Quantitative MRI Assessment of Paraspinal Muscles and Construction of a Predictive Model for Lumbar Disc Herniation

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This study aims to quantitatively assess paraspinal muscle parameters in LDH patients using MRI and to develop a multivariate imaging-based predictive model. Methods A total of 100 participants were prospectively enrolled, including 53 patients with LDH and 47 healthy controls. This cross-sectional study compared demographic and paraspinal muscle imaging characteristics between groups. All subjects underwent T2 mapping and diffusion tensor imaging (DTI) using a 3.0T MRI scanner. Pain and functional status were assessed using the Numeric Pain Rating Scale (NPRS) and Oswestry Disability Index (ODI). Group comparisons were performed using ANCOVA to adjust for confounders. Partial Spearman correlation evaluated associations between imaging metrics and clinical scores. Stepwise multiple linear regression identified predictors of NPRS and ODI, while logistic regression determined independent LDH risk factors and construction of a nomogram-based predictive model. Results The LDH group had a significantly higher mean age than controls ( P = 0.023), with no significant differences in other baseline characteristics ( P > 0.05). ANCOVA revealed lower fractional anisotropy (FA) values in the bilateral erector spinae (ES) at L4/5 and higher apparent diffusion coefficient (ADC) values in the bilateral ES at L4/5, right ES at L5/S1, and bilateral multifidus (MF) in the LDH group ( P < 0.05 or P < 0.01). Partial correlation analysis showed that T2 values of specific ES and MF segments were positively associated with ODI and NPRS scores ( P < 0.05). Multiple regression identified the L4/5 left MF T2 value as the strongest predictor of NPRS and age as the main predictor of ODI ( P < 0.01). Logistic regression confirmed age, the L3/4 right ES T2 value, and the L5/S1 right ES ADC as independent LDH predictors. The multivariate model yielded the best predictive performance (AUC = 0.772), with nomogram analysis highlighting the L5/S1 right ES ADC as the most influential parameter. Conclusions Paraspinal muscle imaging parameters are effective markers for evaluating muscle status and disease burden in LDH. Multivariate logistic regression identified age, the T2 value of the right erector spinae at L3/4, and the ADC value at L5/S1 as LDH risk factors. Multimodal MRI lumbar disc herniation paraspinal muscles predictive model nomogram Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Lumbar disc herniation (LDH) is a common degenerative spinal disorder characterized by rupture of the annulus fibrosus and protrusion of the nucleus pulposus[ 1 , 2 ], leading to compression or irritation of nerve roots and subsequent clinical symptoms. Epidemiological studies report a prevalence of LDH as high as 31.9%[ 1 , 3 ]. With the changing patterns of modern lifestyles, LDH is increasingly affecting younger populations, thereby imposing a substantial health and economic burden on both individuals and society. Studies have shown that over 95% of LDH cases occur at the L4/5 and L5/S1 levels[ 4 – 6 ]. Although the exact pathophysiological mechanism remains unclear, impaired spinal stability has been recognized as a major contributing factor[ 7 ]. According to Panjabi’s[ 8 ] three-subsystem model of spinal stability, the integrity of the spine is maintained through the coordinated interaction of the passive subsystem (vertebrae, intervertebral discs, etc.), the active subsystem (paraspinal muscles), and the neural control subsystem. Dysfunction or impairment in any of these components can compromise spinal equilibrium and trigger a cascade of clinical manifestations. The paraspinal muscles play a pivotal role in sustaining spinal stability[ 9 , 10 ]. In LDH, the disruption of spinal biomechanics leads to increased compensatory loading on these muscles. Chronic mechanical stress may induce degenerative changes in paraspinal muscles, further aggravating spinal instability and ultimately creating a vicious cycle of dysfunction[ 11 , 12 ]. Although conventional imaging modalities such as X-ray and CT are widely used and provide rapid acquisition, they have limited capability in accurately quantifying the microstructural characteristics of paraspinal muscles[ 13 , 14 ]. Additionally, ionizing radiation restricts their utility in long-term follow-up and early lesion surveillance. In contrast, magnetic resonance imaging (MRI), with its superior soft tissue resolution and contrast, is considered the gold standard for assessing the morphology and composition of paraspinal muscles[ 15 ]. In recent years, emerging techniques such as diffusion tensor imaging (DTI) and T2 mapping have offered novel insights into the microstructural evaluation of paraspinal muscles. DTI allows tracking of water molecule diffusion, enabling detection of structural alterations and visualization of muscle fiber orientation via tractography[ 16 , 17 ]. T2 mapping quantitatively measures transverse relaxation time (T2 value), which reflects tissue water content, collagen fiber organization, and other microstructural features[ 18 , 19 ]. Elevated T2 values have been associated with muscle edema[ 20 – 22 ], while the apparent diffusion coefficient (ADC) reflects the degree of water diffusion restriction[ 23 ]. Furthermore, reduced fractional anisotropy (FA) indicates disorganization of fiber orientation, which may relate to neural dysfunction or chronic degeneration[ 24 ]. However, the exact pathophysiological implications of these MRI parameters and their dynamic changes in LDH remain incompletely understood. The segment-specific patterns of paraspinal muscle degeneration and their interaction with LDH pathology require further investigation. Therefore, this study employed multiparametric MRI, including T2, ADC, and FA values, to analyze key lumbar segments (L3/4–L5/S1) with the following objectives: (1) to quantify segment-specific microstructural alterations of paraspinal muscles and compare degeneration patterns between LDH patients and healthy individuals; (2) to establish associations between MRI-derived parameters and clinical measures such as the Numeric Pain Rating Scale (NPRS) and Oswestry Disability Index (ODI); and (3) to identify imaging biomarkers capable of distinguishing LDH patients from healthy controls. Through this comprehensive analysis, we aim to enhance the understanding of paraspinal muscle pathology in LDH and provide a scientific foundation for personalized diagnosis and longitudinal monitoring. Methods Participants This study was approved by the Ethics Committee of the Affiliated Hospital of Guizhou Medical University (Approval No. [2024]240). From January to December 2024, a total of 118 participants were prospectively recruited at the Affiliated Hospital of Guizhou Medical University. Inclusion criteria for the LDH group were as follows: (1) intervertebral disc herniation at the L3/4 to L5/S1 levels confirmed by MRI[ 25 ]; (2) no history of lumbar spine surgery; and (3) age between 20 and 70 years, regardless of sex. Exclusion criteria included: (1) lumbar spondylolisthesis > 3 mm on MRI; (2) spinal fractures or deformities (e.g., scoliosis > 10°); (3) history of lumbar spine surgery; (4) spinal tuberculosis; (5) history of malignancy; (6) history of rheumatic diseases; (7) history of infection; and (8) contraindications to MRI. Healthy volunteers who were willing to participate and met the same exclusion criteria were concurrently recruited as controls. 18 individuals were excluded due to incomplete imaging data or presence of alternative causes of sciatica. A total of 100 participants were finally included in the study. All participants were informed of the purpose of the examinations and provided written informed consent. MRI Acquisition All examinations were performed using a GE Discovery 750W 3.0T MRI scanner (HDxt, GE Healthcare, Milwaukee, WI, USA). The imaging range extended from the L3/L4 to L5/S1 intervertebral discs. The scanning protocol included sagittal T2-weighted imaging (T2WI), axial T2WI, T2 mapping, and diffusion tensor imaging (DTI). Detailed MRI sequences and acquisition parameters are summarized in Table 1 . Table 1 All parameters for scanned MRI sequences Parameter T2WI T2WI T2 mapping DTI Acquisition orientation Sagittal Axial Axial Axial TR (ms) 2682 3136 600 8000 TE (ms) 120 122 7.3 83.5 FOV (mm) 300 × 300 220 × 220 420 × 420 240 × 240 Slice thickness (mm) 4 4 4 4 Interslice gap (mm) 1 1 1 2 Flip angle(°) 142 / / / Matrix 512 256 × 256 256 × 256 96 b-values(s.mm − 2 ) / / / 0,450 NEX 4 2 2 2 Bandwidth(Hz) 50 50 62.5 250 Acquisition time 1min21s 1min15s 4min10s 8min20s Image Processing Original T2 mapping and DTI images were processed using the ADW 4.6 workstation (GE Discovery 750W MRI system). Regions of interest (ROI) measuring 65–80 mm² were manually placed in the central portion of the paraspinal muscles, carefully avoiding inclusion of vessels, fascia, and surrounding intermuscular fat (Fig. 1 ). Quantitative measurements were independently performed by two radiologists, each with three years of experience in musculoskeletal imaging. The average of their measurements was used as the final data. Severity scoring criteria Functional impairment was assessed using the ODI, with higher scores indicating greater disability severity[ 26 ]. Pain intensity was quantified using the NPRS[ 27 ]. Both instruments have demonstrated strong validity, responsiveness, and reliability for evaluating low back pain and musculoskeletal pathology[ 28 , 29 ]. Statistical Analysis Statistical analyses were performed using Jamovi software (version 2.3.28.0) and R software (version 4.3.1). The Shapiro–Wilk test was used to assess the normality of continuous variables. Continuous variables were expressed as mean ± standard deviation or median with interquartile range (1st quartile, 3rd quartile). Normally distributed data were compared using independent-samples t-tests, while non-normally distributed data were analyzed using the non-parametric Mann–Whitney U test. Categorical variables were compared using the chi-square test. Given the age differences between the LDH and control groups, age was included as a covariate in the analysis of covariance (ANCOVA). Partial Spearman correlation analysis was performed to evaluate the associations between quantitative imaging parameters and ODI and NPRS. Stepwise multiple linear regression analysis was conducted to identify clinical and imaging variables independently associated with ODI and NPRS. Logistic regression analyses were used to construct predictive models for LDH risk. Nomograms were generated to visualize the models. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of various parameters, calculating the area under the curve (AUC). Calibration curves and decision curve analysis (DCA) were used to evaluate model agreement and clinical utility. Statistical significance was set at P < 0.05. Results Patient characteristics The study group included 53 participants, while the control group comprised 47 participants, totaling 100 individuals. The mean age of the study group was 48.57 ± 12.06 years, which was significantly higher than that of the control group (41.89 ± 13.10 years; P = 0.023). There were no significant differences between the groups in terms of sex distribution, height, weight, or body mass index (BMI) ( P > 0.05) (Table 2 ). Table 2 Comparison of general clinical data of the subjects Characteristics Study group (n = 53) Control group (n = 47) P Age (years) 48.57 ± 12.06 41.89 ± 13.10 0.023 * Gender (female / male) 28 / 25 20 / 27 0.590 Height (cm) 163.98 ± 7.63 163.00 ± 8.79 0.839 Weight (kg) 63.98 ± 11.64 64.79 ± 10.17 0.935 BMI (kg / m 2 ) 23.96 ± 3.23 24.02 ± 2.83 0.996 *: P <0.05 Analysis of Covariance of Paraspinal Muscle T2, FA, and ADC Values Between the Study and Control Groups T2 values were generally higher in the study group compared to the control group. However, the differences were not statistically significant, even in the most affected segments, particularly in the erector spinae (ES) and multifidus (MF) at the L4/5 and L5/S1 levels ( P > 0.05) (Table 3 ). Table 3 Comparison of T2 value between study group and control group Muscle Level Study group Control group F P ES L3/4_r 41.59 ± 4.55 39.10 ± 6.26 2.440 0.122 L3/4_l 41.87 ± 4.05 42.47 ± 3.99 1.260 0.264 L4/5_r 44.21 ± 5.98 42.99 ± 4.55 0.003 0.955 L4/5_l 45.79 ± 4.91 44.82 ± 3.94 0.027 0.869 L5/S1_r 45.72 ± 5.74 44.72 ± 4.85 0.112 0.739 L5/S1_l 45.73 ± 5.24 45.76 ± 4.17 0.562 0.455 MF L3/4_r 42.04 ± 4.00 41.54 ± 3.74 0.112 0.739 L3/4_l 41.63 ± 3.99 41.13 ± 4.27 0.005 0.942 L4/5_r 41.41 ± 4.55 40.11 ± 3.56 0.686 0.409 L4/5_l 41.76 ± 4.80 40.33 ± 3.93 0.418 0.520 L5/S1_r 39.78 ± 3.71 38.76 ± 2.29 1.430 0.235 L5/S1_l 39.73 ± 3.99 37.97 ± 5.69 1.580 0.212 At the L4/5 level, the FA values of bilateral ES were significantly lower in the study group than in the control group (0.30 ± 0.05 vs. 0.33 ± 0.10 and 0.29 ± 0.06 vs. 0.32 ± 0.09; P < 0.05) (Table 4 ). Table 4 Comparison of FA between study group and control group Muscle Level Study group Control group F P ES L3/4_r 0.29 ± 0.10 0.28 ± 0.06 0.161 0.689 L3/4_l 0.29 ± 0.08 0.29 ± 0.05 0.361 0.549 L4/5_r 0.30 ± 0.05 0.33 ± 0.10 6.875 0.010 * L4/5_l 0.29 ± 0.06 0.32 ± 0.09 4.450 0.038 * L5/S1_r 0.33 ± 0.08 0.36 ± 0.11 3.360 0.070 L5/S1_l 0.29 ± 0.07 0.30 ± 0.07 0.281 0.598 MF L3/4_r 0.28 ± 0.05 0.26 ± 0.05 1.700 0.196 L3/4_l 0.27 ± 0.06 0.28 ± 0.08 0.927 0.338 L4/5_r 0.27 ± 0.06 0.26 ± 0.04 6.875 0.547 L4/5_l 0.26 ± 0.05 0.26 ± 0.08 4.450 0.844 L5/S1_r 0.27 ± 0.06 0.27 ± 0.09 0.365 0.715 L5/S1_l 0.27 ± 0.07 0.26 ± 0.06 0.039 0.599 *: P < 0.05 The ADC values in the study group were significantly higher than those in the control group at the bilateral ES at the L4/5 level ( P < 0.01), as well as in the right ES and bilateral MF at the L5/S1 level ( P < 0.05), indicating statistically significant differences (Table 5 ). Table 5 Comparison of ADC between study group and control group Muscle Level Study group Control group F P ES L3/4_r 1.51 ± 0.25 1.59 ± 0.20 2.576 0.112 L3/4_l 1.54 ± 0.25 1.54 ± 0.24 0.316 0.576 L4/5_r 1.53 ± 0.12 1.41 ± 0.25 12.690 < 0 .001 ** L4/5_l 1.53 ± 0.13 1.44 ± 0.17 14.300 < 0.001 ** L5/S1_r 1.46 ± 0.27 1.25 ± 0.41 7.707 0.007 ** L5/S1_l 1.64 ± 0.35 1.56 ± 0.32 0.885 0.350 MF L3/4_r 1.50 ± 0.20 1.48 ± 0.14 0.269 0.605 L3/4_l 1.51 ± 0.20 1.48 ± 0.25 0.361 0.550 L4/5_r 1.53 ± 0.25 1.50 ± 0.18 1.180 0.279 L4/5_l 1.51 ± 0.16 1.54 ± 0.30 0.401 0.528 L5/S1_r 1.56 ± 0.26 1.45 ± 0.24 4.022 0.048 * L5/S1_l 1.56 ± 0.21 1.47 ± 0.14 8.360 0.005 ** *: P < 0.05; **: P < 0.01 Partial Correlation Analysis Between T2, FA, and ADC Values and Clinical Assessments In the ES, the ADC values of both sides at the L4/5 level were significantly positively correlated with the ODI ( r s = 0.337, P < 0.01; r s = 0.225, P < 0.05, respectively). Conversely, the right-sided ADC value at L4/5 showed a significant negative correlation with the NPRS ( r s = − 0.284, P < 0.01). In the MF, the T2 value of the right side at the L3/4 level was significantly positively correlated with NPRS ( r s = 0.225, P < 0.05) (Table 6 ). Table 6 Correlation of T2, FA, and ADC values at bilateral paraverteral muscles with ODI and NPRS Scores Characteristics Muscle Level NPRS ODI r s P r s P T2 ES L3/4_r 0.130 0.206 0.026 0.798 L3/4_l 0.129 0.210 -0.026 0.802 L4/5_r -0.023 0.827 -0.089 0.389 L4/5_l 0.118 0.253 0.072 0.486 L5/S1_r 0.048 0.645 -0.006 0.956 L5/S1_l 0.158 0.124 0.146 0.156 MF L3/4_r 0.225 0.028 * 0.149 0.147 L3/4_l 0.160 0.119 0.085 0.413 L4/5_r 0.024 0.813 -0.016 0.875 L4/5_l 0.118 0.252 0.040 0.700 L5/S1_r 0.103 0.319 0.064 0.534 L5/S1_l 0.104 0.313 0.081 0.434 FA ES L3/4_r 0.014 0.901 -0.022 0.835 L3/4_l 0.131 0.225 0.149 0.165 L4/5_r -0.111 0.307 -0.180 0.095 L4/5_l -0.003 0.977 0.053 0.626 L5/S1_r -0.115 0.305 -0.098 0.383 L5/S1_l -0.074 0.507 -0.032 0.775 MF L3/4_r 0.135 0.209 0.077 0.477 L3/4_l 0.011 0.918 0.004 0.968 L4/5_r 0.122 0.256 0.099 0.361 L4/5_l 0.032 0.770 0.055 0.609 L5/S1_r 0.085 0.431 0.111 0.303 L5/S1_l 0.047 0.662 0.086 0.423 ADC ES L3/4_r -0.200 0.062 -0.156 0.147 L3/4_l 0.092 0.394 0.062 0.569 L4/5_r 0.284 0.007 ** 0.337 0.001 ** L4/5_l 0.178 0.097 0.225 0.035 * L5/S1_r 0.093 0.407 0.174 0.119 L5/S1_l 0.121 0.278 0.078 0.486 MF L3/4_r -0.037 0.733 -0.073 0.497 L3/4_l -0.008 0.939 -0.080 0.458 L4/5_r 0.024 0.825 -0.059 0.583 L4/5_l -0.028 0.797 -0.002 0.983 L5/S1_r 0.095 0.380 0.185 0.085 L5/S1_l 0.151 0.162 0.181 0.091 *: P < 0.05; **: P < 0.01 Stepwise Multiple Linear Regression Analysis of the Influence of Clinical Assessments and Imaging Parameters Stepwise multiple linear regression analysis revealed that the T2 value of the left MF at the L4/5 level was significantly positively associated with NPRS scores (R² = 0.690, P < 0.01). Age was the strongest predictor of ODI scores (R² = 0.598, P < 0.01), indicating a significant positive correlation between increasing age and greater functional impairment. LDH was a significant predictor in both models (NPRS: R² = 0.714, P = 0.011; ODI: R² = 0.634, P = 0.006) (Table 7 ). Table 7 Results of multiple linear regression analysis Variable R 2 Adjusted R 2 F B SE β t P L4/5-T2-MF_l 0.690 0.687 182.754 0.080 0.011 0.655 7.251 < 0.001 ** LDH 0.714 0.707 101.072 0.522 0.202 0.234 2.588 0.011 * Dependent Variable: NPRS Age 0.598 0.593 121.865 0.242 0.046 0.550 5.323 <0 .001 ** LDH 0.634 0.625 70.288 2.760 0.968 0.294 2.850 0.006 ** Dependent Variable: ODI *: P < 0.05; **: P < 0.01 Modeling And Performance Evaluation Parameters with P < 0.1 in the univariate logistic regression analysis, along with relevant clinical variables, were included in the multivariate logistic regression model. The multivariate analysis identified age, the T2 value of the right erector spinae at the L3/4 level (L3/4-T2_ES_r), and the ADC value of the right erector spinae at the L5/S1 level (L5/S1-ADC_ES_r) as independent risk factors for LDH (Table 8 ). Table 8 Multivariate logistic regression analysis Characteristics B SE P OR 95%CI Age 0.056 0.024 0.022 1.057 1.008–1.109 L3/4-T2_ES_r 0.245 0.090 0.007 1.278 1.070–1.526 L5/S1-ADC_ES_r 2.493 1.053 0.018 12.097 1.537–95.204 ROC curves were generated using both the combined variables from the multivariate model and the individual predictors identified through univariate logistic regression (Fig. 2 ), and corresponding performance metrics were summarized (Table 9 ). The combined model demonstrated the best predictive performance, with an AUC of 0.772 (95% CI: 0.678–0.867) and a Youden index of 0.627. Among individual predictors, L5/S1-ADC_ES_r showed the highest diagnostic performance, with an AUC of 0.733 (95% CI: 0.627–0.838). Table 9 Summary table of performance metrics Characteristics AUC Sensitivity Specificity Youden Index 95%CI L3/4-T2_ES_r 0.677 0.588 0.732 0.320 0.569–0.786 L4/5-ADC_ES_r 0.720 0.686 0.756 0.442 0.611–0.830 L4/5-ADC_ES_l 0.694 0.725 0.659 0.384 0.582–0.830 L5/S1-ADC_ES_r 0.733 0.627 0.805 0.432 0.627–0.838 L5/S1-ADC_ES_l 0.657 0.824 0.488 0.312 0.541–0.773 L5/S1-ADC_MF_r 0.622 0.353 0.878 0.231 0.507–0.737 L5/S1-ADC_MF_l 0.637 0.549 0.732 0.281 0.523–0.750 Combined 0.772 0.569 0.878 0.447 0.678–0.867 A nomogram was constructed based on the multivariate logistic regression model. As shown in the nomogram (Fig. 3 ), for a hypothetical 55-year-old patient (age corresponding to 20 points), with an L3/4-T2_ES_r value of 50 (60 points) and an L5/S1-ADC_ES_r value of 1.1 (40 points), the total score was 120 points, corresponding to an estimated LDH risk of approximately 80%. Calibration and decision curve analyses demonstrated good agreement and clinical applicability of the nomogram model (Figs. 4 A and 4 B). Discussion This prospective cohort study delineated the segment-specific patterns of microstructural degeneration in the paraspinal muscles of patients with LDH. Quantitative analysis revealed that, compared with healthy controls, LDH patients exhibited significantly reduced FA in the bilateral ES muscles at the L4/5 level ( P < 0.05), along with significantly elevated ADC values in the bilateral ES at L4/5, the right ES at L5/S1, and the bilateral MF ( P 0.05), suggesting that LDH-related paraspinal muscle degeneration may follow a pathophysiological trajectory distinct from that of other degenerative spinal conditions. Two possible explanations may account for this discrepancy: First, age-related confounding may accelerate fibrotic processes, thereby masking the influence of inflammatory edema on T2 values. Previous studies have indicated that inflammation or edema is typically associated with elevated T2 signals[ 20 , 21 , 30 , 31 ]. However, in patients with chronic low back pain, gene expression related to paraspinal muscle fibrosis has been found to be markedly upregulated[ 32 ]. Since the degree of fibrosis is negatively correlated with T2 values[ 33 ], it is plausible that fibrosis may offset the T2-elevating effects of edema, resulting in flattened T2 signal changes. Second, the lack of significant findings may reflect limited sensitivity of current MRI sequences in detecting subclinical pathological changes. Future investigations integrating multimodal imaging with histological validation are warranted to further elucidate these mechanisms. Multiple linear regression analysis identified age as the primary predictor of ODI scores (R² = 0.598, P < 0.01), underscoring the pivotal role of aging in the progression of paraspinal muscle degeneration. This finding aligns with the conclusions reported by Valentin[ 34 ]. Partial correlation analysis further demonstrated a positive association between ADC values at the L4/5 level and both NPRS and ODI scores, suggesting a direct and quantifiable relationship between paraspinal microstructural alterations and the severity of clinical symptoms. Although previous studies have associated reduced ADC values with fibrotic changes[ 35 ], the present findings indicate that elevated ADC may reflect early alterations in tissue hydration or acute inflammatory responses. This discrepancy could be attributed