawthon PM (2022) CT Muscle Density, D3Cr Muscle Mass, and Body Fat Associations With Physical Performance, Mobility Outcomes, and Mortality Risk in Older Men. J Gerontol A Biol Sci Med Sci 77:790-799. doi: 10.1093/gerona/glab266 Feng Z, Rong P, Luo M, Sun X, Wang W (2019) Influence of Methods Used to Establish Sarcopenia Cutoff Values for Skeletal Muscle Measures Using Unenhanced and Contrast-Enhanced Computed Tomography Images. JPEN J Parenter Enteral Nutr 43:1028-1036. doi: 10.1002/jpen.1519 Siegel MJ, Bhalla S, Cullinane M (2021) Dual-Energy CT Material Decomposition in Pediatric Thoracic Oncology. Radiol Imaging Cancer 3:e200097. doi: 10.1148/rycan.2021200097 Ohashi Y, Joki N, Yamazaki K, Kawamura T, Tai R, Oguchi H, Yuasa R, Sakai K (2018) Changes in the fluid volume balance between intra- and extracellular water in a sample of Japanese adults aged 15-88 yr old: a cross-sectional study. Am J Physiol Renal Physiol 314:F614-F622. doi: 10.1152/ajprenal.00477.2017 Kerch G (2018) Distribution of tightly and loosely bound water in biological macromolecules and age-related diseases. Int J Biol Macromol 118:1310-1318. doi: 10.1016/j.ijbiomac.2018.06.187 Lorenzo I, Serra-Prat M, Yebenes JC (2019) The Role of Water Homeostasis in Muscle Function and Frailty: A Review. Nutrients 11. doi: 10.3390/nu11081857 Frontera WR, Ochala J (2015) Skeletal muscle: a brief review of structure and function. Calcif Tissue Int 96:183-195. doi: 10.1007/s00223-014-9915-y Yoh K, Ikeda K, Horie K, Inoue S (2023) Roles of Estrogen, Estrogen Receptors, and Estrogen-Related Receptors in Skeletal Muscle: Regulation of Mitochondrial Function. Int J Mol Sci 24. doi: 10.3390/ijms24031853 Pellegrino A, Tiidus PM, Vandenboom R (2022) Mechanisms of Estrogen Influence on Skeletal Muscle: Mass, Regeneration, and Mitochondrial Function. Sports Med 52:2853-2869. doi: 10.1007/s40279-022-01733-9 Ko SH, Jung Y (2021) Energy Metabolism Changes and Dysregulated Lipid Metabolism in Postmenopausal Women. Nutrients 13. doi: 10.3390/nu13124556 Aslesh T, Al-Aghbari A, Yokota T (2023) Assessing the Role of Aquaporin 4 in Skeletal Muscle Function. Int J Mol Sci 24. doi: 10.3390/ijms24021489 Khan S, Ricciardelli C, Yool AJ (2021) Targeting Aquaporins in Novel Therapies for Male and Female Breast and Reproductive Cancers. Cells 10. doi: 10.3390/cells10020215 Critchlow AJ, Hiam D, Williams R, Scott D, Lamon S (2023) The role of estrogen in female skeletal muscle aging: A systematic review. Maturitas 178:107844. doi: 10.1016/j.maturitas.2023.107844 Pinto SM, Cheung JPY, Samartzis D, Karppinen J, Zheng YP, Pang MYC, Wong AYL (2022) Are Morphometric and Biomechanical Characteristics of Lumbar Multifidus Related to Pain Intensity or Disability in People With Chronic Low Back Pain After Considering Psychological Factors or Insomnia? Front Psychiatry 13:809891. doi: 10.3389/fpsyt.2022.809891 Kalichman L, Carmeli E, Been E (2017) The Association between Imaging Parameters of the Paraspinal Muscles, Spinal Degeneration, and Low Back Pain. Biomed Res Int 2017:2562957. doi: 10.1155/2017/2562957 Muellner M, Chiapparelli E, Moser M, Haffer H, Dodo Y, Adl Amini D, Carrino JA, Tan ET, Shue J, Zhu J, Sama AA, Cammisa FP, Girardi FP, Hughes AP (2022) The effect of age on psoas and paraspinal muscle morphology in patients undergoing posterior lumbar fusion surgery. Eur Spine J 31:2619-2628. doi: 10.1007/s00586-022-07346-0 Xia W, Fu H, Zhu Z, Liu C, Wang K, Xu S, Liu H (2019) Association between back muscle degeneration and spinal-pelvic parameters in patients with degenerative spinal kyphosis. BMC Musculoskelet Disord 20:454. doi: 10.1186/s12891-019-2837-0 Moser M, Adl Amini D, Jones C, Zhu J, Okano I, Oezel L, Chiapparelli E, Tan ET, Shue J, Sama AA, Cammisa FP, Girardi FP, Hughes AP (2023) The predictive value of psoas and paraspinal muscle parameters measured on MRI for severe cage subsidence after standalone lateral lumbar interbody fusion. Spine J 23:42-53. doi: 10.1016/j.spinee.2022.03.009 Additional Declarations No competing interests reported. Supplementary Files supportinginformation.docx Cite Share Download PDF Status: Published Journal Publication published 05 Jun, 2025 Read the published version in European Spine Journal → Version 1 posted Editorial decision: Revision requested 22 Apr, 2025 Reviews received at journal 20 Apr, 2025 Reviews received at journal 13 Apr, 2025 Reviewers agreed at journal 12 Apr, 2025 Reviews received at journal 09 Apr, 2025 Reviewers agreed at journal 06 Apr, 2025 Reviewers agreed at journal 04 Apr, 2025 Reviewers invited by journal 19 Mar, 2025 Editor assigned by journal 18 Mar, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 16 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6237350","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431055084,"identity":"726e79d6-c979-4b52-8bdd-daed1296e82b","order_by":0,"name":"Muqing Luo","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Muqing","middleName":"","lastName":"Luo","suffix":""},{"id":431055086,"identity":"f36296f1-3d98-4c70-8176-3718abe85f63","order_by":1,"name":"Huiting Deng","email":"","orcid":"","institution":"Longhua District Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huiting","middleName":"","lastName":"Deng","suffix":""},{"id":431055087,"identity":"468ddfd5-59a9-4a08-8856-c160739549c4","order_by":2,"name":"Menqtian Ma","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Menqtian","middleName":"","lastName":"Ma","suffix":""},{"id":431055089,"identity":"1d98c593-1834-41cd-bdee-3c8e05747388","order_by":3,"name":"Yinqi Liu","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yinqi","middleName":"","lastName":"Liu","suffix":""},{"id":431055092,"identity":"c3505041-0149-432c-aef4-622db4a459f4","order_by":4,"name":"Zeya Zhong","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zeya","middleName":"","lastName":"Zhong","suffix":""},{"id":431055093,"identity":"77042663-255a-4556-891a-5003c17f5f33","order_by":5,"name":"Jianyu Li","email":"","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jianyu","middleName":"","lastName":"Li","suffix":""},{"id":431055096,"identity":"c7307630-7db6-4a04-bc3f-cd3009a163d5","order_by":6,"name":"Kun Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYBACCRDB2AAkmBkbDnyokJCTJ14Le3PjwxlnLIwNG4jWwnO82Zi3rSKR4QABLZIzcg8w/txhlycfkdgmwTtPIoGxgfnhoxt4tEhL5CUwSJ5JLja8AdQiuU0ij52Bzdg4B48WOYkcAwbDNubEjTOAWgy3SRQzNvCwSRPUkthWD9GSOEciseEAAS3SIC0H2w4nzuc52GxwsIEILZI9bwwYG9uOJ25gb2x82HBMwtiwmYBfJI7nGDD+bKtOnN/M/uDwn5o6OXn25oeP8WkBAvYfINLgAIzPjF85Asg3EKtyFIyCUTAKRhwAALnITYA0QaHaAAAAAElFTkSuQmCC","orcid":"","institution":"The First Hospital of Hunan University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Kun","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-03-16 11:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6237350/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6237350/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00586-025-08968-w","type":"published","date":"2025-06-05T15:57:56+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79573232,"identity":"e7881e2c-71c3-4c4e-b6a1-3d13a257836a","added_by":"auto","created_at":"2025-03-31 11:04:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63160,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of participant selection for the study\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/170e1344cdb75f0618d09e0c.jpg"},{"id":79573233,"identity":"0800c71a-fc3b-495a-85c6-962dca2f5ac3","added_by":"auto","created_at":"2025-03-31 11:04:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39263,"visible":true,"origin":"","legend":"\u003cp\u003eRegion of interest delineation for lumbar paraspinal muscles on DECT 70 keV VMIs map at the L4/5 lumbar intervertebral level. ES, erector spinae; MF, multifidus; PS, psoas muscle.