Analysis of the Influence of Myodural Bridge Complex Classification on Cervical Spondylotic Myelopathy Based on Magnetic Resonance Imaging

Analysis of the Influence of Myodural Bridge Complex Classification on Cervical Spondylotic Myelopathy Based on Magnetic Resonance Imaging | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of the Influence of Myodural Bridge Complex Classification on Cervical Spondylotic Myelopathy Based on Magnetic Resonance Imaging Hao-Song Yin, Cong Liu, Nan Zheng, Sheng-Bo Yu, Yan-Yan Chi, Jian-Fei Zhang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4721717/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To classify myodural bridge complex (MDBC) in the posterior atlanto-occipital interspace (PAOiS) and posterior atlanto-axial interspace (PAAiS) in cervical spondylotic myelopathy (CSM) based on Magnetic Resonance Imaging (MRI), analyzing the effects of sex, age, spinal compression ratio(CR), space available for the cord༈SAC༉, and cervical sagittal balance༈CSB) parameters on the classification of MDBC in CSM, the aim is to provide imaging evidence for the functional research and clinical application of MDBC. Methods Imaging data from 96 patients with CSM and 104 healthy adults were retrospectively selected, were evaluated by univariate analysis of factors and multi-factor analysis of factor Influencing the MRI Classification of MDBC in CSM . Results The results showed significantly lower proportions of Type A and Type B MDBC in the CSM group than in the control group (P < 0.001), the proportions of type C and type D MDBC were greater than those in the control group (P < 0.05), and have a statistically significant correlation with age (P 0.05). Types C and D predominated in the MDBC classification in CSM, regardless of sex and age (P > 0.05). Parameters such as the mean subaxial cervical space available for the cord (MSCSAC), and mean subaxial cervical compression ration (MSCCR) significantly influenced the MDBC classification in CSM (P < 0.05), particularly for Types C and D. Sex and CSB did not affect MDBC classification. Conclusion The MDBC classification in CSM predominantly showed Type C and Type D, regardless of age. MSCSAC and MSCCR are influencing factors of MDBC classification in CSM, particularly affecting Type C and Type D MDB, regardless of sex and CSB. Myodural bridge complex Cervical spondylotic myelopathy Imaging classification Compression ration Space available for the cord Cervical sagittal balance Magnetic resonance imaging Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Cervical spondylotic myelopathy (CSM)[1,2]is the most prevalent spinal cord disease in adults, characterized by neurological impairments in limbs, trunk, and sphincter muscles, along with atypical symptoms like headaches[3]. MRI technology enables precise measurement and spatial assessment of spinal cord compression in CSM, elucidating potential correlations between symptom severity and treatment prognosis[4,5,6]. The myodural bridge complex (MDBC), composed of fused myodural bridge (MDB) fibers from various sources, acts synergistically[7]. Feng X et al.[8]classified MDBC into Types A, B, C, and D based on its visibility in the PAOiS and PAAiS, correlating type characteristics with degenerative changes in the cervical spine. Degenerative changes in the cervical spine of patients with CSM often involve spinal canal narrowing and disc protrusion that compress the spinal cord. Parameters such as spinal cord compression ratio (CR)[9], space available for the cord (SAC)[10], and cervical sagittal balance (CSB)[11]are important in assessing the severity of CSM and may affect the categorization into MDBC types. This study utilizes MRI technology to analyze and measure CR, SAC, and CSB values in CSM, identifying factors that influence the classification of CSM into MDBC types. These findings provide a imaging foundation for studying the functional aspects and clinical implications of MDBC. Material and Methods Study participants Approval for this study was obtained from the Ethics Committee for Research of Basic Medical College of Dalian Medical University. 104 healthy adults were served as the control group including 60 males and 40 females (age range from 20 to 69 years with an average of 41.16 ± 11.12 years) and 96 cases diagnosed with CSM were served as the patient group(age range from 20 to 69 years with an average of 38.78 ± 13.88 years) participated in this study Study methods Scanning equipment and parameters. 1.5T MRI scanner (HDxt, GE Healthcare, USA) was used with a neck coil phased array. Sagittal T2WI parameters: TR: 2740.0 ms, TE: 120.0ms, number of slices: 11, slice thickness: 3 mm, matrix: 256 × 256, FOV: 240 mm × 240 mm. MRI evaluation criteria for MDBC classification. Subjects were scanned in the supine position, utilizing a neck phased-array coil that covered the occipital and sub-occipital regions. MRI classification method of Feng X et al. for MDBC was employed[8]. On sagittal T2WI of the cervical spine, MDBC appears as areas of low signal intensity. High signal intensity indicates the presence of fat within the PAOiS and PAAiS, while flow void signals suggest the presence of blood vessels. MDBC is classified into four types (Type A, Type B, Type C, and Type D) based on its location (PAOiS and PAAiS) where it connects to the dura mater and its signal characteristics (Fig. 1 ; Fig. 2: Diagram of MDBC Classification). Measurement of CSB in CSM. CSB is assessed using the techniques outlined by Permsak P et al.[11](Fig. 3 ). (1) Occiput-cervical inclination: Measurements were conducted for the occiput-cervical inclination angles at C3, C4, and C5. This angle is formed by the connection between the posterior edge of the cervical vertebrae and the McGregor line, which extends from the posterior upper side of the hard palate to the midline at the posterior end of the occipital bone. ( Figure Ia). (2) Occiput-C2 angle: The angle is formed between the McGregor line and a line parallel to the lower endplate of C2.(Figure IIb) (3) Occiput-cervical distance: The shortest distance is between the external occipital protuberance and the upper horizontal line of the spinous process of the axis vertebra (Figure IIIc). (4) Cervical lordosis measurement angle: The angle is formed by the line extending from the lower endplate of the axis vertebra to C7. Positive values indicate posterior alignment, whereas negative values indicate anterior alignment (Figure IVd). (5) High cervical sagittal axis: The horizontal distance between the center of C2 and the posterior edge of the upper endplate of C7 is measured. The center of C2 is determined at the intersection point of a diagonal line within the C2 vertebral body. Positive values indicate the center of C2 is positioned anterior to the posterior edge of the C7 endplate, whereas negative values indicate it is located posterior to the posterior edge of the C7 endplate (Figure Ve). Measurement of SAC and CR in CSM. In this study, the cervical spine was divided into five segments: C2-3, C3-4, C4-5, C5-6, and C6-7. The SAC, CR, MSCCR, and MSCSAC