to the heterogeneous pathological stages of LDH—acute stages are typically dominated by inflammatory exudation[ 36 ], while chronic stages are characterized by fibrosis[ 37 , 38 ]. These observations suggest that dynamic monitoring of ADC values may serve as a potential imaging biomarker for disease staging in LDH. Moreover, this study further advances the understanding of paraspinal muscle degeneration by incorporating the perspective of spatial heterogeneity. The L4/5 and L5/S1 segments, which bear the greatest biomechanical load within the lumbar spine[ 39 ], exhibited a concordant pattern of decreased FA and increased ADC values in both the erector spinae and multifidus muscles, indicating microstructural abnormalities within these regions. Such alterations may compromise the dynamic stability of the spine, leading to imbalanced stress distribution across intervertebral discs[ 8 ]. These imaging findings provide evidence supporting the existence of a positive feedback loop involving degeneration, biomechanical imbalance, and symptom escalation. Collectively, these results not only reinforce the theoretical framework of "neurodegeneration–inflammatory microenvironment interaction"[ 37 ], but also challenge the traditional unidimensional hypothesis of mechanical compression[ 40 ]. Logistic regression analysis identified age, the T2 value of the right erector spinae at the L3/4 level (L3/4-T2_ES_r), and the ADC value of the right erector spinae at the L5/S1 level (L5/S1-ADC_ES_r) as significant risk factors for LDH. Among all paraspinal imaging parameters, ROC curve analysis showed that L5/S1-ADC_ES_r had the highest diagnostic performance (AUC = 0.733). When combined with age, the diagnostic performance improved further, yielding an AUC of 0.772. Further validation through logistic regression confirmed that both L5/S1-ADC_ES_r (AUC = 0.703) and age (OR = 1.058) were independent predictors of LDH. Notably, for every unit increase in ADC, the risk of LDH increased by approximately 12-fold (OR = 12.097, P = 0.018), highlighting the potentially critical role of paraspinal microstructural abnormalities in LDH pathogenesis. Nomogram analysis revealed that L5/S1-ADC_ES_r contributed the most to the overall risk prediction model. This supports the hypothesis that elevated ADC may reflect extracellular matrix remodeling secondary to blood–nerve barrier disruption[ 41 ]—a microenvironmental alteration likely to precede macroscopic structural degeneration[ 42 ]. Therefore, integrating age with L5/S1-ADC_ES_r into a comprehensive risk stratification framework may be valuable for early clinical decision-making. Specifically, individuals over 45 years of age with L5/S1-ADC_ES_r > 1.5 × 10⁻³ mm²/s should be prioritized for targeted core muscle strengthening programs to delay degenerative progression. Although this study established a relatively effective risk prediction model for LDH, future work could enhance its performance by incorporating additional imaging parameters—such as fat fraction—to construct a multidimensional evaluation framework capable of quantifying the heterogeneity of muscle degeneration. Moreover, the application of advanced machine learning algorithms, such as random forests or neural networks, may further improve predictive accuracy by capturing complex nonlinear interactions. In parallel, future studies could integrate quantitative ADC values into finite element models to simulate the dynamic impact of muscle degeneration on intervertebral disc stress distribution. Such simulations may contribute to refining surgical indications and developing individualized rehabilitation strategies. In summary, this study not only underscores the value of multiparametric MRI in the assessment of LDH but also provides imaging biomarker–based evidence to support personalized clinical decision-making. Furthermore, it lays a data-driven foundation for optimizing dynamic monitoring and intervention strategies targeting paraspinal muscle degeneration. Limitations This study has several limitations. First, the relatively small sample size may limit the generalizability of the predictive model. Due to the limited cohort size, we were unable to perform stratified analyses based on variables such as age, occupation, disease duration, or the severity of disc herniation, which may influence paraspinal muscle degeneration. It is plausible that occupational load and disease chronicity could lead to structural alterations in the paraspinal muscles. In future studies, we plan to expand the sample size and conduct longitudinal follow-up to assess the predictive value of imaging parameters for disease progression. Second, the study relied solely on imaging-derived parameters, without incorporating multidimensional data such as biomechanical metrics or metabolomics, which may have led to residual confounding. Lastly, the ROI for paraspinal muscles were manually delineated on axial MRI images, which introduces potential measurement bias. To enhance the objectivity and reproducibility of data acquisition, future research should explore the integration of AI-based automated segmentation techniques, which may reduce systematic errors associated with manual ROI definition through standardized image processing. Conclusions This study utilized quantitative MRI to assess structural changes in the paraspinal muscles and demonstrated that T2 values, ADC, and FA are effective biomarkers for characterizing muscle status in patients with LDH. These imaging parameters showed significant associations with pain intensity and functional impairment. A predictive model based on multivariate logistic regression was further developed and visualized using a nomogram to enable individualized risk assessment. The proposed model offers a non-invasive and objective imaging-based approach for the early diagnosis and precise management of LDH, highlighting its promising potential for clinical translation. Declarations Ethics approval and consent to participate This study was conducted in accordance with the declaration of Helsinki. This study was conducted with approval from the Ethics Committee of The Affiliated Hospital of Guizhou Medical University (Approval No. [2024]240). A written informed consent was obtained from all participants. Clinical trial number Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by Science & Technology Projects of Guizhou Province of China (Grant/Award Number: ZK[2023] General 354); Authors' contributions Conception and design of the research: X D; Acquisition of data: M H; Analysis and interpretation of the data: M H, Q D, Y J, C T; Statistical analysis: M H; Writing of the manuscript: M H, Q D; Critical revision of the manuscript for intellectual content: X D; All authors read and approved the final draft. Acknowledgements We are grateful to thank all of the participants, the staff, and the other study investigators for their valuable contributions. References Deyo RA, Mirza SK. Herniated Lumbar Intervertebral Disk. N Engl J Med. 2016;374:1763–72. Wang L, He T, Liu J, Tai J, Wang B, Zhang L, et al. Revealing the Immune Infiltration Landscape and Identifying Diagnostic Biomarkers for Lumbar Disc Herniation. Front Immunol. 2021;12:666355. Sun B-L, Zhang Y, Zhang N, Xiong X, Zhong Y-X, Xing K, et al. Prevalence of lumbar disc herniation in populations with different symptoms based on magnetic resonance imaging study. J Clin Neurosci. 2024;129:110839. Al-Khawaja DO, Mahasneh T, Li JC. Surgical treatment of far lateral lumbar disc herniation: a safe and simple approach. J Spine Surg. 2016;2:21–4. Wang H, Wang Y, Li Y, Wang C, Qie S. A diagnostic model of nerve root compression localization in lower lumbar disc herniation based on random forest algorithm and surface electromyography. Front Hum Neurosci. 2023;17:1176001. Al Qaraghli MI, De Jesus O. Lumbar disc herniation. Statpearls. Treasure Island. (FL): StatPearls Publishing; 2025. Jin L, Yin Y, Chen W, Zhang R, Guo J, Tao S, et al. Role of the lumbosacral transition vertebra and vertebral lamina in the pathogenesis of lumbar disc herniation. Orthop Surg. 2021;13:2355–62. Panjabi MM. The Stabilizing System of the Spine. Part I. Function, Dysfunction, Adaptation, and Enhancement: Journal of Spinal Disorders. 1992;5:383–9. Larivière C, Henry SM, Preuss R. Structural remodeling of the lumbar multifidus, thoracolumbar fascia and lateral abdominal wall perimuscular connective tissues: A search for its potential determinants. J Anat. 2021;238:536–50. Li Y, Chen Y, Liu Y, Hai Y, Zhang X, Guan L, et al. Changes in Paraspinal Muscles and Facet Joints after Minimally Invasive Posterior Lumbar Interbody Fusion Using the Cortical Bone Trajectory Technique: A Prospective Study. Pain Res Manage. 2022;2022:1–7. Bergmark A. Stability of the lumbar spine: A study in mechanical engineering. Acta Orthop Scand. 1989;60:1–54. Yuan H, Dong L, Zhang O, Wang X, Chen Z, Li Y, et al. A comparison of interferential current efficacy in elderly intervertebral disc degeneration patients with or without sarcopenia: a retrospective study. BMC Musculoskelet Disord. 2024;25:214. Li C, Dang C, Liu G, Chen L, Zhang J, Li J, et al. Secondary damage in left-sided frontal white matter detected by diffusion tensor imaging is correlated with executive dysfunction in patients with acute infarction at the ipsilateral posterior corona radiata. Eur J Med Res. 2014;19:44. Engelke K, Chaudry O, Gast L, Eldib MAb, Wang L, Laredo J-D, et al. Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translation. 2023;42:57–72. Hodges PW, Bailey JF, Fortin M, Battié MC. Paraspinal muscle imaging measurements for common spinal disorders: review and consensus-based recommendations from the ISSLS degenerative spinal phenotypes group. Eur Spine J. 2021;30:3428–41. Wang F, Fang S, Li J, Yuan L, Hou B, Zhu J, et al. Correlation analysis of quantitative MRI measurements of thigh muscles with histopathology in patients with idiopathic inflammatory myopathy. Eur Radiol Exp. 2023;7:51. Cameron D, Reiter DA, Adelnia F, Ubaida-Mohien C, Bergeron CM, Choi S, et al. Age‐related changes in human skeletal muscle microstructure and architecture assessed by diffusion‐tensor magnetic resonance imaging and their association with muscle strength. Aging Cell. 2023;22:e13851. Gassert FT, Kufner A, Gassert FG, Leonhardt Y, Kronthaler S, Schwaiger BJ, et al. MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures. Osteoporos Int. 2022;33:487–96. Bouhsina N, Decante C, Hardel J-B, Rouleau D, Abadie J, Hamel A, et al. Comparison of MRI T1, T2, and T2* mapping with histology for assessment of intervertebral disc degeneration in an ovine model. Sci Rep. 2022;12:5398. Das T, Roos JCP, Patterson AJ, Graves MJ, Murthy R. T2-relaxation mapping and fat fraction assessment to objectively quantify clinical activity in thyroid eye disease: an initial feasibility study. Eye. 2019;33:235–43. Kuo GP, Carrino JA. Skeletal muscle imaging and inflammatory myopathies. Curr Opin Rheumatol. 