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/f00bd7ef47e5fb24f06ff2a0.jpg"},{"id":79573240,"identity":"03c5e742-321b-4767-929f-0507c5928c5d","added_by":"auto","created_at":"2025-03-31 11:04:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":164674,"visible":true,"origin":"","legend":"\u003cp\u003eDECT 70 keV VMIs maps (A, D, G), DECT water(muscle) decomposition maps (B, E, H) and DECT muscle(water) decomposition maps (C, F, I) at the L4/5 lumbar intervertebral level among different groups. (A-C) a 25-year-old healthy male. (D-F) a 56-year-old healthy female. (G-I) a 76-year-old healthy male.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/b3dd1597484733aadfbf8377.jpg"},{"id":79576413,"identity":"0ccecf16-0d3d-43cf-b3c3-ef73cfe1ac4c","added_by":"auto","created_at":"2025-03-31 11:20:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":94388,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of paraspinal muscle parameter values for multifidus (A-D), erector spinae (E-H), and psoas major (I-L) across different age groups in healthy adult males. ES, erector spinae; MF, multifidus; PS, psoas muscle; MC, muscle content; WC, water content; MD, mean density; CSA, cross sectional area. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/38f45331394e95b2b9a74b34.jpg"},{"id":79575032,"identity":"d4f5fe74-ce69-43bf-98c8-6acf79da90fb","added_by":"auto","created_at":"2025-03-31 11:12:50","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":104313,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of paraspinal muscle parameter values for multifidus (A-D), erector spinae (E-H), and psoas major (I-L) across different age groups in healthy adult females. ES, erector spinae; MF, multifidus; PS, psoas muscle; MC, muscle content; WC, water content; MD, mean density; CSA, cross sectional area. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/f426b0ec61eda6fc31c65866.jpg"},{"id":79575033,"identity":"45c53fc3-fb29-4bc3-8aa2-7238cdb3e82c","added_by":"auto","created_at":"2025-03-31 11:12:50","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":187665,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between paraspinal muscle parameters and age. Blue indicates a negative correlation, while red represents a positive correlation; the deeper the color and the larger the area of the block, the higher the correlation.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/bc67a9aafe581bea47ace8a6.jpg"},{"id":84242654,"identity":"db30a5a6-7991-4fd5-a5a8-e14c93a7ebba","added_by":"auto","created_at":"2025-06-09 16:10:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1560991,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/5483338a-fcb2-401d-ac37-138bf0751013.pdf"},{"id":79573242,"identity":"58774d1a-c697-44d8-901e-d3dcbb0f4f75","added_by":"auto","created_at":"2025-03-31 11:04:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1995782,"visible":true,"origin":"","legend":"","description":"","filename":"supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-6237350/v1/6b1485d9af9e50ea1359cf29.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Changes of Water and Muscle Content in Paraspinal Muscle Degeneration and Gender Differences During Aging Using Dual-Energy CT","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe paraspinal muscles play a pivotal role in maintaining spinal stability, and their structural and functional changes are closely associated with overall back health[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As individuals age, degeneration of the paraspinal muscles significantly increases the risk of vertebral compression fractures, spondylolisthesis, and lumbar disc disease, thereby adversely affecting the quality of life in the elderly population[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, a comprehensive assessment of the paraspinal muscles, coupled with the early identification of their physiological changes, is essential for understanding back health in older adults. This understanding is critical for developing effective preventive strategies and guiding appropriate treatment interventions.\u003c/p\u003e \u003cp\u003eMuscle imaging evaluation has attracted growing interest in musculoskeletal research, with current imaging methods primarily focused on measuring muscle mass and muscle quality[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the relationship between paraspinal muscle mass/quality and aging still remains inconclusive due to the complex nature of muscle aging. Traditional computed tomography (CT) evaluates muscle mass by measuring cross-sectional area (CSA) and assesses muscle quality through CT values (muscle density, MD)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, their measuring accuracy may be interfered by the presence of other components with similar CT values. On the other hand, current radiological studies on muscle physiology primarily focus on assessing fat content within muscles, using techniques such as quantitative computed tomography (QCT) and quantitative magnetic resonance imaging (qMRI)[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Extensive research has established fat infiltration as a key biomarker of muscle degeneration during aging[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, beyond fat infiltration, muscle tissue is also highly water-rich, and changes in water content may impact both muscle quality and function[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Preliminary studies have shown a correlation between paraspinal muscle water content and chronic nonspecific low back pain[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], but the patterns of water content and associated factors such as muscle inflammation, edema, and fibrotic necrosis in the context of normal paraspinal muscle aging and degeneration remain unexplored.\u003c/p\u003e \u003cp\u003eFast kilovolt peak (kVp) switching dual-energy computed tomography (DECT) with Gemstone Spectral Imaging (GSI) enables precise quantification of a diverse array of materials by utilizing basis material paired images[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The basis material pairs are reconstructed from the two components contained within the mixture, with the attenuation curve corresponding to the specific material's absorption characteristics across varying X-ray energies having been established by physicists[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. This capability allows for the quantification of materials such as calcium, hydroxyapatite, iron, uric acid, fat, and water, which has been reported to enhance clinical diagnosis and inform decision-making in the musculoskeletal and endocrine domains[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Additionally, DECT offers several advantages over magnetic resonance imaging (MRI), including a reduced risk of contraindications, significantly shorter scan times, and lower costs. Nevertheless, research on the application of DECT for the assessment of paraspinal muscle degeneration, particularly concerning muscle and water-related changes associated with normal aging, remains limited. This study employs DECT muscle-water basis pair images to quantitatively analyze muscle and water content changes in the lumbar paraspinal muscles of healthy individuals across different age groups. The goal is to provide a comprehensive, non-invasive, and objective basis for studying age-related lumbar degenerations.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eFrom August 2021 to February 2023, 156 healthy individuals were prospectively enrolled and underwent prospective lumbar DECT imaging. Inclusion criteria were: (1) healthy adults aged 20\u0026ndash;79 years with a normal body mass index (18.5\u0026ndash;24.9 kg/m\u0026sup2;); (2) absence of any history of low back pain. Exclusion criteria included: (1) history of lumbar trauma or surgery; (2) presence of spinal deformities, lumbar infections, tumors, or tumor-like lesions; (3) history of using medications affecting muscle metabolism or alcohol abuse; (4) presence of muscular system diseases, renal insufficiency, cardiovascular disease, diabetes, neurological deficits, or other systemic diseases; (5) incomplete imaging data or poor image quality. Ultimately, a total of 125 participants were included in this study: 40 in the young group, 42 in the middle-aged group, and 43 in the elderly group. An additional 31 participants were excluded due to incomplete imaging data or the detection of spinal infections, lumbar tumors, or other abnormalities, or poor image quality due to motion artifacts. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e details the inclusion and exclusion process. This prospective study received approval from the Medical Ethics Committee of the XXX, and all participants provided informed consent before undergoing the examination.\u003c/p\u003e\n\u003cdiv class=\"Heading\"\u003eDECT Scanning Protocol\u003c/div\u003e \u003cp\u003eDECT imaging was performed using a Revolution CT scanner (GE HealthCare, Milwaukee, WI, USA) in GSI mode. Subjects were positioned supine. The scanning range extended from the 12th thoracic vertebra to the 1st sacral vertebra. Scanning parameters were: tube voltage of 80/140 kV, tube current of 230 mA, collimation width of 0.625 mm, pitch of 0.984:1, gantry rotation speed of 0.8 s/r, and CT dose index (CTDIvol) of 9.09 mGy. Standard kernel was utilized with a 30% weight of Adaptive Statistical Iterative Reconstruction-V (ASiR-V30%) to reconstruct images.\u003c/p\u003e\n\u003ch3\u003eImage Post-Processing\u003c/h3\u003e\n\u003cp\u003eImage data were analyzed using Advantage Workstation 4.6 (GE Medical Healthcare, Milwaukee, WI, USA) and processed with GSI volume viewer software to obtain virtual monoenergetic 70keV images (70keV VMI), muscle-water and water-muscle basis pair images. The regions of interest (ROIs) were positioned in the multifidus (MF), erector spinae (ES), and psoas (PS) muscles bilaterally, avoiding surrounding fat, vertebrae, and subcutaneous fat (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Firstly, ROIs were manually delineated on 70 keV monochromatic axial images at the L1/2 to L4/5 intervertebral disc levels for ES and L2/3 to L5/S1 intervertebral disc levels for MF and PS, and the CT value was recorded as muscle density (MD, HU), the ROI area was regarded as CSA. Then ROIs were cloned to the water-muscle images and muscle-water images to obtain water content (WC, mg cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) and muscle content (MC, mg cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e), respectively. Two experienced radiologists independently performed these measurements three times for each side, and the mean values were calculated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using SPSS 22.0 software. Data normality was assessed with the Kolmogorov-Smirnov test for continuous data. The Kolmogorov-Smirnov test was used to evaluate the normality of continuous variables. Data following a normal distribution are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while non-normally distributed data are reported as median (interquartile range). The differences in paraspinal muscle parameters among young (20\u0026ndash;39 years), middle-aged (40\u0026ndash;59 years), and elderly (60\u0026ndash;79 years) groups were analyzed using one-way ANOVA for normally distributed data and Kruskal-Wallis H test for non-normally distributed data. For pairwise comparisons, the Bonferroni method was applied. Categorical variables were presented as frequencies and assessed using the χ\u0026sup2; test. Spearman correlation analysis was employed to examine the association between paraspinal muscle parameters and age. A P-value of less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical Characteristics\u003c/h2\u003e \u003cp\u003eA total of 125 healthy adults (61 males, 64 females), aged 20\u0026ndash;79 years (median 50 years), were included in the study. The participants were divided into three age groups: young (20\u0026ndash;39 years, median 29.5, 20 males and 20 females), middle-aged (40\u0026ndash;59 years, median 49.5, 20 males and 22 females), and elderly (60\u0026ndash;79 years, median 68, 21 males and 22 females). There were no significant differences in baseline characteristics among the groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of general clinical data of the subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYoung group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMiddle group(n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOld group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;43)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.40\u0026thinsp;\u0026plusmn;\u0026thinsp;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.10\u0026thinsp;\u0026plusmn;\u0026thinsp;5.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.07\u0026thinsp;\u0026plusmn;\u0026thinsp;8.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Male/Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163.45\u0026thinsp;\u0026plusmn;\u0026thinsp;7.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.33\u0026thinsp;\u0026plusmn;\u0026thinsp;8.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e163.44\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.60\u0026thinsp;\u0026plusmn;\u0026thinsp;8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.23\u0026thinsp;\u0026plusmn;\u0026thinsp;11.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.34\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.56\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: The values are given as frequencies or means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. BMI, Body mass index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison of Paraspinal Muscle Parameters Across Age Groups\u003c/h3\u003e\n\u003cp\u003eSignificant differences were observed in MD across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with a decreasing trend from the young to the elderly group. Except for the MD of the PS at the L2/3 to L5/S1 levels between the middle-aged and elderly groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), MD differences were statistically significant across groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Differences in CSA were significant only for the ES at the L4/5 level, the MF at the L5/S1 level, and the PS at the L4/5 to L5/S1 levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). WC differences were significant across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), showing an increasing trend with aging. The WC of the MF at the L4/5 to L5/S1 levels and the ES at the L4/5 level were significantly different between groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). MC differences were statistically significant across age groups only for the MF at the L2/3 to L5/S1 levels (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Comparison of paraspinal muscles parameters at different levels among three age groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"130%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eYoung group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMiddle group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eOld group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e56.13(53.35, 59.24)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e51.30(48.65, 54.43)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e43.08(33.20, 50.29)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e55.40(52.61, 58.89)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e50.70(46.45, 54.65)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e39.12(29.31, 46.61)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e54.48(50.39, 58.21)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e48.75(44.53, 52.05)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e35.40(22.79, 