values were measured for each segment. (1) SAC values were measured as parameters of intervertebral disc and spinal canal volume. The calculation method involved determining the spinal cord available space in each segment, which was calculated as the horizontal sagittal diameter of the vertebral canal minus the sagittal diameter of the spinal cord. MSCSAC was then obtained by averaging SAC values from all five discs, aiming to comprehensively assess SAC values for each patient. (Fig. 4 A) (2) CR value is calculated as the spinal cord compression ratio, which is defined as the minimum sagittal diameter of the spinal cord divided by the widest transverse diameter at the same level. MSCCR is based on the average CR values from all 5 discs, aiming to comprehensively assess CR conditions for each patient. ( Fig. 4 B) Statistical analyses SPSS 27.0 was used. Descriptive statistics were applied to categorical data [n (%)], while metric data underwent normality testing using the Shapiro-Wilk test. Metric data conforming to or approximating a normal distribution was presented as mean ± SD. Differences in sex composition and MDBC type composition between control and patient groups were assessed using independent samples t-tests for age. Chi-square tests were employed to compare the distribution of MDBC types among CSM patients. ANOVA was utilized to compare normal indicators among CSM patients with different MDBC subtypes. For groups showing significant differences, pairwise comparisons were conducted using the S-N-K. Multifactorial analysis included multicategory multifactor logistic regression analysis where applicable. A significance level of P < 0.05 denoted statistical significance. Results MDBC classifcation methods in CSM A significant difference in MDBC classification was observed between the patient and control groups ( P < 0.001). Type A and B MDBCs were less prevalent in the patient group compared to the control group, with type A being the least common (6 cases, 6.1%). Conversely, type C and type D MDBC were more prevalent, with type D comprising the highest proportion (59 cases, 60.2%). Age was significantly different between the two groups ( P = 0.022), while sex was not significantly different (Table 1 ). Table 1 Comparative Analysis of Indicator Differences between Control Group and Diseased Group Indicator Classification Control group Diseased group Statistical value P value Gender Male 60(57.7) 54(55.1) 0.138 0.711 Female 44(42.3) 44(44.9) MDBC classification Type A 63(60.6) 6(6.1) 89.306 < 0.001* Type B 20(19.2) 11(11.2) Type C 12(11.5) 22(22.4) Type D 9(8.7) 59(60.2) Age (years) 44.16 ± 9.76 40.20 ± 14.34 2.305 0.022* Note: * indicates statistical significance Univariate Analysis of Factors Influencing MDBC Classification in CSM (1) There were greater proportions of CSM patients with type C and D MDBC, but the difference in sex or age was not statistically significant (P > 0.05). (Table 2 ) Table 2 Univariate Analysis of the Influence of General Data on MDBC Type Indicator Classification Type A Type B Type C Type D X 2 / F value P value Gender Male 3(3) 6(6) 10(10) 30(30) 4.768 0.90 Female 3(3) 5(5) 12(12) 29(29) Age 40.0 ± 16.05 45.64 ± 14.71 39.77 ± 15.79 39.37 ± 13.71 0.592 0.622 Note: * indicates statistical significan 2) Significant statistical differences (P < 0.01) were observed when comparing SAC values in the C4-7 segments, CR values in the C3-7 segments, and MSCSAC and MSCCR values in relation to MDBC types in CSM. However, no significant association was found between SAC values in the C2-4 segments and CR values in the C2-3 segments with MDBC (P > 0.05) (Table 3 ). 2) There was no significant association found between the classification of MDBC in CSM patients and cervical sagittal balance (CSB) parameters (P > 0.05) (Table 4 ). Table 3 Univariate Analysis of the Influence of CR and SAC Values in Cervical Spine Segments on MDBC Type Indicator Type A Type B Type C Type D X 2 / F value P value CR(C2-3) 0.57 ± 0.06 0.54 ± 0.06 0.53 ± 0.04 0.51 ± 0.06 6.422 0.15 CR(C3-4) 0.54 ± 0.07 0.49 ± 0.08 0.49 ± 0.06 0.45 ± 0.08 7.101 0.001* CR(C4-5) 0.53 ± 0.1 0.43 ± 0.07 0.47 ± 0.07 0.43 ± 0.08 7.001 0.001* CR(C5-6) 0.54 ± 0.1 0.43 ± 0.09 0.46 ± 0.08 0.42 ± 0.09 8.798 0.001* CR(C6-7) 0.55 ± 0.06 0.46 ± 0.04 0.48 ± 0.08 0.45 ± 0.12 5.37 0.002* MSCCR 0.55 ± 0.06 0.47 ± 0.06 0.49 ± 0.05 0.45 ± 0.07 12.966 < 0.001* SAC(C2-3) 5.53 ± 1.17 5.43 ± 0.6 5.76 ± 0.86 5.17 ± 1.05 7.672 0.34 SAC(C3-4) 4.9 ± 1.22 3.64 ± 0.89 3.89 ± 0.84 3.61 ± 1.06 8.039 0.21 SAC(C4-5) 4.8 ± 1.26 3.41 ± 1.31 3.6 ± 1.07 3.39 ± 0.99 8.362 <0.01* SAC(C5-6) 4.59 ± 1.33 3.27 ± 1.18 3.44 ± 1.05 3.03 ± 1.23 8.063 <0.001* SAC(C6-7) 5.68 ± 1.27 4.45 ± 1.44 4.38 ± 1.31 3.78 ± 1.67 7.865 <0.001* MSCSAC 5.14 ± 0.94 3.97 ± 0.96 4.01 ± 0.73 3.66 ± 0.94 13.632 <0.001* Note: * indicates statistical significance Table 4 Univariate Analysis of the Influence of Cervical Sagittal Parameters on MDBC Type Indicator Type A Type B Type C Type D X 2 / F value P value C3- Occipito-cervical inclination 93.76 ± 7.45 93.09 ± 7.33 91.35 ± 7.09 93.17 ± 6.77 0.634 0.595 C4-Occipito-cervical inclination 94.96 ± 7.22 91.64 ± 6.36 91.07 ± 7.25 92.17 ± 7.19 1.418 0.242 C5-Occipito-cervical inclination 97.87 ± 10 91.8 ± 8.83 93.34 ± 8.92 94.09 ± 9.17 1.467 0.229 Occipito -C2 angle 3.27 ± 9.05 5.53 ± 6.74 1.83 ± 9.93 0.66 ± 11.48 0.676 0.569 Occipito-cervical distance 28.24 ± 7.2 32.95 ± 9.08 32.17 ± 6.59 30.08 ± 7.02 1.777 0.157 Cervical lordosis measurement angle -9.79 ± 10.06 6.58 ± 10.92 6.14 ± 10.92 -5.69 ± 8.53 0.859 0.466 High cervical sagittal vertical axis 13.02 ± 8.49 13.51 ± 5.79 12.27 ± 6.79 12.14 ± 4.25 0.167 0.919 Note: * indicates statistical significance Multi-factor Analysis of Factors Influencing MDBC Classification in CSM Patients All variables, including sex, age, SAC (C2-7) values, CR (C2-7) values, MSCSAC, MSCCR values, and CSB parameters, were utilized as independent factors in a multi-factor logistic regression analysis, with MDBC type in CSM patients as the dependent variable. Type A MDBC was used as the baseline category for model establishment. The results of the multi-category multi-factor logistic regression indicated that MSCSAC and MSCCR significantly influenced the likelihood of Type C and D MDBC ( P < 0.05). Specifically, each 1 cm increase in MSCSAC was associated with reduced odds of Type C and D MDBC and increased odds of Type A MDBC. The odds ratio (OR) for Type C MDBC decreased to 0.333 times that of Type A MDBC (OR = 0.333, P = 0.016), and for Type D MDBC, it decreased to 0.483 times that of Type A MDBC (OR = 0.483, P = 0.01). Furthermore, each 1% increase in MSCCR was associated with decreased odds of Type D MDBC and increased odds of Type A MDBC. The odds ratio (OR) for Type D MDBC decreased to 0.013 times that of Type A MDBC (OR = 0.013, P = 0.008) (Table 5 ). Table 5 Multivariate and multifactorial Logistic Regression Analysis of Factors Influencing MDBC Type in Cervical Spondylosis Patients Type Factor β value P value OR value 95% CI Type B MSCSAC -0.977 0.15 0.376 0.115～1.229 MSCCR -16.146 0.085 9.722 0.01～9.346 Type C