2007;19:530–5. Arpan I, Forbes SC, Lott DJ, Senesac CR, Daniels MJ, Triplett WT, et al. T 2 mapping provides multiple approaches for the characterization of muscle involvement in neuromuscular diseases: a cross-sectional study of lower leg muscles in 5–15‐year‐old boys with Duchenne muscular dystrophy. NMR Biomed. 2013;26:320–8. Keller S, Yamamura J, Sedlacik J, Wang ZJ, Gebert P, Starekova J, et al. Diffusion tensor imaging combined with T2 mapping to quantify changes in the skeletal muscle associated with training and endurance exercise in competitive triathletes. Eur Radiol. 2020;30:2830–42. Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis – a technical review. NMR Biomed. 2002;15:456–67. Diener H-C, Hankey GJ. Primary and Secondary Prevention of Ischemic Stroke and Cerebral Hemorrhage. J Am Coll Cardiol. 2020;75:1804–18. Koivunen K, Widbom-Kolhanen S, Pernaa K, Arokoski J, Saltychev M. Reliability and validity of Oswestry Disability Index among patients undergoing lumbar spinal surgery. BMC Surg. 2024;24:13. Amjad F, Khalid A. Comparative effects of Bowen therapy and tennis ball technique on pain and functional disability in patients with thoracic myofascial pain syndrome. J Orthop Surg Res. 2023;18:895. Pontes-Silva A, Dibai-Filho AV, Costa De Jesus SF, De Santos LA, Bassi-Dibai D, De Fidelis CA, et al. The best structure of the Tampa Scale for Kinesiophobia for patients with chronic low back pain has two domains and nine items. Clin Rehabil. 2023;37:407–14. Nagy Z, Kiss N, Szigeti M, Áfra J, Lekka N, Misik F, et al. Construct validity of the Hungarian Version of the Patient-Reported Outcomes Measurement Information System-29 Profile Among Patients with Low Back Pain. World Neurosurg. 2024;181:e55–66. Ran J, Ji S, Morelli JN, Wu G, Li X. T2 mapping in dermatomyositis/polymyositis and correlation with clinical parameters. Clinical Radiology. 2018;73:1057.e13-1057.e18. Peng F, Xu H, Song Y, Xu K, Li S, Cai X, et al. Utilization of T1-Mapping for the pelvic and thigh muscles in Duchenne Muscular Dystrophy: a quantitative biomarker for disease involvement and correlation with clinical assessments. BMC Musculoskelet Disord. 2022;23:681. Shahidi B, Fisch KM, Gibbons MC, Ward SR. Increased Fibrogenic Gene Expression in Multifidus Muscles of Patients With Chronic Versus Acute Lumbar Spine Pathology. Spine. 2020;45:E189–95. Idilman IS, Celik A, Savas B, Idilman R, Karcaaltincaba M. The feasibility of T2 mapping in the assessment of hepatic steatosis, inflammation, and fibrosis in patients with non-alcoholic fatty liver disease: a preliminary study. Clinical Radiology. 2021;76:709.e13-709.e18. Valentin S, Licka T, Elliott J. Age and side-related morphometric MRI evaluation of trunk muscles in people without back pain. Man Therap. 2015;20:90–5. Elhawary M, Elmansy M, Ali K, Abdallah E, Razek A, Barakat T, et al. Diffusion tensor magnetic resonance imaging in the grading of liver fibrosis associated with congenital ductal plate malformations. Pol J Radiol. 2023;88:135–40. Brisby H, Olmarker K, Larsson K, Nutu M, Rydevik B. Proinflammatory cytokines in cerebrospinal fluid and serum in patients with disc herniation and sciatica. Eur Spine J. 2002;11:62–6. Risbud MV, Shapiro IM. Role of cytokines in intervertebral disc degeneration: pain and disc content. Nat Rev Rheumatol. 2014;10:44–56. Agha O, Mueller-Immergluck A, Liu M, Zhang H, Theologis AA, Clark A, et al. Intervertebral disc herniation effects on multifidus muscle composition and resident stem cell populations. JOR Spine. 2020;3:e1091. Li D, Wang L, Wang Z, Li C, Yuan S, Tian Y, et al. Age-related radiographic parameters difference between the degenerative lumbar spinal stenosis patients and healthy people and correlation analysis. J Orthop Surg Res. 2022;17:475. Mister WJ. Rupture of the intervertebral disc with involvement of the spinal canal. N Engl J Med. 2009. Reis C, Wang Y, Akyol O, Ho W, Ii R, Stier G, et al. What’s New in Traumatic Brain Injury: Update on Tracking, Monitoring and Treatment. IJMS. 2015;16:11903–65. Luo M, Liu Y, Liu WV, Ma M, Liao Y, Chen S, et al. Quantitative magnetic resonance imaging of paraspinal muscles for assessing chronic non-specific low back pain in young adults: a prospective case-control study. Eur Spine J. 2024;33:4544–54. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-6777748","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476014016,"identity":"91f067af-c880-4046-91e8-54c26f55afbc","order_by":0,"name":"Mi Han","email":"","orcid":"","institution":"Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mi","middleName":"","lastName":"Han","suffix":""},{"id":476014017,"identity":"52fb443c-2d81-4884-8ea4-1b5b88b382c0","order_by":1,"name":"Qiong Deng","email":"","orcid":"","institution":"Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiong","middleName":"","lastName":"Deng","suffix":""},{"id":476014018,"identity":"3d741041-6a47-4e23-ab3f-87eabd3e83e1","order_by":2,"name":"Yao Jia","email":"","orcid":"","institution":"Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yao","middleName":"","lastName":"Jia","suffix":""},{"id":476014019,"identity":"2cc30a05-7f6b-4cbb-b179-122d31a4cbbc","order_by":3,"name":"Changzhan Tong","email":"","orcid":"","institution":"Affiliated Hospital of Guizhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Changzhan","middleName":"","lastName":"Tong","suffix":""},{"id":476014020,"identity":"336976d6-63cd-4abe-99b1-bbd35a28d822","order_by":4,"name":"Xia Du","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBACNvbG5gcfKv7x8BOthY/ncJvhjDMH5CQbiNUiJ5HeIM3bdsDY4ADRDmNIbDDgbbuTuPl48gaGHxXbiNFysOGBxLlnidvOPCtg7DlzmwgtjI0NBgZlzInbbuQYMDO2EaOFmbFBIoGNOXHzDKK1sAG1HGg7bGwgQbQWHsY2w4YzaXISQL8cJMov8vOfP378p8KGh789eeODHxVEaEECCcRHDUILqTpGwSgYBaNghAAAffNA4e50CbUAAAAASUVORK5CYII=","orcid":"","institution":"Affiliated Hospital of Guizhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xia","middleName":"","lastName":"Du","suffix":""}],"badges":[],"createdAt":"2025-05-29 15:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6777748/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6777748/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85737182,"identity":"aa65fd0f-585a-4f00-9b72-2a72ff87ca5c","added_by":"auto","created_at":"2025-07-01 08:10:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":548990,"visible":true,"origin":"","legend":"\u003cp\u003eHealthy control group subject scan images. Axial (A) and sagittal (B) views of the L5/S1 disc level for a 32-year-old male, and DTI (C) and T2 mapping (D) sequence ROI delineation diagram at the L4/5 level.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6777748/v1/b5a6ded04494307c6849e315.png"},{"id":85735807,"identity":"260d9f4e-e0e4-4a4c-b5d5-81c1e1113bf0","added_by":"auto","created_at":"2025-07-01 08:02:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61411,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves distinguishing the case group from the control group based on different imaging parameters. The AUC of the combined variables is the highest (0.772).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6777748/v1/77cc46898474d6f96d88b6b5.png"},{"id":85737183,"identity":"76dd448d-4c96-4878-98f5-2fc435d029cc","added_by":"auto","created_at":"2025-07-01 08:10:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":813379,"visible":true,"origin":"","legend":"\u003cp\u003eRisk prediction nomogram for lumbar disc herniation.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6777748/v1/4f6fd50cb2853554598c17f2.png"},{"id":85735809,"identity":"c9ffa3f2-23f8-46f6-9770-ebfb54cf0488","added_by":"auto","created_at":"2025-07-01 08:02:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":44528,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curve of the prediction model for the nomogram (A), clinical decision curve (B).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6777748/v1/355a1ff12b1657f8952f852c.png"},{"id":91850615,"identity":"5ac69755-cbd1-4889-99b2-c134f5c6f1ea","added_by":"auto","created_at":"2025-09-22 11:16:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2466073,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6777748/v1/03b49fdd-1127-45b6-bbc5-1dd4321a2797.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quantitative MRI Assessment of Paraspinal Muscles and Construction of a Predictive Model for Lumbar Disc Herniation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLumbar disc herniation (LDH) is a common degenerative spinal disorder characterized by rupture of the annulus fibrosus and protrusion of the nucleus pulposus[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], leading to compression or irritation of nerve roots and subsequent clinical symptoms. Epidemiological studies report a prevalence of LDH as high as 31.9%[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With the changing patterns of modern lifestyles, LDH is increasingly affecting younger populations, thereby imposing a substantial health and economic burden on both individuals and society. Studies have shown that over 95% of LDH cases occur at the L4/5 and L5/S1 levels[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Although the exact pathophysiological mechanism remains unclear, impaired spinal stability has been recognized as a major contributing factor[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to Panjabi\u0026rsquo;s[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] three-subsystem model of spinal stability, the integrity of the spine is maintained through the coordinated interaction of the passive subsystem (vertebrae, intervertebral discs, etc.), the active subsystem (paraspinal muscles), and the neural control subsystem. Dysfunction or impairment in any of these components can compromise spinal equilibrium and trigger a cascade of clinical manifestations. The paraspinal muscles play a pivotal role in sustaining spinal stability[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In LDH, the disruption of spinal biomechanics leads to increased compensatory loading on these muscles. Chronic mechanical stress may induce degenerative changes in paraspinal muscles, further aggravating spinal instability and ultimately creating a vicious cycle of dysfunction[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough conventional imaging modalities such as X-ray and CT are widely used and provide rapid acquisition, they have limited capability in accurately quantifying the microstructural characteristics of paraspinal muscles[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Additionally, ionizing radiation restricts their utility in long-term follow-up and early lesion surveillance. In contrast, magnetic resonance imaging (MRI), with its superior soft tissue resolution and contrast, is considered the gold standard for assessing the morphology and composition of paraspinal muscles[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In recent years, emerging techniques such as diffusion tensor imaging (DTI) and T2 mapping have offered novel insights into the microstructural evaluation of paraspinal muscles. DTI allows tracking of water molecule diffusion, enabling detection of structural alterations and visualization of muscle fiber orientation via tractography[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. T2 mapping quantitatively measures transverse relaxation time (T2 value), which reflects tissue water content, collagen fiber organization, and other microstructural features[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Elevated T2 values have been associated with muscle edema[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], while the apparent diffusion coefficient (ADC) reflects the degree of water diffusion restriction[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, reduced fractional anisotropy (FA) indicates disorganization of fiber orientation, which may relate to neural dysfunction or chronic degeneration[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, the exact pathophysiological implications of these MRI parameters and their dynamic changes in LDH remain incompletely understood. The segment-specific patterns of paraspinal muscle degeneration and their interaction with LDH pathology require further investigation.