45.73)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e50.33(47.79, 53.90)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e38.85(26.35, 46.13)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e11.57(-8.86, 28.94)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCSA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003cp\u003eL1/2\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e57.30(54.01, 59.88)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e56.53(50.96, 60.38)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e54.60(51.70, 59.84)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e54.08(49.58, 57.18)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e56.38(54.38, 58.39)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e55.78(54.28, 57.88)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e56.05(45.34, 58.78)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e57.00(55.36, 59.20)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1205.50(1024.73, 1551.50)\u003c/p\u003e\n \u003cp\u003e1224.75(1091.83, 1569.40)\u003c/p\u003e\n \u003cp\u003e1114.83(845.11,1452.25)\u003c/p\u003e\n \u003cp\u003e770.18(633.99, 914.41)\u003c/p\u003e\n \u003cp\u003e202.30(154.05, 239.81)\u003c/p\u003e\n \u003cp\u003e324.25(276.61, 406.46)\u003c/p\u003e\n \u003cp\u003e548.40(434.54, 639.61)\u003c/p\u003e\n \u003cp\u003e484.98(389.78, 555.99)\u003c/p\u003e\n \u003cp\u003e368.28(257.70, 584.25)\u003c/p\u003e\n \u003cp\u003e670.08(458.38, 900.20)\u003c/p\u003e\n \u003cp\u003e866.90(638.66, 1207.29)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e816.55(578.85, 1058.18)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e53.00 (46.88, 56.80)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e51.40(48.55, 55.23)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e46.85(35.85, 52.53)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e35.70(26.33, 50.60)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e54.13(51.20, 55.96)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e51.73(49.56, 54.76)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e53.48(51.93, 56.46)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e54.05(51.70, 56.08)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1267.70(1085.69,1487.41)\u003c/p\u003e\n \u003cp\u003e1301.05(1187.66, 1522.66)\u003c/p\u003e\n \u003cp\u003e1096.70(910.53, 1305.04)\u003c/p\u003e\n \u003cp\u003e694.23(556.90, 818.23)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e162.00(134.53, 202.15)\u003c/p\u003e\n \u003cp\u003e286.40(239.38, 359.68)\u003c/p\u003e\n \u003cp\u003e590.80(450.53, 734.20)\u003c/p\u003e\n \u003cp\u003e522.95(433.30, 608.95)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e312.70(217.94, 485.69)\u003c/p\u003e\n \u003cp\u003e540.80(421.60, 734.39)\u003c/p\u003e\n \u003cp\u003e680.55(532.65, 944.76)\u003c/p\u003e\n \u003cp\u003e601.25(455.04, 826.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e37.20(24.53, 45.63)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e37.70(25.24, 45.10)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e24.65(11.59, 33.85)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e9.25(-11.08, 20.23)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e45.55(39.70, 52.25)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e45.70(39.15, 51.25)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e49.75(44.30, 52.95)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e49.05(43.85, 52.55)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1172.55(950.50, 1399.00)\u003c/p\u003e\n \u003cp\u003e1290.65(1024.90,1596.00)\u003c/p\u003e\n \u003cp\u003e1088.10(952.85, 1288.40)\u003c/p\u003e\n \u003cp\u003e844.95(636.60, 966.60)\u003c/p\u003e\n \u003cp\u003e165.58(139.05, 219.11)\u003c/p\u003e\n \u003cp\u003e312.33(262.76, 396.65)\u003c/p\u003e\n \u003cp\u003e622.15(528.05, 720.25)\u003c/p\u003e\n \u003cp\u003e600.05(494.81, 736.33)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e294.45(239.30, 521.65)\u003c/p\u003e\n \u003cp\u003e522.85(413.50, 817.75)\u003c/p\u003e\n \u003cp\u003e621.75(511.45, 897.10)\u003csup\u003e\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e561.85(466.80, 773.35)\u003csup\u003e\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003cp\u003e0.622\u003c/p\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.026\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.000\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.165\u003c/p\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: The values are given as median (interquartile range) or means \u0026plusmn; standard deviation. ES, erector spinae;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMF, multifidus; PS, psoas muscle；MD, mean density; CSA, cross sectional area. * Young group vs. Middle\u003c/p\u003e\n\u003cp\u003eGroup, # Middle group vs. Old group, \u0026sect; Young group vs. Old group. *, #, \u0026sect; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **, ##, \u0026sect;\u0026sect; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ***,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e###, \u0026sect;\u0026sect;\u0026sect;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Comparison of paraspinal muscles parameters at different levels among three age groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"130%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eMuscle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYoung group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eMiddle group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eOld group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp;P\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eMC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL1/2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1069.00\u0026plusmn;254.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1107.5\u0026plusmn;279.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1135.90\u0026plusmn;326.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1069.03\u0026plusmn;258.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1099.57\u0026plusmn;321.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1092.30\u0026plusmn;335.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1072.21\u0026plusmn;324.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1093.12\u0026plusmn;256.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1064.42\u0026plusmn;399.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1019.90\u0026plusmn;340.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e907.47\u0026plusmn;3305.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e844.83\u0026plusmn;404.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWC\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eES\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMF\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003cp\u003eL1/2\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1288.95\u0026plusmn;284.88\u003c/p\u003e\n \u003cp\u003e1358.52\u0026plusmn;344.17\u003c/p\u003e\n \u003cp\u003e1189.40\u0026plusmn;283.40\u003c/p\u003e\n \u003cp\u003e1346.84\u0026plusmn;332.32\u003c/p\u003e\n \u003cp\u003e1575.90\u0026plusmn;304.95\u003c/p\u003e\n \u003cp\u003e1440.35\u0026plusmn;339.14\u003c/p\u003e\n \u003cp\u003e1411.27\u0026plusmn;311.35\u003c/p\u003e\n \u003cp\u003e1705.63\u0026plusmn;291.81\u003c/p\u003e\n \u003cp\u003e411.73(297.20, 486.28)\u003c/p\u003e\n \u003cp\u003e422.48(304.88, 559.20)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e480.98(309.83, 592.63)\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e592.33(428.63, 822.01)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e347.33(238.69, 510.51)\u003c/p\u003e\n \u003cp\u003e363.65(225.69, 571.99)\u003c/p\u003e\n \u003cp\u003e422.60(233.81, 688.39)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e462.68(330.84, 