MSCSAC -1.100 0.016 * 0.333 0.136～0.813 MSCCR -10.475 0.137 2.823 0.0028～28.445 Type D MSCSAC -1.265 0.01 * 0.483 0.107～0.743 MSCCR -20.469 0.008 ** 0.013 0.0003～0.004 Note: * indicates statistical significance Dicussion Prior research has validated the feasibility of MRI-based morphological studies on MDBC[8,12,13,14,15]. A recent MRI study reaffirmed the classification of human MDBC into four types: Type A, Type B, Type C, and Type D[8]. This study is the first quantitative analysis to assess the influence of different MDBC types on CSM based on MRI. The findings revealed that Type A MDBC predominated in the normal population at 60.6%, consistent with the findings of Feng X[8]. In contrast, Type C and Type D were more prevalent in CSM patients, with Type D being the most common at 60.2%, followed by Type C at 22.4%, and Type B at 11.2%. Type A had the lowest occurrence at 6.1%. The classification of MDBC in CSM did not correlate with age or sex. Literature suggests that the pathogenesis of CSM involves tension stress transmitted to the spinal cord through the dentate ligament[16]. Changes in dural tension may affect suboccipital muscle activity through sensory pathways, potentially influencing MDB. In experiments with mice, Song X et al.[17] found that neck stiffness could lead to MDB proliferation and hypertrophy, indicating the adaptability of MDBC fibers. They hypothesized that ongoing abnormal tension from CSM might contribute to MDB growth and hypertrophy. Further investigations are necessary to explore whether Type C and Type D MDBC are implicated in the development of CSM. The CR is essential for assessing clinical symptoms and cerebrospinal fluid (CSF) flow velocity in CSM patients[9,18]. It measures spinal cord compression by comparing the spinal canal diameter to the transverse diameter of the spinal cord. A lower CR indicates more severe spinal cord injury, often leading to significant functional impairment. SAC is also crucial in CSM evaluation, predicting symptomatic spinal stenosis[10,19]. Spinal canal stenosis can impact CSF dynamics. MDBC is one of the sources of CSF dynamics[23,24], and we think that the effects of the CR and SAC values on CSF dynamics may influence MDBC. CSB is a significant risk factor in CSM, affecting muscle length changes, particularly in the suboccipital muscles, the suboccipital muscle contributes to the formation of MDBC[20,21,22]. Multi-factor analysis indicates that the MSCSAC and MSCCR values of CSM are factors influencing the MDBC MRI classification, the results on factors influencing CSM MDBC classification showed that MSCSAC and MSCCR are pivotal. In this study, the classification was affected by SAC values in the C4-7 segments, CR values in the C3-7 segments, MSCSAC, and MSCCR, but not by SAC values in the C2-4 segments or CR values in the C2-3 segments. The decreasing involvement order of CSM segments-C5-6, C6-7, C4-5, C3-4, and C2-C3[25]may explain why C2-4 segment SAC values and C2-3 CR values do not impact MDBC classification in CSM. Each 1.0 cm increase in MSCSAC was associated with a decrease in Type C and Type D MDBC incidence, while increasing Type A MDBC incidence. Type C MDBC incidence decreased to 0.33 times that of Type A MDBC, and Type D MDBC incidence decreased to 0.483 times that of Type A MDBC. Each 1.0% increase in MSCCR was associated with Type D MDBC incidence decreasing to 0.013 times that of Type A MDBC. The study underscores that the severity of cervical spinal cord compression in CSM influences variations in MDBC classification, although further research is needed to elucidate the underlying mechanisms. Research has documented that CSM correlates with imbalances in CSB parameters, including advancing age, reduced range of motion in cervical lordosis angle measurements, and decreased minimum bending angle[26](Lin T, et al . 2021). However, findings from this study indicate no association between CSM and CSB parameters. This discrepancy may be due to the study's use of static images obtained from supine MRI scans, which tend to yield false negative results. Typically, cervical lordosis is more accurately assessed using standing MRI or standing X-ray, which provide better differentiation effects[27]. Conclusion The MDBC classification in CSM showed Type C and Type D predominantly, regardless of age. MSCSAC and MSCCR are influencing factors of MDBC classification in CSM, particularly affecting Type C and Type D MDB, regardless of sex and CSB. Limitations Firstly, the limitations of conventional MRI resolution and slice thickness in this study may contribute to false negatives in detecting MDBC, potentially resulting in an increased incidence of Type A MDB. Utilizing high-resolution MRI or 3D MRI techniques could mitigate this issue. Additionally, this study gathered quantitative imaging measurements of CSM in the MDBC from static MR images, which potentially influenced the accuracy of data analysis. Future research could investigate MDBC classification in CSM with spinal cord involvement using dynamic MR sequences and appropriate post-processing methodologies. Lastly, the sample size used in this study was relatively limited. Subsequent studies could enhance reliability by expanding the sample size. Declarations Acknowledgements Not Applicable Authors’ contributions HNW, HJS, and QX contributed to the concept and design of the study. HSY, CL YPT and ZCN acquired the data. SBY, NZ, YYCand JFZ analyzed and interpreted the data. QX, HJS, SBY, and HNW conceived and illustrated the unrolled model. HSY and CL drafted the manuscript. QX, HJS, and HNW revised the manuscript critically. All authors approved and edited the manuscript. HSY and CL are co-first authors and contributed equally to the work. QX, HJS, and HNW are co-corresponding authors and contributed equally to the work. All authors read and approved the fnal manuscript. Funding Natural Science Foundation of China (32071184) Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Ethics approval and consent to participate The study has been performed in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee for Research of Basic Medical College of Dalian Medical University. All patients participated free willingly and with written informed consent to the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details 1 Department of Anatomy, College of Basic Medicine, Dalian Medical University, Dalian 116044, China 2 The 967 Hospital of the Joint Logistics Support Force, Dalian 116021, China 3 Postgraduate Training Base, the 967 Hospital of the Joint Logistics Support Force Jinzhou Medical University, Dalian 116021, China. 4 Department of Radiotherapy, the 967 Hospital of the Joint Logistics Support Force, Dalian 116021, China. References Zhang L, Cui Z, Yuan C, et al. 