Predictive value of vertebral specificity of bone mineral density for cage subsidence among patients undergoing anterior cervical diskectomy and fusion

Predictive value of vertebral specificity of bone mineral density for cage subsidence among patients undergoing anterior cervical diskectomy and fusion | 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 Predictive value of vertebral specificity of bone mineral density for cage subsidence among patients undergoing anterior cervical diskectomy and fusion Xiaozhe Zhou, Ranxu Yang, Xiong Zhang, Yunsheng Wang, Wenshuai Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6040618/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Apr, 2025 Read the published version in European Spine Journal → Version 1 posted 12 You are reading this latest preprint version Abstract Purpose To investigate the predictive value of different vertebral specificity of BMD for cage subsidence among patients undergoing ACDF. Methods BMD at different vertebrae was measured by CT image and MRI image. Cage subsidence was defined as ≥ 3 mm loss of fusion segmental height. Logistic regression analysis was used to identify BMD at specific vertebrae associated with cage subsidence. Receiver operating characteristic curve analysis was used to evaluate the value of BMD of different vertebrae in predicting cage subsidence. Results 117 patients (182 intervertebral spaces) were included, with a mean age of 54.6 ± 10.9years. The mean follow-up was 12.5 ± 3.8months. Of the 182 intervertebral spaces, subsidence was found in 85 (46.7%) intervertebral spaces. The Hounsfield unit (HU) values measured by CT in the subsidence group were lower than those in the non-subsidence group. The bone quality scores measured by MRI in the subsidence group were higher than in the non- subsidence group. The logistic regression analysis showed that the HU values were significantly negatively correlated with subsidence (p < 0.001), while the bone quality scores were significantly positively correlated with subsidence (p < 0.001). Interestingly, the areas under the curve (AUCs) of BMD in the upper vertebrae were greater than that in the lower vertebrae, whether measured by CT. Conclusion There are significant differences in the predictive value of BMD of different vertebrae for cage subsidence among patients undergoing ACDF. For the assessment of BMD, we recommend that single specific vertebrae, especially the upper vertebrae, should not be ignored. Anterior cervical diskectomy and fusion Bone mineral density Cage subsidence Different vertebrae MRI CT Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Anterior cervical discectomy and fusion (ACDF) has emerged as a prevalent surgical intervention for the treatment of cervical spondylosis[1]. Despite its widespread adoption, postoperative complications such as cage subsidence remain a notable concern[2]. The correlation between low bone mineral density (BMD) and the increased risk of cage subsidence following ACDF is well-documented in the literature[3]. This association underscores the necessity for diligent preoperative assessment of BMD as a critical step in the surgical planning for patients undergoing ACDF to mitigate the risk of this complication. The current gold standard for assessing BMD is dual-energy X-ray absorptiometry (DXA)[4]. However, it routinely measures the lumbar spine and hip, not the cervical spine. Sometimes the BMD of lumbar spine and hip joint can not fully reflect the BMD of cervical spine. Hounsfield unit (HU) values obtained by computed tomography (CT) are considered to be a useful method for assessing BMD[5]. Previous studies found that the HU value of cervical vertebrae obtained by cervical CT was significantly correlated with the T-score, and a series of HU thresholds was established for diagnosing osteoporosis[6]. It has been found that the HU value can predict the occurrence of cage subsidence[2, 7]. Recently, another new method for assessing bone quality is the vertebral bone quality (VBQ) score, which is obtained using MRI and also has a good diagnostic capacity for osteoporosis and osteoporosis-related complications [2, 8]. One of the common advantages of the HU value and VBQ score is that they can be