602.40)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1366.97\u0026plusmn;355.01\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1403.95\u0026plusmn;355.79\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1124.32\u0026plusmn;287.95\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1343.33\u0026plusmn;337.14\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1700.45\u0026plusmn;309.11\u003c/p\u003e\n \u003cp\u003e1426.33\u0026plusmn;292.43\u003c/p\u003e\n \u003cp\u003e1558.72\u0026plusmn;265.05\u003c/p\u003e\n \u003cp\u003e1807.01\u0026plusmn;287.68\u003c/p\u003e\n \u003cp\u003e502.15(353.63, 598.35)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e524.50(382.43, 724.16)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e551.45(473.13, 771.03)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e929.60(718.25, 1321.55)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e403.25(244.45, 624.83)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e420.80(283.88, 608.70)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e775.28(537.03, 1067.09)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e945.00(550.55, 1262.95)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1182.07\u0026plusmn;378.66\u003c/p\u003e\n \u003cp\u003e1194.89\u0026plusmn;387.95\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e991.43\u0026plusmn;346.01\u003csup\u003e\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1086.79\u0026plusmn;403.36\u003csup\u003e\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1623.82\u0026plusmn;410.70\u003c/p\u003e\n \u003cp\u003e1430.46\u0026plusmn;418.42\u003c/p\u003e\n \u003cp\u003e1544.35\u0026plusmn;405.27\u003c/p\u003e\n \u003cp\u003e1767.88\u0026plusmn;384.02\u003c/p\u003e\n \u003cp\u003e833.05(484.48, 1055.19)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e905.10(640.91 1269.65)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1104.00(614.78, 1397.13)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1756.50(1283.75, 2122.25)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e990.73(670.23, 1388.88)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1002.34(590.29, 1448.25)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1409.50(1118.00, 1776.50)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e1614.00(1355.38, 2042.45)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.023\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.013\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003cp\u003e0.983\u003c/p\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eL2/3\u003c/p\u003e\n \u003cp\u003eL3/4\u003c/p\u003e\n \u003cp\u003eL4/5\u003c/p\u003e\n \u003cp\u003eL5/S1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e106.42(-70.36, 187.63)\u003c/p\u003e\n \u003cp\u003e193.98(112.02, 266.74)\u003c/p\u003e\n \u003cp\u003e171.81(69.65, 275.03)\u003c/p\u003e\n \u003cp\u003e142.40(12.56, 265.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e117.94(0.08, 240.00)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e270.15(158.38, 402.98)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e166.84(43.24, 286.78)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e204.13(53.55, 339.18)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e349.85(178.15, 605.60)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e469.75(275.20, 658.70)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e341.05(143.20, 592.60)\u003csup\u003e\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e408.95(178.67, 564.60)\u003csup\u003e\u0026sect;\u0026sect;\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: The values are given as median (interquartile range) or means \u0026plusmn; standard deviation. ES, erector spinae;\u003c/p\u003e\n\u003cp\u003eMF, multifidus; PS, psoas muscle；WC, water content; MC, muscle content. * Young group vs. Middle\u0026nbsp;\u003c/p\u003e\n\u003cp\u003egroup, # Middle group vs. Old group, \u0026sect; Young group vs. Old group. *, #, \u0026sect; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **, ##, \u0026sect;\u0026sect; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ***,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e###, \u0026sect;\u0026sect;\u0026sect; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eComparison of Paraspinal Muscle Parameters in Male Subjects Across Age Groups\u003c/h3\u003e\n\u003cp\u003eIn male subjects, MD differences were significant across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with a decreasing trend from young to elderly. WC differences were significant across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), showing an increasing trend except for the PS at the L3/4 level. MC differences were significant only for the MF at the L4/5 level between the young and elderly groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). CSA differences were significant only for the MF at the L2/3 and L5/S1 levels and the PS at the L4/5 to L5/S1 levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComparison of Paraspinal Muscle Parameters in Female Subjects Across Age Groups\u003c/h2\u003e \u003cp\u003eIn female subjects, MD differences were significant across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with a decreasing trend from young to elderly. WC differences were significant across age groups (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), showing an increasing trend except for the PS at the L2/3, L4/5, and L5/S1 levels and the MF at the L3/4 level. WC differences between the middle-aged and elderly groups were significant for all intervertebral disc levels except for the PS at the L5/S1 level (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). MC differences were significant for the MF at the L3/4 and L5/S1 levels between the middle-aged and elderly groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with higher WC in the middle-aged group. CSA differences were significant for the MF at the L4/5 to L5/S1 levels, the PS at the L4/5 to L5/S1 levels, and the PS at the L1/2 to L2/3 levels (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation Between Paraspinal Muscle Parameters and Age\u003c/h2\u003e \u003cp\u003eThe MD of the paraspinal muscles was negatively correlated with age across all levels (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with the higher correlations for the MF at the L4/5 and L5/S1 levels and the ES at the L4/5 level (r = -0.823, -0.830, -0.833, respectively; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The WC of the paraspinal muscles was positively correlated with age across all levels (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with the higher correlations for the MF at the L4/5 and L5/S1 levels and the ES at the L4/5 level (r\u0026thinsp;=\u0026thinsp;0.809, 0.817, 0.783, respectively; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The CSA of the PS at the L4/5 to L5/S1 levels showed a moderate correlation with age (r = -0.490, -0.531, respectively; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;6).\u003c/p\u003e \u003cp\u003eIn male subjects, the MD of the MF at L4/5 and L5/S1, and the ES at L4/5, showed strong negative correlations with age (r = -0.828 to -0.865, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the WC at these levels had strong positive correlations (r\u0026thinsp;=\u0026thinsp;0.813 to 0.872, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, in females, the MD of the MF at L4/5 and L5/S1, and the ES at L4/5, exhibited strong negative correlations with age (r = -0.793 to -0.812, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the WC at these levels had strong positive correlations (r\u0026thinsp;=\u0026thinsp;0.784 to 0.826, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-2).