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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-4721717","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335743907,"identity":"b3566058-863c-4ae1-9531-c9751da6c61a","order_by":0,"name":"Hao-Song Yin","email":"","orcid":"","institution":"the 967 Hospital of the Joint Logistics Support Force Jinzhou Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hao-Song","middleName":"","lastName":"Yin","suffix":""},{"id":335743909,"identity":"f28caaba-2c77-488c-b033-8792ee7a2aaa","order_by":1,"name":"Cong Liu","email":"","orcid":"","institution":"The 967 Hospital of the Joint Logistics Support Force","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Liu","suffix":""},{"id":335743910,"identity":"b918b9c3-109f-4aa4-a200-d3198561c771","order_by":2,"name":"Nan Zheng","email":"","orcid":"","institution":"Dalian Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nan","middleName":"","lastName":"Zheng","suffix":""},{"id":335743911,"identity":"ffac5e11-d012-42ab-88d2-9201f5e285d4","order_by":3,"name":"Sheng-Bo Yu","email":"","orcid":"","institution":"Dalian Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sheng-Bo","middleName":"","lastName":"Yu","suffix":""},{"id":335743912,"identity":"2fbbddba-fcf3-44a0-a725-c8b1cf8cefc5","order_by":4,"name":"Yan-Yan Chi","email":"","orcid":"","institution":"Dalian Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan-Yan","middleName":"","lastName":"Chi","suffix":""},{"id":335743913,"identity":"7f3f79ed-5cb8-4ed7-801f-916223e4f252","order_by":5,"name":"Jian-Fei Zhang","email":"","orcid":"","institution":"Dalian Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jian-Fei","middleName":"","lastName":"Zhang","suffix":""},{"id":335743914,"identity":"09ee0f2a-232b-4b7d-a348-9ffbf44736ff","order_by":6,"name":"Yan-Ping Tian","email":"","orcid":"","institution":"The 967 Hospital of the Joint Logistics Support Force","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan-Ping","middleName":"","lastName":"Tian","suffix":""},{"id":335743916,"identity":"aa976db3-35a7-465c-84d3-01c39a4e546a","order_by":7,"name":"Zhi-Chao Ning","email":"","orcid":"","institution":"The 967 Hospital of the Joint Logistics Support Force","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhi-Chao","middleName":"","lastName":"Ning","suffix":""},{"id":335743918,"identity":"23ab7683-d91d-41d4-b2f5-530e54938aa1","order_by":8,"name":"Hao-Nan Wang","email":"","orcid":"","institution":"The 967 Hospital of the Joint Logistics Support Force","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hao-Nan","middleName":"","lastName":"Wang","suffix":""},{"id":335743925,"identity":"78c02d91-68e2-4698-893a-9cd6885557ff","order_by":9,"name":"Hong-Jin Sui","email":"","orcid":"","institution":"Dalian Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hong-Jin","middleName":"","lastName":"Sui","suffix":""},{"id":335743926,"identity":"f6df8156-9178-43fc-bab3-83562e310dca","order_by":10,"name":"Qiang Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACNv72ww8+VNjYyTMzNj5IqKghrIVP4kya4YwzacmG7cyHDR6cOUZYixxDgoE0b9thxobzbGmSD1uYiXAYw4EEAx42ZmbGZh6zisQGNgb+9u4E/FqYGw88kOBh42Nn5jG7kbhDhkHizNkNhG0xkOAB23Ij8Qwbg4FELiEtCQYSQMTYcJjHrCCxjZlILUCLgFrY0hiI0wIK5IYDCcmGzcyHJRLOHOMh6Bf5/vbDj//++28nz3+w8eOPiho5/vZe/FowAA9pykfBKBgFo2AUYAUANYJHqcOsFfUAAAAASUVORK5CYII=","orcid":"","institution":"Dalian Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-07-11 04:36:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4721717/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4721717/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62323066,"identity":"18832cf5-027f-4aea-83e9-59e648de6986","added_by":"auto","created_at":"2024-08-13 02:09:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":836376,"visible":true,"origin":"","legend":"\u003cp\u003eCraniovertebral T2WI (Sagittal View)\u003c/p\u003e\n\u003cp\u003e1. occipital bone; 2. posterior atlanto-occipital interspace (PAOiS); 3. posterior arch of the atlas; 4. posterior atlanto-axial interspace (PAAiS); 5. spinous process of the axis. the arrow indicates MDB.\u003c/p\u003e\n\u003cp\u003eA: Type A MDBC: No low-intensity MDBC connecting with the dura mater is shown in the PAOiS and PAAiS.\u003c/p\u003e\n\u003cp\u003eB: Type B MDBC: Only low-intensity MDBC connecting with the dura mater is shown in the PAOiS (arrow).\u003c/p\u003e\n\u003cp\u003eC: Type C MDBC: Only low-intensity MDBC signals connecting with the dura mater are shown in thePAAiS (arrow).\u003c/p\u003e\n\u003cp\u003eD: Type D MDBC: A low signal intensity of the MDBC connecting with the dura mater is shown simultaneously in the PAOiS and PAAiS (arrow).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4721717/v1/971831a4e26c332d9dad3c26.png"},{"id":62323069,"identity":"7c2afeb0-4e43-49b3-aaa3-1d8044cf3fdd","added_by":"auto","created_at":"2024-08-13 02:09:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1384604,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the MDBC classification (sagittal view)\u003c/p\u003e\n\u003cp\u003e1. occipital bone; 2. posterior atlanto-occipital interspace (PAOiS); 3. posterior arch of the atlas; 4. posterior atlanto-axial interspace (PAAiS); 5. spinous process of the axis. the arrow indicates MDB.\u003c/p\u003e\n\u003cp\u003eA represents the schematic diagram of type A MDBC.\u003c/p\u003e\n\u003cp\u003eB shows a schematic diagram of type B MDBC.\u003c/p\u003e\n\u003cp\u003eC shows a schematic diagram of type C MDBC.\u003c/p\u003e\n\u003cp\u003eD shows a schematic diagram of the type D MDBC. The arrow indicates MDB.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4721717/v1/779eda21a4620a2baf7277bf.png"},{"id":62323068,"identity":"a66c29d0-7bd0-4d9e-b1ba-fcb44dba3b02","added_by":"auto","created_at":"2024-08-13 02:09:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":761958,"visible":true,"origin":"","legend":"\u003cp\u003eMeasurement of Sagittal Balance Indices of the Cervical Spine\u003c/p\u003e\n\u003cp\u003eIa: Occipito-cervical tilt; \u0026nbsp;IIb: Occiput-C2 angle; \u0026nbsp;IIIc: Occipito-cervical distance; IVd: Cervical lordosis measurement angle; \u0026nbsp;Ve: High cervical sagittal vertical axis\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4721717/v1/ffe818ddc30a79a729fd3cd1.png"},{"id":62323067,"identity":"a48997c1-b543-4f71-a7cb-fac0234bf055","added_by":"auto","created_at":"2024-08-13 02:09:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":300762,"visible":true,"origin":"","legend":"\u003cp\u003eA: Available spinal cord space = vertebral canal horizontal sagittal diameter - spinal cord sagittal diameter;\u003c/p\u003e\n\u003cp\u003eB: Spinal cord compression ratio = Minimum spinal cord sagittal diameter \u003cstrong\u003e÷\u003c/strong\u003eWidest transverse diameter at the same level\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4721717/v1/e4024908896dadbc5aa1e9d9.png"},{"id":88626842,"identity":"6c40fa03-d0a3-47b8-838e-6266597bb614","added_by":"auto","created_at":"2025-08-08 13:02:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5151351,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4721717/v1/0704e20e-a391-4bb6-9c6e-f8c1e7b52243.