\u003c/p\u003e \u003cp\u003eTherefore, this study employed multiparametric MRI, including T2, ADC, and FA values, to analyze key lumbar segments (L3/4\u0026ndash;L5/S1) with the following objectives: (1) to quantify segment-specific microstructural alterations of paraspinal muscles and compare degeneration patterns between LDH patients and healthy individuals; (2) to establish associations between MRI-derived parameters and clinical measures such as the Numeric Pain Rating Scale (NPRS) and Oswestry Disability Index (ODI); and (3) to identify imaging biomarkers capable of distinguishing LDH patients from healthy controls. Through this comprehensive analysis, we aim to enhance the understanding of paraspinal muscle pathology in LDH and provide a scientific foundation for personalized diagnosis and longitudinal monitoring.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e This study was approved by the Ethics Committee of the Affiliated Hospital of Guizhou Medical University (Approval No. [2024]240). From January to December 2024, a total of 118 participants were prospectively recruited at the Affiliated Hospital of Guizhou Medical University. Inclusion criteria for the LDH group were as follows: (1) intervertebral disc herniation at the L3/4 to L5/S1 levels confirmed by MRI[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; (2) no history of lumbar spine surgery; and (3) age between 20 and 70 years, regardless of sex. Exclusion criteria included: (1) lumbar spondylolisthesis\u0026thinsp;\u0026gt;\u0026thinsp;3 mm on MRI; (2) spinal fractures or deformities (e.g., scoliosis\u0026thinsp;\u0026gt;\u0026thinsp;10\u0026deg;); (3) history of lumbar spine surgery; (4) spinal tuberculosis; (5) history of malignancy; (6) history of rheumatic diseases; (7) history of infection; and (8) contraindications to MRI. Healthy volunteers who were willing to participate and met the same exclusion criteria were concurrently recruited as controls. 18 individuals were excluded due to incomplete imaging data or presence of alternative causes of sciatica. A total of 100 participants were finally included in the study. All participants were informed of the purpose of the examinations and provided written informed consent.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMRI Acquisition\u003c/h3\u003e\n\u003cp\u003eAll examinations were performed using a GE Discovery 750W 3.0T MRI scanner (HDxt, GE Healthcare, Milwaukee, WI, USA). The imaging range extended from the L3/L4 to L5/S1 intervertebral discs. The scanning protocol included sagittal T2-weighted imaging (T2WI), axial T2WI, T2 mapping, and diffusion tensor imaging (DTI). Detailed MRI sequences and acquisition parameters are summarized in 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\u003eAll parameters for scanned MRI sequences\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT2WI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT2WI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT2 mapping\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDTI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcquisition orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSagittal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAxial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAxial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAxial\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTR (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTE (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFOV (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300 \u0026times; 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 \u0026times; 220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e420 \u0026times; 420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e240 \u0026times; 240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlice thickness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterslice gap (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlip angle(\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatrix\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256 \u0026times; 256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e256 \u0026times; 256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eb-values(s.mm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBandwidth(Hz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcquisition time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1min21s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1min15s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4min10s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8min20s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eImage Processing\u003c/h3\u003e\n\u003cp\u003eOriginal T2 mapping and DTI images were processed using the ADW 4.6 workstation (GE Discovery 750W MRI system). Regions of interest (ROI) measuring 65\u0026ndash;80 mm\u0026sup2; were manually placed in the central portion of the paraspinal muscles, carefully avoiding inclusion of vessels, fascia, and surrounding intermuscular fat (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Quantitative measurements were independently performed by two radiologists, each with three years of experience in musculoskeletal imaging. The average of their measurements was used as the final data.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eSeverity scoring criteria\u003c/h3\u003e\n\u003cp\u003eFunctional impairment was assessed using the ODI, with higher scores indicating greater disability severity[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Pain intensity was quantified using the NPRS[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Both instruments have demonstrated strong validity, responsiveness, and reliability for evaluating low back pain and musculoskeletal pathology[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using Jamovi software (version 2.3.28.0) and R software (version 4.3.1). The Shapiro\u0026ndash;Wilk test was used to assess the normality of continuous variables. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median with interquartile range (1st quartile, 3rd quartile). Normally distributed data were compared using independent-samples t-tests, while non-normally distributed data were analyzed using the non-parametric Mann\u0026ndash;Whitney U test. Categorical variables were compared using the chi-square test. Given the age differences between the LDH and control groups, age was included as a covariate in the analysis of covariance (ANCOVA). Partial Spearman correlation analysis was performed to evaluate the associations between quantitative imaging parameters and ODI and NPRS. Stepwise multiple linear regression analysis was conducted to identify clinical and imaging variables independently associated with ODI and NPRS. Logistic regression analyses were used to construct predictive models for LDH risk. Nomograms were generated to visualize the models. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of various parameters, calculating the area under the curve (AUC). Calibration curves and decision curve analysis (DCA) were used to evaluate model agreement and clinical utility. Statistical significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eThe study group included 53 participants, while the control group comprised 47 participants, totaling 100 individuals. The mean age of the study group was 48.57\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06 years, which was significantly higher than that of the control group (41.89\u0026thinsp;\u0026plusmn;\u0026thinsp;13.10 years; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). There were no significant differences between the groups in terms of sex distribution, height, weight, or body mass index (BMI) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\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=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\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\u003eStudy group (n\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003e48.57\u0026thinsp;\u0026plusmn;\u0026thinsp;12.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.89\u0026thinsp;\u0026plusmn;\u0026thinsp;13.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (female / male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 / 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 / 27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.590\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\u003e163.98\u0026thinsp;\u0026plusmn;\u0026thinsp;7.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.839\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\u003e63.98\u0026thinsp;\u0026plusmn;\u0026thinsp;11.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.79\u0026thinsp;\u0026plusmn;\u0026thinsp;10.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.935\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\u003e23.96\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*: \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eAnalysis of Covariance of Paraspinal Muscle T2, FA, and ADC Values Between the Study and Control Groups\u003c/b\u003e \u003c/p\u003e \u003cp\u003eT2 values were generally higher in the study group compared to the control group. However, the differences were not statistically significant, even in the most affected segments, particularly in the erector spinae (ES) and multifidus (MF) at the L4/5 and L5/S1 levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of T2 value between study group and control group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.59\u0026thinsp;\u0026plusmn;\u0026thinsp;4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.10\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.87\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e42.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e42.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e45.79\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e44.