\u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eCurrently, the non-invasive imaging evidences for water and muscle content changes in paraspinal muscles with aging and the gender-specific differences are still insufficient. Our findings based on DECT measurements demonstrate a significant decrease in the MD of the paraspinal muscles with advancing age, accompanied by an increase in WC, particularly noted in the MF and ES muscles of the lower lumbar spine. Notably, in males, the increase in WC is more pronounced with age, while in females, this trend becomes significant primarily from middle age onward. Moreover, in males, the MC of the lower lumbar MF shows a decline with age; conversely, in females, MC is observed to be higher in the middle-aged cohort and lowest in the elderly group. These age- and gender-specific parameters are not only essential for developing personalized rehabilitation strategies but also enhance the non-invasive detection of pathological degeneration. By comparing pathological states against age-specific baseline values, these findings provide valuable insights for clinical diagnosis and treatment, paving the way for more tailored interventions in both male and female patients across different age groups.\u003c/p\u003e \u003cp\u003eCT values (Hounsfield units, HU) are important for assessing muscle density, reflecting muscle performance and physical function[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Previous research has demonstrated a strong correlation between the decline in paraspinal muscle CT values and increased muscle fat content[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our study corroborates this by demonstrating a decreasing trend in paraspinal muscle MD with age, indicating increased muscle fat infiltration and decreased muscle function, consistent with Orwoll ES's findings[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The consistency and low variability of CT measurements make it an effective tool for assessing changes in muscle fat content, especially in monitoring sarcopenia and myosteatosis[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, CT values represent the average density of various intramuscular components, which alone cannot provide a detailed analysis of the physiological composition changes in paraspinal muscles.\u003c/p\u003e \u003cp\u003eDECT basis material pair images provides detailed, high-contrast quantitative images by analyzing the characteristic attenuation curve of specific material in projection domain [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This technique could be facilely used to track content changes (mg cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e) of specific component. Studies suggest that the balance between intracellular and extracellular water content is key in evaluating muscle aging, with intracellular water (ICW) content closely related to muscle mass, strength, and function[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Using DECT muscle-water basis material paired technology, our results show an increasing trend in paraspinal muscle WC with age, indicating an increase in water content in muscle interstitial spaces with aging. This finding is supported by a cross-sectional study on adult body composition, which found an increasing ratio of extracellular water (ECW) to ICW with age[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The expansion of the extracellular space and increased ECW content may be due to reduced muscle cell number, reduced function of central body fluid regulation, and diminished kidney concentration ability, leading to a transfer of muscle cell water to the interstitial spaces[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Additionally, decreased muscle repair capacity with aging may lead to inflammation and edema, increasing extracellular water content[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Thus, changes in paraspinal muscle WC based on muscle-water decomposition images may serve as biomarkers for evaluating muscle aging and degeneration. Furthermore, the study found that changes in paraspinal muscle WC were more pronounced in males, while in females, this change was significant only at older ages. This may be related to the protective effect of estrogen on muscle mass and strength by mediating various estrogen receptors, which contribute to its anti-inflammatory effects, promotion of muscle cell proliferation, and inhibition of muscle atrophy. [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Moreover, studies show that aquaporins are essential for maintaining intracellular water and muscle function in skeletal muscle[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Sex hormones, including estrogen, regulate aquaporins, and postmenopausal estrogen loss disrupts this regulation, leading to imbalanced intracellular water and accelerated muscle decline[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This finding highlights the importance of exercise plans and nutritional advice for postmenopausal women to slow muscle aging and degeneration, thus improving the quality of life in elderly women.\u003c/p\u003e \u003cp\u003eThe study also shows that the MC of the lower lumbar MF decreases with age in males, while in females, it is higher in the middle-aged group and lowest in the elderly group, which had not been reported before. This gender difference may be due to various factors, including physiology, hormone levels, lifestyle, and physical activity levels[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This finding further underscores the importance of gender-specific considerations in developing personalized rehabilitation strategies. Additionally, only the MC of the MF at the lower lumbar levels showed significant changes across age groups, possibly due to the greater stress these muscles endure in spine movement and stability, making them more prone to degeneration[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, measuring the MC of the lower lumbar MF may better reflect changes in muscle fiber quantity during aging, aiding in early identification and intervention of muscle function changes.\u003c/p\u003e \u003cp\u003eThe impact of age on the CSA of most paraspinal muscles was not significant, likely because total CSA represents the entire muscle area within the fascia, which can be replaced by adipose tissue as muscle content decreases, resulting in no significant change in total CSA[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, the CSA of the lower-level PS decreased significantly with age, suggesting that the CSA of the psoas muscle, being a low-fat muscle[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], may more accurately reflect changes in muscle fiber quantity during aging.\u003c/p\u003e \u003cp\u003eNotably, the high correlations between age and the WD and WC of MF and ES at the lower lumbar levels indicate that paraspinal muscles in these areas are more prone to atrophy and degeneration, leading to reduced muscle function. This may be due to the greater mechanical load that the ES and MF at lower lumbar levels endure during spinal movements, making them more susceptible to degeneration with aging[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Therefore, it is essential to focus on the functional recovery and strengthening of the MF and ES, using specific training methods such as suspension core training.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, the sample size across different age groups was relatively small, introducing potential selection bias. Larger sample sizes are required to further explore the underlying mechanisms of age-related changes in muscle composition and their relationship with muscle function. Second, unmeasured or residual confounding factors, such as exercise or dietary habits, may exist. Third, the selection of ROI is subjective, and this study only extracted paraspinal muscles at the intervertebral disc level for analysis. Future research could employ automatic segmentation technology to perform comprehensive studies on paraspinal muscles.