used to measure the region of interest (ROI) and therefore the cervical spine site can be measured directly. With the continuation of BMD research, some studies began to focus on the prediction of site-specific BMD for site-specific complications[2, 9]. For example, studies have shown that endplate BMD is more closely related to cage subsidence[2, 10]. In clinical work, we have found that cage subsidence often occurs on one side (upper or lower). However, the current studies were all based on the BMD of the whole cervical spine or the average of the upper and lower vertebrae to predict cage subsidence and did not focus on a single specific vertebral BMD. In this study, we reviewed and explored the predictive value of different vertebrae for cage subsidence, highlighting the importance of BMD of single vertebrae. MATERIALS AND METHODS Patients The Institutional Review Board of our hospital approved this retrospective cohort study (Ke-2024-077-1), and the requirement for informed consent was waived due to its retrospective design. We conducted a retrospective review of the electronic medical records of patients who underwent ACDF at our hospital between January 2021 and December 2022. Be careful when handling the endplate during the operation to avoid damaging the upper and lower endplates. The surface area of cage in contact with the endplate was uniform. All patients underwent anterior plate fixation. The cages used by all patients are made of PEEK, and the plates and screws are made of titanium alloy, and the brand is the same. During the surgery, all patients used cages of the same length and width (with equal contact area), while the height of the cage was selected based on the appropriate specifications determined by the intraoperative cage trialing.Inclusion criteria were as follows: 1) patient age > 18 years; 2) patients with preoperative cervical CT or T1-weighted MRI within 1 week before operation;3)patients underwent cervical spine radiography at two postoperative time points: within one week and at a minimum of six months following the surgical procedure. The demographic data collected included age, sex, body mass index (BMI), smoking history, diabetes history, and cage height. Exclusion criteria were patients with a history of cervical trauma, malignant tumors, infections, or previous neck surgery. BMD evaluation by CT As in the previous protocol[5, 11], PACS was used to measure the HU value. All CT scans were done on the same unit with the same settings. Briefly, the HU value of the upper or lower vertebral body of the surgical site is measured by placing the elliptic ROI in the axial mid-body of the target vertebral body (Fig. 1 ). In addition to the HU values of the vertebral body, we also measured the HU values of the lower endplate of the upper vertebral body and the upper endplate of the lower vertebral body. Referring to previous studies[2], the subchondral bone area 0.6 mm from the upper and lower endplates of the surgical segment was used as ROI (Fig. 1 ). Include trabeculae as much as possible in the ROI and avoid cortical bone and heterogeneous areas. Bone quality evaluation by MRI As previous protocol[2], BMD was measured using either vertebral bone quality (VBQ) scores or endplate bone quality (EBQ) scores. Briefly, for the measurement of VBQ scores, the ROI was placed in a mid-sagittal section to measure the signal intensity (SI) of the upper or lower vertebral body of the surgical site. Subsequently, the SI from these vertebral bodies was divided by the signal intensity of the cerebrospinal fluid (CSF) in the foramen magnum to derive a comparative ratio (Formula 1; Fig. 2 ). \(\:\text{V}\text{B}\text{Q}\:\text{s}\text{c}\text{o}\text{r}\text{e}=\frac{{\text{S}\text{I}}_{targeted\:vertebral\:body\:}}{{\text{S}\text{I}}_{\:CSF}}\) For measuring EBQ, the subchondral bone area 0.6 mm from the upper or lower endplate was determined as the ROI; In addition, ensure that the area is parallel to the endplates. The SI of these endplates is then divided by the SI of the CSF to obtain EBQ scores (Formula 2; Fig. 2 ). \(\:\text{E}\text{B}\text{Q}\:\text{s}\text{c}\text{o}\text{r}\text{e}=\frac{{\text{S}\text{I}}_{targeted\:endplates\:}}{{\text{S}\text{I}}_{\:CSF}}\) Cage