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of the Influence of Myodural Bridge Complex Classification on Cervical Spondylotic Myelopathy Based on Magnetic Resonance Imaging","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical spondylotic myelopathy (CSM)[1,2]is the most prevalent spinal cord disease in adults, characterized by neurological impairments in limbs, trunk, and sphincter muscles, along with atypical symptoms like headaches[3]. MRI technology enables precise measurement and spatial assessment of spinal cord compression in CSM, elucidating potential correlations between symptom severity and treatment prognosis[4,5,6]. The myodural bridge complex (MDBC), composed of fused myodural bridge (MDB) fibers from various sources, acts synergistically[7]. Feng X et al.[8]classified MDBC into Types A, B, C, and D based on its visibility in the PAOiS and PAAiS, correlating type characteristics with degenerative changes in the cervical spine. Degenerative changes in the cervical spine of patients with CSM often involve spinal canal narrowing and disc protrusion that compress the spinal cord. Parameters such as spinal cord compression ratio (CR)[9], space available for the cord (SAC)[10], and cervical sagittal balance (CSB)[11]are important in assessing the severity of CSM and may affect the categorization into MDBC types. This study utilizes MRI technology to analyze and measure CR, SAC, and CSB values in CSM, identifying factors that influence the classification of CSM into MDBC types. These findings provide a imaging foundation for studying the functional aspects and clinical implications of MDBC.\u003c/p\u003e\n"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\"\u003e\n \u003ch2\u003eStudy participants\u003c/h2\u003e\n \u003cp\u003eApproval for this study was obtained from the Ethics Committee for Research of Basic Medical College of Dalian Medical University. 104 healthy adults were served as the control group including 60 males and 40 females (age range from 20 to 69 years with an average of 41.16\u0026thinsp;\u0026plusmn;\u0026thinsp;11.12 years) and 96 cases diagnosed with CSM were served as the patient group(age range from 20 to 69 years with an average of 38.78\u0026thinsp;\u0026plusmn;\u0026thinsp;13.88 years) participated in this study\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\"\u003e\n \u003ch2\u003eStudy methods\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eScanning equipment and parameters.\u003c/strong\u003e 1.5T MRI scanner (HDxt, GE Healthcare, USA) was used with a neck coil phased array. Sagittal T2WI parameters: TR: 2740.0 ms, TE: 120.0ms, number of slices: 11, slice thickness: 3 mm, matrix: 256 \u0026times; 256, FOV: 240 mm \u0026times; 240 mm.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMRI evaluation criteria for MDBC classification.\u003c/strong\u003e Subjects were scanned in the supine position, utilizing a neck phased-array coil that covered the occipital and sub-occipital regions. MRI classification method of Feng X et al. for MDBC was employed[8]. On sagittal T2WI of the cervical spine, MDBC appears as areas of low signal intensity. High signal intensity indicates the presence of fat within the PAOiS and PAAiS, while flow void signals suggest the presence of blood vessels. MDBC is classified into four types (Type A, Type B, Type C, and Type D) based on its location (PAOiS and PAAiS) where it connects to the dura mater and its signal characteristics (Fig. \u003cspan\u003e1\u003c/span\u003e; Fig.\u0026nbsp;2: Diagram of MDBC Classification).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMeasurement of CSB in CSM.\u003c/strong\u003e CSB is assessed using the techniques outlined by Permsak P et al.[11](Fig. \u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e(1) Occiput-cervical inclination: Measurements were conducted for the occiput-cervical inclination angles at C3, C4, and C5. This angle is formed by the connection between the posterior edge of the cervical vertebrae and the McGregor line, which extends from the posterior upper side of the hard palate to the midline at the posterior end of the occipital bone. ( Figure Ia).\u003cp\u003e(2) Occiput-C2 angle: The angle is formed between the McGregor line and a line parallel to the lower endplate of C2.(Figure IIb)\u003c/p\u003e\n \u003cp\u003e(3) Occiput-cervical distance: The shortest distance is between the external occipital protuberance and the upper horizontal line of the spinous process of the axis vertebra (Figure IIIc).\u003c/p\u003e\n \u003cp\u003e(4) Cervical lordosis measurement angle: The angle is formed by the line extending from the lower endplate of the axis vertebra to C7. Positive values indicate posterior alignment, whereas negative values indicate anterior alignment (Figure IVd).\u003c/p\u003e\n \u003cp\u003e(5) High cervical sagittal axis: The horizontal distance between the center of C2 and the posterior edge of the upper endplate of C7 is measured. The center of C2 is determined at the intersection point of a diagonal line within the C2 vertebral body. Positive values indicate the center of C2 is positioned anterior to the posterior edge of the C7 endplate, whereas negative values indicate it is located posterior to the posterior edge of the C7 endplate (Figure Ve).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMeasurement of SAC and CR in CSM.\u003c/strong\u003e In this study, the cervical spine was divided into five segments: C2-3, C3-4, C4-5, C5-6, and C6-7. The SAC, CR, MSCCR, and MSCSAC values were measured for each segment.\u003c/p\u003e\n \u003cp\u003e(1) SAC values were measured as parameters of intervertebral disc and spinal canal volume. The calculation method involved determining the spinal cord available space in each segment, which was calculated as the horizontal sagittal diameter of the vertebral canal minus the sagittal diameter of the spinal cord. MSCSAC was then obtained by averaging SAC values from all five discs, aiming to comprehensively assess SAC values for each patient. (Fig. \u003cspan\u003e4\u003c/span\u003eA)\u003c/p\u003e\n \u003cp\u003e(2) CR value is calculated as the spinal cord compression ratio, which is defined as the minimum sagittal diameter of the spinal cord divided by the widest transverse diameter at the same level. MSCCR is based on the average CR values from all 5 discs, aiming to comprehensively assess CR conditions for each patient. ( Fig. \u003cspan\u003e4\u003c/span\u003eB)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\"\u003e\n \u003ch2\u003eStatistical analyses\u003c/h2\u003e\n \u003cp\u003eSPSS 27.0 was used. Descriptive statistics were applied to categorical data [n (%)], while metric data underwent normality testing using the Shapiro-Wilk test. Metric data conforming to or approximating a normal distribution was presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Differences in sex composition and MDBC type composition between control and patient groups were assessed using independent samples t-tests for age. Chi-square tests were employed to compare the distribution of MDBC types among CSM patients. ANOVA was utilized to compare normal indicators among CSM patients with different MDBC subtypes. For groups showing significant differences, pairwise comparisons were conducted using the S-N-K. Multifactorial analysis included multicategory multifactor