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDECT material separation with rapid kVp switching effectively quantifies age-related physiological changes in paraspinal muscles. Notably, paraspinal muscle water content, as measured through muscle-water separation, shows significant age- and gender-dependent differences. This method supports personalized prevention and intervention strategies for age- and gender-related musculoskeletal diseases and provides valuable clinical references for distinguishing pathological degeneration.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Muqing Luo, Huiting Deng, Zeya Zhong, Jianyu Li and Yinqi Liu. The first draft of the manuscript was written by Muqing Luo and all authors commented on previous versions of the manuscript. Revision and final version of the manuscript were written by Mengtian Ma and Kun Zhang. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to express our sincere appreciation to Dr. Suping Chen from GE HealthCare for her invaluable technical guidance and support during the manuscript revision process, which significantly contributed to the success of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWesselink EO, Pool-Goudzwaard A, De Leener B, Law CSW, Fenyo MB, Ello GM, Coppieters MW, Elliott JM, Mackey S, Weber KA, 2nd (2024) Investigating the associations between lumbar paraspinal muscle health and age, BMI, sex, physical activity, and back pain using an automated computer-vision model: A UK Biobank study. Spine J. doi: 10.1016/j.spinee.2024.02.013\u003c/li\u003e\n\u003cli\u003eChen X, Cui P, Li Y, Wang Y, Lu S (2024) Links among MRI features in paraspinal muscles, inflammatory processes, and related back pain in patients with lumbar disc herniation. JOR Spine 7:e1310. doi: 10.1002/jsp2.1310\u003c/li\u003e\n\u003cli\u003eHuang YL, Zhou JL, Jiang YM, Zhang ZG, Zhao W, Han D, He B (2020) Assessment of lumbar paraspinal muscle activation using fMRI BOLD imaging and T2 mapping. Quant Imaging Med Surg 10:106-115. doi: 10.21037/qims.2019.10.20\u003c/li\u003e\n\u003cli\u003eSeyedhoseinpoor T, Taghipour M, Dadgoo M, Sanjari MA, Takamjani IE, Kazemnejad A, Khoshamooz Y, Hides J (2022) Alteration of lumbar muscle morphology and composition in relation to low back pain: a systematic review and meta-analysis. Spine J 22:660-676. doi: 10.1016/j.spinee.2021.10.018\u003c/li\u003e\n\u003cli\u003eEngelke K, Chaudry O, Gast L, Eldib MA, Wang L, Laredo JD, Schett G, Nagel AM (2023) Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translat 42:57-72. doi: 10.1016/j.jot.2023.07.005\u003c/li\u003e\n\u003cli\u003eUrakawa H, Sato K, Vaishnav AS, Lee R, Chaudhary C, Mok JK, Virk S, Sheha E, Katsuura Y, Kaito T, Gang CH, Qureshi SA (2023) Preoperative cross-sectional area of psoas muscle correlates with short-term functional outcomes after posterior lumbar surgery. Eur Spine J 32:2326-2335. doi: 10.1007/s00586-023-07533-7\u003c/li\u003e\n\u003cli\u003eAmini B, Boyle SP, Boutin RD, Lenchik L (2019) Approaches to Assessment of Muscle Mass and Myosteatosis on Computed Tomography: A Systematic Review. J Gerontol A Biol Sci Med Sci 74:1671-1678. doi: 10.1093/gerona/glz034\u003c/li\u003e\n\u003cli\u003ePeng X, Li X, Xu Z, Wang L, Cai W, Yang S, Liao W, Cheng X (2020) Age-related fatty infiltration of lumbar paraspinal muscles: a normative reference database study in 516 Chinese females. Quant Imaging Med Surg 10:1590-1601. doi: 10.21037/qims-19-835\u003c/li\u003e\n\u003cli\u003eKrkoska P, Kokosova V, Dostal M, Vlazna D, Kerkovsky M, Straka M, Gerstberger R, Matulova K, Ovesna P, Adamova B (2024) Assessment of lumbar paraspinal muscle morphology using mDixon Quant magnetic resonance imaging (MRI): a cross-sectional study in healthy subjects. Quant Imaging Med Surg 14:6015-6035. doi: 10.21037/qims-23-1796\u003c/li\u003e\n\u003cli\u003eGao Y, Jiang H, Gao R, Zhou X (2024) Evaluation of lumbar paraspinal muscles degeneration and fatty infiltration in dynamic sagittal imbalance based on magnetic resonance imaging. Eur Spine J 33:1840-1849. doi: 10.1007/s00586-023-08033-4\u003c/li\u003e\n\u003cli\u003eEck BL, Yang M, Elias JJ, Winalski CS, Altahawi F, Subhas N, Li X (2023) Quantitative MRI for Evaluation of Musculoskeletal Disease: Cartilage and Muscle Composition, Joint Inflammation, and Biomechanics in Osteoarthritis. Invest Radiol 58:60-75. doi: 10.1097/RLI.0000000000000909\u003c/li\u003e\n\u003cli\u003eMarcus RL, Addison O, Kidde JP, Dibble LE, Lastayo PC (2010) Skeletal muscle fat infiltration: impact of age, inactivity, and exercise. J Nutr Health Aging 14:362-366. doi: 10.1007/s12603-010-0081-2\u003c/li\u003e\n\u003cli\u003eLee SH, Park SW, Kim YB, Nam TK, Lee YS (2017) The fatty degeneration of lumbar paraspinal muscles on computed tomography scan according to age and disc level. Spine J 17:81-87. doi: 10.1016/j.spinee.2016.08.001\u003c/li\u003e\n\u003cli\u003eSerra-Prat M, Lorenzo I, Palomera E, Yebenes JC, Campins L, Cabre M (2019) Intracellular Water Content in Lean Mass is Associated with Muscle Strength, Functional Capacity, and Frailty in Community-Dwelling Elderly Individuals. A Cross-Sectional Study. Nutrients 11. doi: 10.3390/nu11030661\u003c/li\u003e\n\u003cli\u003eZhou X, Liu Y, Chen S, Xiang J, Li J, Li J, You T, Zhong Z, Zhang K (2024) Increased water content in multifidus muscles of young adults with chronic nonspecific low back pain detected by dual-energy CT and MRI. Eur J Radiol 176:111515. doi: 10.1016/j.ejrad.2024.111515\u003c/li\u003e\n\u003cli\u003eGoo HW, Goo JM (2017) Dual-Energy CT: New Horizon in Medical Imaging. Korean J Radiol 18:555-569. doi: 10.3348/kjr.2017.18.4.555\u003c/li\u003e\n\u003cli\u003eMolwitz I, Leiderer M, McDonough R, Fischer R, Ozga AK, Ozden C, Tahir E, Koehler D, Adam G, Yamamura J (2021) Skeletal muscle fat quantification by dual-energy computed tomography in comparison with 3T MR imaging. Eur Radiol 31:7529-7539. doi: 10.1007/s00330-021-07820-1\u003c/li\u003e\n\u003cli\u003eLi B, Hua N, Li J, Andreu-Arasa VC, LeBedis C, Anderson SW (2023) Quantification of spinal bone marrow fat fraction using three-material decomposition technique on dual-energy CT: A phantom study. Med Phys 50:4105-4111. doi: 10.1002/mp.16442\u003c/li\u003e\n\u003cli\u003eSullivan J, Pillinger MH, Toprover M (2021) Chondrocalcinosis: Advances in Diagnostic Imaging. Curr Rheumatol Rep 23:77. doi: 10.1007/s11926-021-01044-4\u003c/li\u003e\n\u003cli\u003eBorges AP, Antunes C, Caseiro-Alves F (2023) Spectral CT: Current Liver Applications. Diagnostics (Basel) 13. doi: 10.3390/diagnostics13101673\u003c/li\u003e\n\u003cli\u003eEngelke K, Museyko O, Wang L, Laredo JD (2018) Quantitative analysis of skeletal muscle by computed tomography imaging-State of the art. J Orthop Translat 15:91-103. doi: 10.1016/j.jot.2018.10.004\u003c/li\u003e\n\u003cli\u003eOrwoll ES, Blackwell T, Cummings SR, Cauley JA, Lane NE, Hoffman AR, Burghardt AJ, Evans WJ, Cawthon PM (2022) CT Muscle Density, D3Cr Muscle Mass, and Body Fat Associations With Physical Performance, Mobility Outcomes, and Mortality Risk in Older Men. J Gerontol A Biol Sci Med Sci 77:790-799. doi: 10.1093/gerona/glab266\u003c/li\u003e\n\u003cli\u003eFeng Z, Rong P, Luo M, Sun X, Wang W (2019) Influence of Methods Used to Establish Sarcopenia Cutoff Values for Skeletal Muscle Measures Using Unenhanced and Contrast-Enhanced Computed Tomography Images. JPEN J Parenter Enteral Nutr 43:1028-1036. doi: 10.1002/jpen.1519\u003c/li\u003e\n\u003cli\u003eSiegel MJ, Bhalla S, Cullinane M (2021) Dual-Energy CT Material Decomposition in Pediatric Thoracic Oncology. Radiol Imaging Cancer 3:e200097. doi: 10.1148/rycan.2021200097\u003c/li\u003e\n\u003cli\u003eOhashi Y, Joki N, Yamazaki K, Kawamura T, Tai R, Oguchi H, Yuasa R, Sakai K (2018) Changes in the fluid volume balance between intra- and extracellular water in a sample of Japanese adults aged 15-88 yr old: a