Subsidence Assessment Segmental height was measured on lateral X-rays as the distance from the inferior endplate of the inferior fused vertebral body to the superior endplate of the superior fused vertebral body. Cage subsidence was defined as a loss of segmental height of ≥ 3 mm at the fusion site. (Fig. 3 ) Statistical Analysis IBM SPSS version 25 (IBM Corp.) software was used for statistical analysis. After an agreement was reached between the observers, each parameter was independently measured twice by 2 orthopedic spine surgeons, and the intraclass correlation coefficient (ICC) was analyzed. Intra- and interobserver agreement were assessed via the ICC, and ICC values of 0.8 to 1.0, 0.6 to 0.79, and less than 0.6 indicated excellent, good, and poor agreement, respectively. Independent sample t-test was used to compare variables between groups. The quantitative data were analyzed by the Chi-square test or Fisher exact test. The relationship between BMD and cage subsidence was analyzed by logistic regression. Receiver operating characteristic curve (ROC) analysis was used to evaluate the value of the BMD in predicting cage subsidence. The area under the ROC curve (AUC) was computed to evaluate the diagnostic performance of the BMD of different vertebrae. RESULTS A total of 117 patients (182 intervertebral spaces) were included, with a mean age of 54.6 ± 10.9years. The mean follow-up was 12.5 ± 3.8 months. Of the 182 intervertebral spaces, subsidence was found in 85 (46.7%) intervertebral spaces (Table 1 ). There were no significant differences between the subsidence and non-subsidence groups in terms of age (p = 0.674), sex(p = 0.203), BMI (p = 0.218), Smoking (p = 0.051), diabetes (p = 0.908), cage height(p = 0.449) and follow-up period (p = 0.766) (Table 1 ). Regarding the cervical spine parameters, the intraobserver and interobserver reliability results showed excellent and good agreement, respectively (ICC ≥ 0.8). Table 1 Demographic characteristics between the subsidence and non-subsidence groups Variable All No subsidence Subsidence P Number (%) 182 (100%) 97 (53.3%) 85 (46.7%) Age 54.6 ± 10.9 54.3 ± 11.4 55.0 ± 10.4 0.674 Female, n(%) 76 (41.8%) 42 (43.4%) 34 (40.0%) 0.203 BMI (kg/m2) 25.0 ± 3.5 25.3 ± 3.4 24.7 ± 3.5 0.218 Smoking, n(%) 34 (18.7%) 13 (13.4%) 21 (24.7%) 0.051 Diabetes, n(%) 23 (12.6%) 12 (12.3%) 11 (12.9%) 0.908 Cage height(mm) 6.2 ± 1.0 6.3 ± 1.0 6.1 ± 1.0 0.499 Follow-up period(m) 12.5 ± 3.8 12.39 ± 4.0 12.55 ± 3.5 0.766 To compare the BMD in different groups, the BMD of the upper vertebral body (V-upper), the lower endplate of the upper vertebral body (E-upper), the lower vertebral body (V-lower), and the upper endplate of the lower vertebral body (E-lower) were measured by CT and MRI, respectively. The HU values in the subsidence group were significantly lower than those in the non-subsidence group (V-upper:361.8 vs. 285.8, p < 0.001; V-lower:324.0 vs. 262.1, p < 0.001; V-average:342.9 vs. 273.9, p < 0.001; E-upper:612.9 vs. 514.0, p < 0.001; E-upper:562.5 vs. 499.6, p = 0.002; E-average:587.7 vs. 506.7, p < 0.001) (Table 2 ). In addition, BMD on MRI measurements showed similar results (V-upper:2.19 vs. 2.69, p < 0.001; V-lower:2.18 vs. 2.58, p < 0.001; V-average:2.19 vs. 2.63, p < 0.001; E-upper:2.42 vs.2.92, p < 0.001; E-upper:2.44 vs.2.85, p < 0.001; E-average:2.34 vs. 2.89, p < 0.001) (Table 3 ). Table 2 Bone assessment using CT between the subsidence and non-subsidence groups Variable All No subsidence Subsidence P Vertebral body V-upper 326.3 ± 93.1 361.8 ± 89.8 285.8 ± 79.7 < 0.001 V-lower 295.1 ± 84.2 324.0 ± 82.7 262.1 ± 73.5 < 0.001 V-average 310.7 ± 85.9 342.9 ± 82.9 273.9 ± 74.0 < 0.001 Endplate E-upper 566.7 ± 138.6 612.9 ± 141.4 514.0 ± 115.1 < 0.001 E-lower 533.1 ± 137.0 562.5 ± 137.4 499.6 ± 129.5 0.002 E-average 549.9 ± 122.1 587.7 ± 120.3 506.7 ± 109.9 < 0.001 Table 3 Bone assessment using MRI between the subsidence and non-subsidence groups Variable All No subsidence Subsidence P Vertebral body V-upper 2.42 ± 0.56 2.19 ± 0.42 2.69 ± 0.58 < 0.001 V-lower 2.37 ± 0.54 2.18 ± 0.47 2.58 ± 0.54 < 0.001 V-average 2.40 ± 0.52 2.19 ± 0.41 2.63 ± 0.54 < 0.001 Endplate E-upper 2.65 ± 0.59 2.42 ± 0.48 2.92 ± 0.58 < 0.001 E-lower 2.63 ± 0.56 2.44 ± 0.51 2.85 ± 0.53 < 0.001 E-average 2.60 ± 0.57 2.34 ± 0.48 2.89 ± 0.53 < 0.001 Univariate logistic regression analysis was performed for the HU values of cervical vertebrae at different positions (Table 4 ). The logistic regression analysis showed that BMD of the upper vertebral body (OR 0.989, 95% CI 0.984–0.993; p < 0.001), lower endplate of the upper vertebral body (OR 0.989, 95% CI 0.984–0.994; p < 0.001), lower vertebral body (OR 0.994, 95% CI 0.991–0.996; p = 0.001), upper endplate of the lower vertebral body (OR 0.996, 95% CI 0.994–0.999; p < 0.001) were significantly correlated with cage subsidence. The results of the MRI measurements were similar (Table 4 ). Table 4 Univariate Logistic Regression Analysis for Bone Assessment of Subsidence After Anterior Cervical Diskectomy fusions. Variable Nagelkerke R 2 OR 95%CI P CT V-upper 0.231 0.989 0.984–0.993 < 0.001 V-lower 0.190 0.989 0.984–0.994 < 0.001 V-average 0.227 0.988 0.983–0.993 < 0.001 E-upper 0.175 0.994 0.991–0.996 < 0.001 E-lower 0.072 0.996 0.994–0.999 < 0.001 E-average 0.149 0.994 0.991–0.997 < 0.001 MRI V-upper 0.264 7.709 3.655–16.261 < 0.001 V-lower 0.184 4.989 2.544–9.783 < 0.001 V-average 0.248 7.915 3.671–17.064 < 0.001 E-upper 0.254 6.902 3.341–14.255 < 0.001 E-lower 0.183 4.761 2.459–9.217 < 0.001 E-average 0.312 9.930 4.540-21.718 < 0.001 ROC curves were created to assess the BMD of cervical vertebrae at different positions for predicting cage subsidence, and their thresholds were calculated by the Youden index (Table 5 ). Whether measured by CT or MRI, BMD at different locations showed good predictive value for cage subsidence. Interestingly, we found that the AUCs based on the BMD of the upper vertebrae were significantly larger than that of the lower (vertebral body: 0.754 > 0.723, 0.755 > 0.717; endplate: 0.702 > 0.646, 0.766 > 0.712) (Fig. 4 ). Table 5 The optimal threshold of the Bone Assessment for predicting cage subsidence constructed by the Youden index Variable Threshold AUC p Value CT V-upper 293.5 0.754 < 0.001 V-lower 259.9 0.723 < 0.001 V-average 263.4 0.749 < 0.001 E-upper 533.1 0.702 < 0.001 E-lower 547.3 0.646 0.001 E-average 545.0 0.697 < 0.001 MRI V-upper 2.56 0.755 < 0.001 V-lower 2.22 0.717 < 0.001 V-average 2.64 0.747 < 0.001 E-upper 2.83 0.766 < 0.001 E-lower 2.52 0.712 < 0.001 E-average 2.71 0.790 < 0.001 DISCUSSION To the best of our knowledge, this study is the first to assess the value of vertebral specificity of BMD in predicting cage subsidence following ACDF. The results showed that the BMD of the upper vertebral body was more predictive of cage subsidence than that of the lower vertebral body. Our findings highlight the assessment of BMD in individual vertebrae, especially in the upper vertebrae at the surgical site. Measuring BMD by mean or median may overlook the possibility of some complications. ACDF has emerged as the foremost surgical intervention for managing degenerative cervical spondylosis. However, postoperative complications such as cage subsidence into the adjacent vertebral endplate are still unavoidable [1, 12]. Cage subsidence following ACDF can lead to several complications, such as a reduction in disc height, loss of segmental lordosis, and potential recurrence of neural compression[3, 13]. These issues may cause persistent or recurrent symptoms, diminished clinical outcomes, and may even necessitate revision surgery[14]. Therefore, preoperative evaluation of patients who will undergo ACDF is required to intervene early to prevent cage subsidence from occurring. In the present investigation, the assessment of cage subsidence was obtained by measuring segmental height and computed as the disparity between postoperative X-ray images captured within one week post-surgery and the most recent follow-up X-ray[15]. Cage subsidence was defined as ≥ 3 mm loss of segmental height of the fusion, which has been demonstrated as a well-validated threshold in previous literature[16]. We found that cage subsidence occurred in 46.7% of all intervertebral spaces, which is similar to previous studies[2]. A large number of studies have clarified that BMD is one of the most important factors affecting cage subsidence[3, 7, 17]. However, the current gold standard