logistic regression analysis where applicable. A significance level of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denoted statistical significance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003eMDBC classifcation methods in CSM\u003c/h2\u003e\n \u003cp\u003eA significant difference in MDBC classification was observed between the patient and control groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Type A and B MDBCs were less prevalent in the patient group compared to the control group, with type A being the least common (6 cases, 6.1%). Conversely, type C and type D MDBC were more prevalent, with type D comprising the highest proportion (59 cases, 60.2%). Age was significantly different between the two groups (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.022), while sex was not significantly different (Table \u003cspan\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparative Analysis of Indicator Differences between Control Group and Diseased Group\u0026nbsp;\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1722924882.png\"\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiseased group\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStatistical value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60(57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54(55.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44(44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMDBC classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63(60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20(19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22(22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59(60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.20\u0026thinsp;\u0026plusmn;\u0026thinsp;14.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.022*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: * indicates statistical significance\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003eUnivariate Analysis of Factors Influencing MDBC Classification in CSM\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003e(1) There were greater proportions of CSM patients with type C and D MDBC, but the difference in sex or age was not statistically significant (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (Table \u003cspan\u003e2\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eUnivariate Analysis of the Influence of General Data on MDBC Type\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eClassification\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType A\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType B\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType D\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30(30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29(29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.0\u0026thinsp;\u0026plusmn;\u0026thinsp;16.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.64\u0026thinsp;\u0026plusmn;\u0026thinsp;14.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.77\u0026thinsp;\u0026plusmn;\u0026thinsp;15.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.37\u0026thinsp;\u0026plusmn;\u0026thinsp;13.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.622\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003eNote: * indicates statistical significan\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\u003cspan\u003e\n \u003cp\u003e2) Significant statistical differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were observed when comparing SAC values in the C4-7 segments, CR values in the C3-7 segments, and MSCSAC and MSCCR values in relation to MDBC types in CSM. However, no significant association was found between SAC values in the C2-4 segments and CR values in the C2-3 segments with MDBC (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table \u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e2) There was no significant association found between the classification of MDBC in CSM patients and cervical sagittal balance (CSB) parameters (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table \u003cspan\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eUnivariate Analysis of the Influence of CR and SAC Values in Cervical Spine Segments on MDBC Type\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType A\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType B\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType D\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR(C2-3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.422\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR(C3-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR(C4-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR(C5-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCR(C6-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAC(C2-3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAC(C3-4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAC(C4-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAC(C5-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSAC(C6-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCSAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eNote: * indicates statistical significance\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eUnivariate Analysis of the Influence of Cervical Sagittal Parameters on MDBC Type\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType A\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType B\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType C\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType D\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/\u003cem\u003eF\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC3- Occipito-cervical inclination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.76\u0026thinsp;\u0026plusmn;\u0026thinsp;7.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.09\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.35\u0026thinsp;\u0026plusmn;\u0026thinsp;7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC4-Occipito-cervical inclination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.07\u0026thinsp;\u0026plusmn;\u0026thinsp;7.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.17\u0026thinsp;\u0026plusmn;\u0026thinsp;7.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC5-Occipito-cervical inclination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97.87\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.34\u0026thinsp;\u0026plusmn;\u0026thinsp;8.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.09\u0026thinsp;\u0026plusmn;\u0026thinsp;9.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccipito -C2 angle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;9.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;9.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;11.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccipito-cervical distance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.24\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.95\u0026thinsp;\u0026plusmn;\u0026thinsp;9.