cross-sectional study. Am J Physiol Renal Physiol 314:F614-F622. doi: 10.1152/ajprenal.00477.2017\u003c/li\u003e\n\u003cli\u003eKerch G (2018) Distribution of tightly and loosely bound water in biological macromolecules and age-related diseases. Int J Biol Macromol 118:1310-1318. doi: 10.1016/j.ijbiomac.2018.06.187\u003c/li\u003e\n\u003cli\u003eLorenzo I, Serra-Prat M, Yebenes JC (2019) The Role of Water Homeostasis in Muscle Function and Frailty: A Review. Nutrients 11. doi: 10.3390/nu11081857\u003c/li\u003e\n\u003cli\u003eFrontera WR, Ochala J (2015) Skeletal muscle: a brief review of structure and function. Calcif Tissue Int 96:183-195. doi: 10.1007/s00223-014-9915-y\u003c/li\u003e\n\u003cli\u003eYoh K, Ikeda K, Horie K, Inoue S (2023) Roles of Estrogen, Estrogen Receptors, and Estrogen-Related Receptors in Skeletal Muscle: Regulation of Mitochondrial Function. Int J Mol Sci 24. doi: 10.3390/ijms24031853\u003c/li\u003e\n\u003cli\u003ePellegrino A, Tiidus PM, Vandenboom R (2022) Mechanisms of Estrogen Influence on Skeletal Muscle: Mass, Regeneration, and Mitochondrial Function. Sports Med 52:2853-2869. doi: 10.1007/s40279-022-01733-9\u003c/li\u003e\n\u003cli\u003eKo SH, Jung Y (2021) Energy Metabolism Changes and Dysregulated Lipid Metabolism in Postmenopausal Women. Nutrients 13. doi: 10.3390/nu13124556\u003c/li\u003e\n\u003cli\u003eAslesh T, Al-Aghbari A, Yokota T (2023) Assessing the Role of Aquaporin 4 in Skeletal Muscle Function. Int J Mol Sci 24. doi: 10.3390/ijms24021489\u003c/li\u003e\n\u003cli\u003eKhan S, Ricciardelli C, Yool AJ (2021) Targeting Aquaporins in Novel Therapies for Male and Female Breast and Reproductive Cancers. Cells 10. doi: 10.3390/cells10020215\u003c/li\u003e\n\u003cli\u003eCritchlow AJ, Hiam D, Williams R, Scott D, Lamon S (2023) The role of estrogen in female skeletal muscle aging: A systematic review. Maturitas 178:107844. doi: 10.1016/j.maturitas.2023.107844\u003c/li\u003e\n\u003cli\u003ePinto SM, Cheung JPY, Samartzis D, Karppinen J, Zheng YP, Pang MYC, Wong AYL (2022) Are Morphometric and Biomechanical Characteristics of Lumbar Multifidus Related to Pain Intensity or Disability in People With Chronic Low Back Pain After Considering Psychological Factors or Insomnia? Front Psychiatry 13:809891. doi: 10.3389/fpsyt.2022.809891\u003c/li\u003e\n\u003cli\u003eKalichman L, Carmeli E, Been E (2017) The Association between Imaging Parameters of the Paraspinal Muscles, Spinal Degeneration, and Low Back Pain. Biomed Res Int 2017:2562957. doi: 10.1155/2017/2562957\u003c/li\u003e\n\u003cli\u003eMuellner M, Chiapparelli E, Moser M, Haffer H, Dodo Y, Adl Amini D, Carrino JA, Tan ET, Shue J, Zhu J, Sama AA, Cammisa FP, Girardi FP, Hughes AP (2022) The effect of age on psoas and paraspinal muscle morphology in patients undergoing posterior lumbar fusion surgery. Eur Spine J 31:2619-2628. doi: 10.1007/s00586-022-07346-0\u003c/li\u003e\n\u003cli\u003eXia W, Fu H, Zhu Z, Liu C, Wang K, Xu S, Liu H (2019) Association between back muscle degeneration and spinal-pelvic parameters in patients with degenerative spinal kyphosis. BMC Musculoskelet Disord 20:454. doi: 10.1186/s12891-019-2837-0\u003c/li\u003e\n\u003cli\u003eMoser M, Adl Amini D, Jones C, Zhu J, Okano I, Oezel L, Chiapparelli E, Tan ET, Shue J, Sama AA, Cammisa FP, Girardi FP, Hughes AP (2023) The predictive value of psoas and paraspinal muscle parameters measured on MRI for severe cage subsidence after standalone lateral lumbar interbody fusion. Spine J 23:42-53. doi: 10.1016/j.spinee.2022.03.009\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Paraspinal muscle, Dual-energy computed tomography, Aging, material decomposition","lastPublishedDoi":"10.21203/rs.3.rs-6237350/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6237350/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjectives\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo quantitatively assess paraspinal muscle degeneration and gender-related differences during aging in adults using rapid kVp switching dual-energy computed tomography (DECT).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 156 healthy adults underwent lumbar DECT scans and were prospectively grouped into young (20\u0026ndash;39 years), middle-aged (40\u0026ndash;59 years), and elderly (60\u0026ndash;79 years) groups. Muscle density (MD), cross-sectional area (CSA), muscle content (MC), and water content (WC) were measured using muscle-water decomposition images for the bilateral erector spinae (ES) at the L1/2 to L4/5 levels and bilateral multifidus (MF) and psoas (PS) at the L2/3 to L5/S1 levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAcross age groups, significant differences in paraspinal muscle MD and WC were observed (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with MD negatively and WC positively correlated with age at lower lumbar levels for both MF and ES (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In females, except for the L5/S1 PS, WC differences between the middle-aged and elderly groups were significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but not between the young and middle-aged groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In males, multifidus MC at L4/5 decreased with age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while in females, multifidus MC at L3/4 and L5/S1 was higher in the middle-aged group and lowest in the elderly group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PS CSA at L4/5-L5/S1 showed a moderate negative correlation with age (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe muscle-water decomposition technique using rapid kVp switching DECT provides a noninvasive quantitative assessment of paraspinal muscle degeneration by evaluating changes in muscle and water content, potentially reflecting alterations in the extracellular matrix. This method highlights age- and gender-related differences, aiding in the differentiation between physiological aging and pathological degeneration.\u003c/p\u003e","manuscriptTitle":"Changes of Water and Muscle Content in Paraspinal Muscle Degeneration and Gender Differences During Aging Using Dual-Energy CT","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:04:45","doi":"10.21203/rs.3.rs-6237350/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-23T02:05:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-20T14:12:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-14T03:51:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166338648007793759038882078990204888772","date":"2025-04-12T16:43:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-10T02:10:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45220837421483126794802696394179028178","date":"2025-04-07T01:41:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54978602129787980645164630413106489810","date":"2025-04-04T04:40:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-19T12:44:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-18T13:24:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-18T13:24:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Spine Journal","date":"2025-03-16T11:38:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"57c17a87-2a3b-4145-bb68-b9218d3bc19a","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T16:05:10+00:00","versionOfRecord":{"articleIdentity":"rs-6237350","link":"https://doi.org/10.1007/s00586-025-08968-w","journal":{"identity":"european-spine-journal","isVorOnly":false,"title":"European Spine Journal"},"publishedOn":"2025-06-05 15:57:56","publishedOnDateReadable":"June 5th, 2025"},"versionCreatedAt":"2025-03-31 11:04:45","video":"","vorDoi":"10.1007/s00586-025-08968-w","vorDoiUrl":"https://doi.org/10.1007/s00586-025-08968-w","workflowStages":[]},"version":"v1","identity":"rs-6237350","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6237350","identity":"rs-6237350","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}