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e45.72\u0026thinsp;\u0026plusmn;\u0026thinsp;5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e44.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e45.73\u0026thinsp;\u0026plusmn;\u0026thinsp;5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e45.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e42.04\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.63\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.41\u0026thinsp;\u0026plusmn;\u0026thinsp;4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e40.11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e40.33\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.520\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.73\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.97\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt the L4/5 level, the FA values of bilateral ES were significantly lower in the study group than in the control group (0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 vs. 0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 and 0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 vs. 0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of FA between study group and control group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe ADC values in the study group were significantly higher than those in the control group at the bilateral ES at the L4/5 level (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), as well as in the right ES and bilateral MF at the L5/S1 level (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating statistically significant differences (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of ADC between study group and control group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\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\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0\u0026thinsp;.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.048\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePartial Correlation Analysis Between T2, FA, and ADC Values and Clinical Assessments\u003c/h3\u003e\n\u003cp\u003eIn the ES, the ADC values of both sides at the L4/5 level were significantly positively correlated with the ODI (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.337, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.225, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively). Conversely, the right-sided ADC value at L4/5 showed a significant negative correlation with the NPRS (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = \u0026minus;\u0026thinsp;0.284, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In the MF, the T2 value of the right side at the L3/4 level was significantly positively correlated with NPRS (\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e = 0.225, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of T2, FA, and ADC values at bilateral paraverteral muscles with ODI and NPRS Scores\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMuscle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNPRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eODI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003es\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e 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\u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.035\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL3/4_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL3/4_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL4/5_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eL5/S1_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStepwise Multiple Linear Regression Analysis of the Influence of Clinical Assessments and Imaging Parameters\u003c/h2\u003e \u003cp\u003eStepwise multiple linear regression analysis revealed that the T2 value of the left MF at the L4/5 level was significantly positively associated with NPRS scores (R\u0026sup2; = 0.690, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Age was the strongest predictor of ODI scores (R\u0026sup2; = 0.598, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating a significant positive correlation between increasing age and greater functional impairment. LDH was a significant predictor in both models (NPRS: R\u0026sup2; = 0.714, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011; ODI: R\u0026sup2; = 0.634, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of multiple linear regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\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\u003eL4/5-T2-MF_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e182.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eDependent Variable: NPRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;0\u0026thinsp;.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.006\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eDependent Variable: ODI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e*: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **: \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eModeling And Performance Evaluation\u003c/h2\u003e \u003cp\u003eParameters with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate logistic regression analysis, along with relevant clinical variables, were included in the multivariate logistic regression model. The multivariate analysis identified age, the T2 value of the right erector spinae at the L3/4 level (L3/4-T2_ES_r), and the ADC value of the right erector spinae at the L5/S1 level (L5/S1-ADC_ES_r) as independent risk factors for LDH (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.008\u0026ndash;1.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3/4-T2_ES_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.070\u0026ndash;1.526\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1-ADC_ES_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.537\u0026ndash;95.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eROC curves were generated using both the combined variables from the multivariate model and the individual predictors identified through univariate logistic regression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and corresponding performance metrics were summarized (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The combined model demonstrated the best predictive performance, with an AUC of 0.772 (95% CI: 0.678\u0026ndash;0.867) and a Youden index of 0.627. Among individual predictors, L5/S1-ADC_ES_r showed the highest diagnostic performance, with an AUC of 0.733 (95% CI: 0.627\u0026ndash;0.838).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary table of performance metrics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYouden Index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3/4-T2_ES_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.569\u0026ndash;0.786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4/5-ADC_ES_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.611\u0026ndash;0.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4/5-ADC_ES_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.582\u0026ndash;0.830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1-ADC_ES_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.627\u0026ndash;0.838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1-ADC_ES_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.541\u0026ndash;0.773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1-ADC_MF_r\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.507\u0026ndash;0.737\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1-ADC_MF_l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.523\u0026ndash;0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.678\u0026ndash;0.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA nomogram was constructed based on the multivariate logistic regression model. As shown in the nomogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), for a hypothetical 55-year-old patient (age corresponding to 20 points), with an L3/4-T2_ES_r value of 50 (60 points) and an L5/S1-ADC_ES_r value of 1.1 (40 points), the total score was 120 points, corresponding to an estimated LDH risk of approximately 80%. Calibration and decision curve analyses demonstrated good agreement and clinical applicability of the nomogram model (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis prospective cohort study delineated the segment-specific patterns of microstructural degeneration in the paraspinal muscles of patients with LDH. Quantitative analysis revealed that, compared with healthy controls, LDH patients exhibited significantly reduced FA in the bilateral ES muscles at the L4/5 level (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), along with significantly elevated ADC values in the bilateral ES at L4/5, the right ES at L5/S1, and the bilateral MF (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Notably, no significant group differences were observed in the T2 values of paraspinal muscles across the evaluated lumbar segments (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), suggesting that LDH-related paraspinal muscle degeneration may follow a pathophysiological trajectory distinct from that of other degenerative spinal conditions. Two possible explanations may account for this discrepancy: First, age-related confounding may accelerate fibrotic processes, thereby masking the influence of inflammatory edema on T2 values. Previous studies have indicated that inflammation or edema is typically associated with elevated T2 signals[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, in patients with chronic low back pain, gene expression related to paraspinal muscle fibrosis has been found to be markedly upregulated[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Since the degree of fibrosis is negatively correlated with T2 values[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], it is plausible that fibrosis may offset the T2-elevating effects of edema, resulting in flattened T2 signal changes. Second, the lack of significant findings may reflect limited sensitivity of current MRI sequences in detecting subclinical pathological changes. Future investigations integrating multimodal imaging with histological validation are warranted to further elucidate these mechanisms.