for assessing BMD, DXA, does not specifically reflect the cervical spine. In addition, DXA measurements may be affected by proliferative osteophytes and degenerative changes[18]. CT-based HU value can be used to represent the density of the measured object[19]. It is found that the HU value has a good correlation with the T-score and can be used as an auxiliary tool to evaluate BMD[11, 20]. A key advantage of the HU value is the selection of ROI for bone density measurements at specific sites. Xu et al. found that BMD at specific sites could better predict the occurrence of osteoporotic-related complications[21]. The results of Wang et al. showed that preoperative HU values in the cervical spine could predict cage subsidence in patients after ACDF[22]. Similarly, MRI-based VBQ scores showed significant advantages in assessing bone quality. Initially, Ehresman et al. developed the VBQ score based on MRI T1-weighted imaging[23]. Numerous subsequent studies have also confirmed the effectiveness of the VBQ score in assessing BMD[24]. In addition, Li et al. also demonstrated the validity of the C-VBQ score in cage subsidence[2]. In this study, BMD at the cervical spine surgical site was measured by CT and MRI, respectively. It was found that the BMD was significantly different in patients with and without cage subsidence, and it had a good predictive value for cage subsidence. There is growing interest in assessing BMD at specific sites to predict cage subsidence, such as end plates. Jones et al. demonstrated that BMD of endplate is an effective predictor of cage subsidence after lateral lumbar interbody fusion (LLIF)[25]. Similarly, Li et al. demonstrated that a low cervical BMD of the endplate is an independent predictor of cage subsidence[2]. Therefore, we also measured the BMD of the endplate and the results verified the value of low BMD in the endplate to the cage subsidence. In clinical work, we have found that cage subsidence often occurs on one side (upper or lower) of the surgical site. However, current studies have focused on predicting cage subsidence based on the BMD of the entire cervical spine or the average of the upper and lower vertebrae at the surgical site, without focusing on specific vertebral BMD. Interestingly, we found that BMD based on the upper vertebral body was a better predictor of cage subsidence than the lower vertebral body. The reason for this difference has not been studied, and we speculate that the narrowing of the intervertebral space may be more caused by the downward movement of the upper vertebral body at the surgical site. However, it is important to note that our study emphasizes the importance of specific vertebrae, rather than ignoring the overall BMD of the spine. LIMITATIONS There are several limitations in our study. First, this is a retrospective study, and there are potential biases that may limit the generality of our findings. Secondly, Because of the limitation of retrospective study and the number of cases, we did not study the effect of surgical level and sagittal plane parameters on cage subsidence. Thirdly, our study focused on the relationship between BMD and cage subsidence, and some potential influencing factors, such as drug treatment and laboratory indicators, were not included in this study. Finally, we found the vertebral specificity in predicting cage subsidence in patients after ACDF, but did not explore the possible causes, and further exploration is needed in the future. CONCLUSION BMD at the surgical site is a good predictor of cage subsidence in patients after ACDF. There are significant differences in the predictive value of BMD of different vertebrae for cage subsidence among patients undergoing ACDF. To assess BMD, we recommend that single specific vertebrae, especially the upper vertebrae, should not be ignored. Declarations Author Contribution Xiaozhe Zhou and Ranxu Yang equally participated in data collection and article writing. Xiong Zhang participated in statistical analysis. Yunsheng Wang participated in the language editing. Wenshuai Li participated in the design of the study and article writing. Linfeng Wang participated in the design of the study and the revision of the manuscript. All authors read and approve the final version of the manuscript. References Soliman MAR, Aguirre AO, Kuo CC, Ruggiero N, Khan A, Ghannam MM, Rho K, Jowdy PK, Mullin JP, Pollina J: A Novel Cervical Vertebral Bone Quality Score Independently Predicts Cage Subsidence After Anterior Cervical Diskectomy and Fusion . Neurosurgery 2023, 92 (4):779–786. Li J, Wang L, Li Q, Deng Z, Wang L, Song Y: A novel MRI-based Cervical-Endplate Bone Quality score independently predicts cage subsidence after Anterior Cervical Discectomy and Fusion . 