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.17\u0026thinsp;\u0026plusmn;\u0026thinsp;6.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.08\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCervical lordosis measurement angle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-9.79\u0026thinsp;\u0026plusmn;\u0026thinsp;10.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.58\u0026thinsp;\u0026plusmn;\u0026thinsp;10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.14\u0026thinsp;\u0026plusmn;\u0026thinsp;10.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-5.69\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh cervical sagittal vertical axis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.02\u0026thinsp;\u0026plusmn;\u0026thinsp;8.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.51\u0026thinsp;\u0026plusmn;\u0026thinsp;5.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.14\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eNote: * indicates statistical significance\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003eMulti-factor Analysis of Factors Influencing MDBC Classification in CSM Patients\u003c/h2\u003e\n \u003cp\u003eAll variables, including sex, age, SAC (C2-7) values, CR (C2-7) values, MSCSAC, MSCCR values, and CSB parameters, were utilized as independent factors in a multi-factor logistic regression analysis, with MDBC type in CSM patients as the dependent variable. Type A MDBC was used as the baseline category for model establishment. The results of the multi-category multi-factor logistic regression indicated that MSCSAC and MSCCR significantly influenced the likelihood of Type C and D MDBC (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, each 1 cm increase in MSCSAC was associated with reduced odds of Type C and D MDBC and increased odds of Type A MDBC. The odds ratio (OR) for Type C MDBC decreased to 0.333 times that of Type A MDBC (OR\u0026thinsp;=\u0026thinsp;0.333, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.016), and for Type D MDBC, it decreased to 0.483 times that of Type A MDBC (OR\u0026thinsp;=\u0026thinsp;0.483, \u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.01). Furthermore, each 1% increase in MSCCR was associated with decreased odds of Type D MDBC and increased odds of Type A MDBC. The odds ratio (OR) for Type D MDBC decreased to 0.013 times that of Type A MDBC (OR\u0026thinsp;=\u0026thinsp;0.013, P\u0026thinsp;=\u0026thinsp;0.008) (Table \u003cspan\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eMultivariate and multifactorial Logistic Regression Analysis of Factors Influencing MDBC Type in Cervical Spondylosis Patients\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eType B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCSAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.115～1.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-16.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01～9.346\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eType C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCSAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.136～0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-10.475\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0028～28.445\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eType D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCSAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.107～0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSCCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-20.469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e**\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0003～0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: * indicates statistical significance\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Dicussion","content":"\u003cp\u003ePrior research has validated the feasibility of MRI-based morphological studies on MDBC[8,12,13,14,15]. A recent MRI study reaffirmed the classification of human MDBC into four types: Type A, Type B, Type C, and Type D[8]. This study is the first quantitative analysis to assess the influence of different MDBC types on CSM based on MRI. The findings revealed that Type A MDBC predominated in the normal population at 60.6%, consistent with the findings of Feng X[8]. In contrast, Type C and Type D were more prevalent in CSM patients, with Type D being the most common at 60.2%, followed by Type C at 22.4%, and Type B at 11.2%. Type A had the lowest occurrence at 6.1%. The classification of MDBC in CSM did not correlate with age or sex. Literature suggests that the pathogenesis of CSM involves tension stress transmitted to the spinal cord through the dentate ligament[16]. Changes in dural tension may affect suboccipital muscle activity through sensory pathways, potentially influencing MDB. In experiments with mice, Song X et al.[17] found that neck stiffness could lead to MDB proliferation and hypertrophy, indicating the adaptability of MDBC fibers. They hypothesized that ongoing abnormal tension from CSM might contribute to MDB growth and hypertrophy. Further investigations are necessary to explore whether Type C and Type D MDBC are implicated in the development of CSM.\u003c/p\u003e \u003cp\u003eThe CR is essential for assessing clinical symptoms and cerebrospinal fluid (CSF) flow velocity in CSM patients[9,18]. It measures spinal cord compression by comparing the spinal canal diameter to the transverse diameter of the spinal cord. A lower CR indicates more severe spinal cord injury, often leading to significant functional impairment. SAC is also crucial in CSM evaluation, predicting symptomatic spinal stenosis[10,19]. Spinal canal stenosis can impact CSF dynamics. MDBC is one of the sources of CSF dynamics[23,24], and we think that the effects of the CR and SAC values on CSF dynamics may influence MDBC. CSB is a significant risk factor in CSM, affecting muscle length changes, particularly in the suboccipital muscles, the suboccipital muscle contributes to the formation of MDBC[20,21,22]. Multi-factor analysis indicates that the MSCSAC and MSCCR values of CSM are factors influencing the MDBC MRI classification, the results on factors influencing CSM MDBC classification showed that MSCSAC and MSCCR are pivotal. In this study, the classification was affected by SAC values in the C4-7 segments, CR values in the C3-7 segments, MSCSAC, and MSCCR, but not by SAC values in the C2-4 segments or CR values in the C2-3 segments. The decreasing involvement order of CSM segments-C5-6, C6-7, C4-5, C3-4, and C2-C3[25]may explain why C2-4 segment SAC values and C2-3 CR values do not impact MDBC classification in CSM. Each 1.0 cm increase in MSCSAC was associated with a decrease in Type C and Type D MDBC incidence, while increasing Type A MDBC incidence. Type C MDBC incidence decreased to 0.33 times that of Type A MDBC, and Type D MDBC incidence decreased to 0.483 times that of Type A MDBC. Each 1.0% increase in MSCCR was associated with Type D MDBC incidence decreasing to 0.013 times that of Type A MDBC. The study underscores that the severity of cervical spinal cord compression in CSM influences variations in MDBC classification, although further research is needed to elucidate the underlying mechanisms.