\u003c/p\u003e \u003cp\u003eMultiple linear regression analysis identified age as the primary predictor of ODI scores (R\u0026sup2; = 0.598, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), underscoring the pivotal role of aging in the progression of paraspinal muscle degeneration. This finding aligns with the conclusions reported by Valentin[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Partial correlation analysis further demonstrated a positive association between ADC values at the L4/5 level and both NPRS and ODI scores, suggesting a direct and quantifiable relationship between paraspinal microstructural alterations and the severity of clinical symptoms. Although previous studies have associated reduced ADC values with fibrotic changes[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], the present findings indicate that elevated ADC may reflect early alterations in tissue hydration or acute inflammatory responses. This discrepancy could be attributed to the heterogeneous pathological stages of LDH\u0026mdash;acute stages are typically dominated by inflammatory exudation[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], while chronic stages are characterized by fibrosis[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These observations suggest that dynamic monitoring of ADC values may serve as a potential imaging biomarker for disease staging in LDH.\u003c/p\u003e \u003cp\u003eMoreover, this study further advances the understanding of paraspinal muscle degeneration by incorporating the perspective of spatial heterogeneity. The L4/5 and L5/S1 segments, which bear the greatest biomechanical load within the lumbar spine[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], exhibited a concordant pattern of decreased FA and increased ADC values in both the erector spinae and multifidus muscles, indicating microstructural abnormalities within these regions. Such alterations may compromise the dynamic stability of the spine, leading to imbalanced stress distribution across intervertebral discs[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These imaging findings provide evidence supporting the existence of a positive feedback loop involving degeneration, biomechanical imbalance, and symptom escalation. Collectively, these results not only reinforce the theoretical framework of \"neurodegeneration\u0026ndash;inflammatory microenvironment interaction\"[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], but also challenge the traditional unidimensional hypothesis of mechanical compression[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLogistic regression analysis identified age, the T2 value of the right erector spinae at the L3/4 level (L3/4-T2_ES_r), and the ADC value of the right erector spinae at the L5/S1 level (L5/S1-ADC_ES_r) as significant risk factors for LDH. Among all paraspinal imaging parameters, ROC curve analysis showed that L5/S1-ADC_ES_r had the highest diagnostic performance (AUC\u0026thinsp;=\u0026thinsp;0.733). When combined with age, the diagnostic performance improved further, yielding an AUC of 0.772. Further validation through logistic regression confirmed that both L5/S1-ADC_ES_r (AUC\u0026thinsp;=\u0026thinsp;0.703) and age (OR\u0026thinsp;=\u0026thinsp;1.058) were independent predictors of LDH. Notably, for every unit increase in ADC, the risk of LDH increased by approximately 12-fold (OR\u0026thinsp;=\u0026thinsp;12.097, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018), highlighting the potentially critical role of paraspinal microstructural abnormalities in LDH pathogenesis. Nomogram analysis revealed that L5/S1-ADC_ES_r contributed the most to the overall risk prediction model. This supports the hypothesis that elevated ADC may reflect extracellular matrix remodeling secondary to blood\u0026ndash;nerve barrier disruption[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u0026mdash;a microenvironmental alteration likely to precede macroscopic structural degeneration[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Therefore, integrating age with L5/S1-ADC_ES_r into a comprehensive risk stratification framework may be valuable for early clinical decision-making. Specifically, individuals over 45 years of age with L5/S1-ADC_ES_r\u0026thinsp;\u0026gt;\u0026thinsp;1.5 \u0026times; 10⁻\u0026sup3; mm\u0026sup2;/s should be prioritized for targeted core muscle strengthening programs to delay degenerative progression.\u003c/p\u003e \u003cp\u003eAlthough this study established a relatively effective risk prediction model for LDH, future work could enhance its performance by incorporating additional imaging parameters\u0026mdash;such as fat fraction\u0026mdash;to construct a multidimensional evaluation framework capable of quantifying the heterogeneity of muscle degeneration. Moreover, the application of advanced machine learning algorithms, such as random forests or neural networks, may further improve predictive accuracy by capturing complex nonlinear interactions. In parallel, future studies could integrate quantitative ADC values into finite element models to simulate the dynamic impact of muscle degeneration on intervertebral disc stress distribution. Such simulations may contribute to refining surgical indications and developing individualized rehabilitation strategies. In summary, this study not only underscores the value of multiparametric MRI in the assessment of LDH but also provides imaging biomarker\u0026ndash;based evidence to support personalized clinical decision-making. Furthermore, it lays a data-driven foundation for optimizing dynamic monitoring and intervention strategies targeting paraspinal muscle degeneration.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, the relatively small sample size may limit the generalizability of the predictive model. Due to the limited cohort size, we were unable to perform stratified analyses based on variables such as age, occupation, disease duration, or the severity of disc herniation, which may influence paraspinal muscle degeneration. It is plausible that occupational load and disease chronicity could lead to structural alterations in the paraspinal muscles. In future studies, we plan to expand the sample size and conduct longitudinal follow-up to assess the predictive value of imaging parameters for disease progression. Second, the study relied solely on imaging-derived parameters, without incorporating multidimensional data such as biomechanical metrics or metabolomics, which may have led to residual confounding. Lastly, the ROI for paraspinal muscles were manually delineated on axial MRI images, which introduces potential measurement bias. To enhance the objectivity and reproducibility of data acquisition, future research should explore the integration of AI-based automated segmentation techniques, which may reduce systematic errors associated with manual ROI definition through standardized image processing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study utilized quantitative MRI to assess structural changes in the paraspinal muscles and demonstrated that T2 values, ADC, and FA are effective biomarkers for characterizing muscle status in patients with LDH. These imaging parameters showed significant associations with pain intensity and functional impairment. A predictive model based on multivariate logistic regression was further developed and visualized using a nomogram to enable individualized risk assessment. The proposed model offers a non-invasive and objective imaging-based approach for the early diagnosis and precise management of LDH, highlighting its promising potential for clinical translation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the declaration of Helsinki. This study was conducted with approval from the Ethics Committee of The Affiliated Hospital of Guizhou Medical University (Approval No. [2024]240). A written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Science \u0026amp; Technology Projects of Guizhou Province of China (Grant/Award Number: ZK[2023] General 354);\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design of the research: X D; Acquisition of data: M H; Analysis and interpretation of the data: M H, Q D, Y J, C T; Statistical analysis: M H; Writing of the manuscript: M H, Q D; Critical revision of the manuscript for intellectual content: X D; All authors read and approved the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to thank all of the participants, the staff, and the other study investigators for their valuable contributions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDeyo RA, Mirza SK. Herniated Lumbar Intervertebral Disk. N Engl J Med. 2016;374:1763\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, He T, Liu J, Tai J, Wang B, Zhang L, et al. Revealing the Immune Infiltration Landscape and Identifying Diagnostic Biomarkers for Lumbar Disc Herniation. Front Immunol. 2021;12:666355.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun B-L, Zhang Y, Zhang N, Xiong X, Zhong Y-X, Xing K, et al. Prevalence of lumbar disc herniation in populations with different symptoms based on magnetic resonance imaging study. J Clin Neurosci. 2024;129:110839.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Khawaja DO, Mahasneh T, Li JC. Surgical treatment of far lateral lumbar disc herniation: a safe and simple approach. J Spine Surg. 2016;2:21\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Wang Y, Li Y, Wang C, Qie S. A diagnostic model of nerve root compression localization in lower lumbar disc herniation based on random forest algorithm and surface electromyography. Front Hum Neurosci. 2023;17:1176001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Qaraghli MI, De Jesus O. Lumbar disc herniation. Statpearls. Treasure Island. (FL): StatPearls Publishing; 2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJin L, Yin Y, Chen W, Zhang R, Guo J, Tao S, et al. Role of the lumbosacral transition vertebra and vertebral lamina in the pathogenesis of lumbar disc herniation. Orthop Surg. 2021;13:2355\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePanjabi MM. The Stabilizing System of the Spine. Part I. Function, Dysfunction, Adaptation, and Enhancement: Journal of Spinal Disorders. 1992;5:383\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLarivi\u0026egrave;re C, Henry SM, Preuss R. Structural remodeling of the lumbar multifidus, thoracolumbar fascia and lateral abdominal wall perimuscular connective tissues: A search for its potential determinants. J Anat. 2021;238:536\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Chen Y, Liu Y, Hai Y, Zhang X, Guan L, et al. Changes in Paraspinal Muscles and Facet Joints after Minimally Invasive Posterior Lumbar Interbody Fusion Using the Cortical Bone Trajectory Technique: A Prospective Study. Pain Res Manage. 2022;2022:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBergmark A. Stability of the lumbar spine: A study in mechanical engineering. Acta Orthop Scand. 1989;60:1\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan H, Dong L, Zhang O, Wang X, Chen Z, Li Y, et al. A comparison of interferential current efficacy in elderly intervertebral disc degeneration patients with or without sarcopenia: a retrospective study. BMC Musculoskelet Disord. 2024;25:214.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi C, Dang C, Liu G, Chen L, Zhang J, Li J, et al. Secondary damage in left-sided frontal white matter detected by diffusion tensor imaging is correlated with executive dysfunction in patients with acute infarction at the ipsilateral posterior corona radiata. Eur J Med Res. 2014;19:44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEngelke K, Chaudry O, Gast L, Eldib MAb, Wang L, Laredo J-D, et al. Magnetic resonance imaging techniques for the quantitative analysis of skeletal muscle: State of the art. J Orthop Translation. 2023;42:57\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHodges PW, Bailey JF, Fortin M, Batti\u0026eacute; MC. Paraspinal muscle imaging measurements for common spinal disorders: review and consensus-based recommendations from the ISSLS degenerative spinal phenotypes group. Eur Spine J. 2021;30:3428\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang F, Fang S, Li J, Yuan L, Hou B, Zhu J, et al. Correlation analysis of quantitative MRI measurements of thigh muscles with histopathology in patients with idiopathic inflammatory myopathy. Eur Radiol Exp. 2023;7:51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCameron D, Reiter DA, Adelnia F, Ubaida-Mohien C, Bergeron CM, Choi S, et al. Age‐related changes in human skeletal muscle microstructure and architecture assessed by diffusion‐tensor magnetic resonance imaging and their association with muscle strength. Aging Cell. 2023;22:e13851.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGassert FT, Kufner A, Gassert FG, Leonhardt Y, Kronthaler S, Schwaiger BJ, et al. MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures. Osteoporos Int. 2022;33:487\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouhsina N, Decante C, Hardel J-B, Rouleau D, Abadie J, Hamel A, et al. Comparison of MRI T1, T2, and T2* mapping with histology for assessment of intervertebral disc degeneration in an ovine model. Sci Rep. 2022;12:5398.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDas T, Roos JCP, Patterson AJ, Graves MJ, Murthy R. T2-relaxation mapping and fat fraction assessment to objectively quantify clinical activity in thyroid eye disease: an initial feasibility study. Eye. 2019;33:235\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKuo GP, Carrino JA. Skeletal muscle imaging and inflammatory myopathies. Curr Opin Rheumatol. 2007;19:530\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArpan I, Forbes SC, Lott DJ, Senesac CR, Daniels MJ, Triplett WT, et al. \u003cem\u003eT\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e mapping provides multiple approaches for the characterization of muscle involvement in neuromuscular diseases: a cross-sectional study of lower leg muscles in 5\u0026ndash;15‐year‐old boys with Duchenne muscular dystrophy. NMR Biomed. 2013;26:320\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeller S, Yamamura J, Sedlacik J, Wang ZJ, Gebert P, Starekova J, et al. Diffusion tensor imaging combined with T2 mapping to quantify changes in the skeletal muscle associated with training and endurance exercise in competitive triathletes. Eur Radiol. 2020;30:2830\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis \u0026ndash; a technical review. NMR Biomed. 2002;15:456\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiener H-C, Hankey GJ. Primary and Secondary Prevention of Ischemic Stroke and Cerebral Hemorrhage. J Am Coll Cardiol. 2020;75:1804\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoivunen K, Widbom-Kolhanen S, Pernaa K, Arokoski J, Saltychev M. Reliability and validity of Oswestry Disability Index among patients undergoing lumbar spinal surgery. BMC Surg. 2024;24:13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmjad F, Khalid A. Comparative effects of Bowen therapy and tennis ball technique on pain and functional disability in patients with thoracic myofascial pain syndrome. J Orthop Surg Res. 2023;18:895.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePontes-Silva A, Dibai-Filho AV, Costa De Jesus SF, De Santos LA, Bassi-Dibai D, De Fidelis CA, et al. The best structure of the Tampa Scale for Kinesiophobia for patients with chronic low back pain has two domains and nine items. Clin Rehabil. 2023;37:407\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagy Z, Kiss N, Szigeti M, \u0026Aacute;fra J, Lekka N, Misik F, et al. Construct validity of the Hungarian Version of the Patient-Reported Outcomes Measurement Information System-29 Profile Among Patients with Low Back Pain. World Neurosurg. 2024;181:e55\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRan J, Ji S, Morelli JN, Wu G, Li X. T2 mapping in dermatomyositis/polymyositis and correlation with clinical parameters. Clinical Radiology. 2018;73:1057.e13-1057.e18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeng F, Xu H, Song Y, Xu K, Li S, Cai X, et al. Utilization of T1-Mapping for the pelvic and thigh muscles in Duchenne Muscular Dystrophy: a quantitative biomarker for disease involvement and correlation with clinical assessments. BMC Musculoskelet Disord. 2022;23:681.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahidi B, Fisch KM, Gibbons MC, Ward SR. Increased Fibrogenic Gene Expression in Multifidus Muscles of Patients With Chronic Versus Acute Lumbar Spine Pathology. Spine. 2020;45:E189\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIdilman IS, Celik A, Savas B, Idilman R, Karcaaltincaba M. The feasibility of T2 mapping in the assessment of hepatic steatosis, inflammation, and fibrosis in patients with non-alcoholic fatty liver disease: a preliminary study. Clinical Radiology. 2021;76:709.e13-709.e18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValentin S, Licka T, Elliott J. Age and side-related morphometric MRI evaluation of trunk muscles in people without back pain. Man Therap. 2015;20:90\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElhawary M, Elmansy M, Ali K, Abdallah E, Razek A, Barakat T, et al. Diffusion tensor magnetic resonance imaging in the grading of liver fibrosis associated with congenital ductal plate malformations. Pol J Radiol. 2023;88:135\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrisby H, Olmarker K, Larsson K, Nutu M, Rydevik B. Proinflammatory cytokines in cerebrospinal fluid and serum in patients with disc herniation and sciatica. Eur Spine J. 2002;11:62\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRisbud MV, Shapiro IM. Role of cytokines in intervertebral disc degeneration: pain and disc content. Nat Rev Rheumatol. 2014;10:44\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgha O, Mueller-Immergluck A, Liu M, Zhang H, Theologis AA, Clark A, et al. Intervertebral disc herniation effects on multifidus muscle composition and resident stem cell populations. JOR Spine. 2020;3:e1091.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi D, Wang L, Wang Z, Li C, Yuan S, Tian Y, et al. Age-related radiographic parameters difference between the degenerative lumbar spinal stenosis patients and healthy people and correlation analysis. J Orthop Surg Res. 2022;17:475.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMister WJ. Rupture of the intervertebral disc with involvement of the spinal canal. N Engl J Med. 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReis C, Wang Y, Akyol O, Ho W, Ii R, Stier G, et al. What\u0026rsquo;s New in Traumatic Brain Injury: Update on Tracking, Monitoring and Treatment. IJMS. 2015;16:11903\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo M, Liu Y, Liu WV, Ma M, Liao Y, Chen S, et al. Quantitative magnetic resonance imaging of paraspinal muscles for assessing chronic non-specific low back pain in young adults: a prospective case-control study. Eur Spine J. 2024;33:4544\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Multimodal MRI, lumbar disc herniation, paraspinal muscles, predictive model, nomogram","lastPublishedDoi":"10.21203/rs.3.rs-6777748/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6777748/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMicrostructural changes in the paravertebral muscles due to lumbar disc herniation (LDH) remain unclear. This study aims to quantitatively assess paraspinal muscle parameters in LDH patients using MRI and to develop a multivariate imaging-based predictive model.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 100 participants were prospectively enrolled, including 53 patients with LDH and 47 healthy controls. This cross-sectional study compared demographic and paraspinal muscle imaging characteristics between groups. All subjects underwent T2 mapping and diffusion tensor imaging (DTI) using a 3.0T MRI scanner. Pain and functional status were assessed using the Numeric Pain Rating Scale (NPRS) and Oswestry Disability Index (ODI). Group comparisons were performed using ANCOVA to adjust for confounders. Partial Spearman correlation evaluated associations between imaging metrics and clinical scores. Stepwise multiple linear regression identified predictors of NPRS and ODI, while logistic regression determined independent LDH risk factors and construction of a nomogram-based predictive model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe LDH group had a significantly higher mean age than controls (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023), with no significant differences in other baseline characteristics (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). ANCOVA revealed lower fractional anisotropy (FA) values in the bilateral erector spinae (ES) at L4/5 and higher apparent diffusion coefficient (ADC) values in the bilateral ES at L4/5, right ES at L5/S1, and bilateral multifidus (MF) in the LDH group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 or \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Partial correlation analysis showed that T2 values of specific ES and MF segments were positively associated with ODI and NPRS scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multiple regression identified the L4/5 left MF T2 value as the strongest predictor of NPRS and age as the main predictor of ODI (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Logistic regression confirmed age, the L3/4 right ES T2 value, and the L5/S1 right ES ADC as independent LDH predictors. The multivariate model yielded the best predictive performance (AUC\u0026thinsp;=\u0026thinsp;0.772), with nomogram analysis highlighting the L5/S1 right ES ADC as the most influential parameter.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eParaspinal muscle imaging parameters are effective markers for evaluating muscle status and disease burden in LDH. Multivariate logistic regression identified age, the T2 value of the right erector spinae at L3/4, and the ADC value at L5/S1 as LDH risk factors.\u003c/p\u003e","manuscriptTitle":"Quantitative MRI Assessment of Paraspinal Muscles and Construction of a Predictive Model for Lumbar Disc Herniation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-01 08:02:22","doi":"10.21203/rs.3.rs-6777748/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"39fa363e-4c5a-4a05-8008-bad4652209a7","owner":[],"postedDate":"July 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-22T11:08:20+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-01 08:02:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6777748","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6777748","identity":"rs-6777748","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}