\u003c/p\u003e \u003cp\u003eResearch has documented that CSM correlates with imbalances in CSB parameters, including advancing age, reduced range of motion in cervical lordosis angle measurements, and decreased minimum bending angle[26](Lin T, \u003cem\u003eet al\u003c/em\u003e. 2021). However, findings from this study indicate no association between CSM and CSB parameters. This discrepancy may be due to the study's use of static images obtained from supine MRI scans, which tend to yield false negative results. Typically, cervical lordosis is more accurately assessed using standing MRI or standing X-ray, which provide better differentiation effects[27].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe MDBC classification in CSM showed Type C and Type D predominantly, regardless of age. MSCSAC and MSCCR are influencing factors of MDBC classification in CSM, particularly affecting Type C and Type D MDB, regardless of sex and CSB.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eFirstly, the limitations of conventional MRI resolution and slice thickness in this study may contribute to false negatives in detecting MDBC, potentially resulting in an increased incidence of Type A MDB. Utilizing high-resolution MRI or 3D MRI techniques could mitigate this issue. Additionally, this study gathered quantitative imaging measurements of CSM in the MDBC from static MR images, which potentially influenced the accuracy of data analysis. Future research could investigate MDBC classification in CSM with spinal cord involvement using dynamic MR sequences and appropriate post-processing methodologies. Lastly, the sample size used in this study was relatively limited. Subsequent studies could enhance reliability by expanding the sample size.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHNW, HJS, and QX contributed to the concept and design of the study. HSY, CL YPT and ZCN acquired the data. SBY, NZ, YYCand JFZ analyzed and interpreted the data. QX, HJS, SBY, and HNW conceived and illustrated the unrolled model. HSY and CL drafted the manuscript. QX, HJS, and HNW revised the manuscript critically. All authors approved and edited the manuscript. HSY and CL are co-first authors and contributed equally to the work. QX, HJS, and HNW are co-corresponding authors and contributed equally to the work. All authors read and approved the fnal manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNatural Science Foundation of China (32071184)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecorresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has been performed in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee for Research of Basic Medical College of Dalian Medical University. All patients participated free willingly and with written informed consent to the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003eDepartment of Anatomy, College of Basic Medicine, Dalian Medical University, Dalian 116044, China\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003eThe 967 Hospital of the Joint \u0026nbsp;Logistics Support Force, Dalian 116021, China\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003ePostgraduate Training Base, the 967 Hospital of the Joint Logistics Support Force Jinzhou Medical University, Dalian 116021, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003eDepartment of Radiotherapy, the 967 Hospital of the Joint Logistics Support Force, Dalian 116021, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhang L, Cui Z, Yuan C, et al. 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European Spine Journal, 2021, 30: 1521-1528.\u003cu\u003e https://doi.org/10.1007/s00586-021-06833-0\u003c/u\u003e\u003c/li\u003e\n\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":"Myodural bridge complex, Cervical spondylotic myelopathy, Imaging classification, Compression ration, Space available for the cord, Cervical sagittal balance, Magnetic resonance imaging","lastPublishedDoi":"10.21203/rs.3.rs-4721717/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4721717/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eObjective\u003c/b\u003e To classify myodural bridge complex (MDBC) in the posterior atlanto-occipital interspace (PAOiS) and posterior atlanto-axial interspace (PAAiS) in cervical spondylotic myelopathy (CSM) based on Magnetic Resonance Imaging (MRI), analyzing the effects of sex, age, spinal compression ratio(CR), space available for the cord༈SAC༉, and cervical sagittal balance༈CSB) parameters on the classification of MDBC in CSM, the aim is to provide imaging evidence for the functional research and clinical application of MDBC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e Imaging data from 96 patients with CSM and 104 healthy adults were retrospectively selected, were evaluated by univariate analysis of factors and multi-factor analysis of factor Influencing the MRI Classification of MDBC in CSM .\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e The results showed significantly lower proportions of Type A and Type B MDBC in the CSM group than in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the proportions of type C and type D MDBC were greater than those in the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and have a statistically significant correlation with age (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but not with sex (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Types C and D predominated in the MDBC classification in CSM, regardless of sex and age (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Parameters such as the mean subaxial cervical space available for the cord (MSCSAC), and mean subaxial cervical compression ration (MSCCR) significantly influenced the MDBC classification in CSM (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), particularly for Types C and D. Sex and CSB did not affect MDBC classification.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e The MDBC classification in CSM predominantly showed Type C and Type D, regardless of age. MSCSAC and MSCCR are influencing factors of MDBC classification in CSM, particularly affecting Type C and Type D MDB, regardless of sex and CSB.\u003c/p\u003e","manuscriptTitle":"Analysis of the Influence of Myodural Bridge Complex Classification on Cervical Spondylotic Myelopathy Based on Magnetic Resonance Imaging","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-13 02:09:07","doi":"10.21203/rs.3.rs-4721717/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":"a2c4ca8c-4d41-406e-8b68-c3417997402e","owner":[],"postedDate":"August 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-08T12:53:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-13 02:09:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4721717","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4721717","identity":"rs-4721717","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}