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Cite Share Download PDF Status: Published Journal Publication published 15 Apr, 2025 Read the published version in European Spine Journal → Version 1 posted Editorial decision: Revision requested 11 Mar, 2025 Reviews received at journal 03 Mar, 2025 Reviewers agreed at journal 03 Mar, 2025 Reviews received at journal 02 Mar, 2025 Reviewers agreed at journal 02 Mar, 2025 Reviews received at journal 01 Mar, 2025 Reviewers agreed at journal 28 Feb, 2025 Reviewers agreed at journal 28 Feb, 2025 Reviewers invited by journal 28 Feb, 2025 Editor assigned by journal 24 Feb, 2025 Submission checks completed at journal 24 Feb, 2025 First submitted to journal 16 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-6040618","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":420297200,"identity":"aebcaabf-06f6-4968-b477-1059becd5899","order_by":0,"name":"Xiaozhe Zhou","email":"","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaozhe","middleName":"","lastName":"Zhou","suffix":""},{"id":420297202,"identity":"768befe9-5c45-4256-9a8b-ca47562a7424","order_by":1,"name":"Ranxu Yang","email":"","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ranxu","middleName":"","lastName":"Yang","suffix":""},{"id":420297205,"identity":"e9b3e115-6fea-4d59-b9eb-c0e1130fa9c8","order_by":2,"name":"Xiong Zhang","email":"","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiong","middleName":"","lastName":"Zhang","suffix":""},{"id":420297208,"identity":"ea9c8c69-da5b-49a6-91de-31ede318563a","order_by":3,"name":"Yunsheng Wang","email":"","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yunsheng","middleName":"","lastName":"Wang","suffix":""},{"id":420297210,"identity":"688ae8b9-f602-43ad-bb7d-c42189f8dc2d","order_by":4,"name":"Wenshuai Li","email":"","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenshuai","middleName":"","lastName":"Li","suffix":""},{"id":420297212,"identity":"ec65c7b0-f1cc-4a9d-97e2-a52be9b24612","order_by":5,"name":"Linfeng Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYBACefn3Dw4k/quR45dgYIMIHSCgxbAhh/HBB7ZjxpIziNXCcCCH2XAGG3OiwQ1itTA2nD0mzcPDlmB8u/nYo5ttDHJ8NxIYPxfg0cLO2JcmzSMhk2d251i6cW4bg7HkjQRm6Rn4bGlmMJPmMWArNruRYyYN1JK44UYCGzMPPpcdA2lJYE7cPCP/G0hLPWEtZ3iMDWccYE7cIJHDBtKSYEBICzC0Eh98bDhmLHEjzdw455yE4cwzD5ul8WmRl2A+cCCxARiVM5KfPc4ps5HnO5588DNeh6EBCQZQwJOgYRSMglEwCkYBNgAA615MIK2yis8AAAAASUVORK5CYII=","orcid":"","institution":"Hebei Medical University Third Hospital","correspondingAuthor":true,"prefix":"","firstName":"Linfeng","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-02-16 10:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6040618/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6040618/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00586-025-08859-0","type":"published","date":"2025-04-15T15:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":77615892,"identity":"2a282807-f7c0-467b-8443-52a35d6f2be6","added_by":"auto","created_at":"2025-03-03 15:01:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":127869,"visible":true,"origin":"","legend":"\u003cp\u003eHU values of the vertebral body and endplate determined using region of interest were shown. V-upper: upper vertebral body; E-upper: endplate of the upper vertebral body; E-lower: endplate of the lower vertebral body; V-lower: lower vertebral body.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6040618/v1/91489abb78b5f9477aa57c1f.jpg"},{"id":77615893,"identity":"aeb3cae5-a966-44f6-97fc-a69af17a5fcd","added_by":"auto","created_at":"2025-03-03 15:01:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37658,"visible":true,"origin":"","legend":"\u003cp\u003eCervical sagittal non-contrast-enhanced T1-weighted magnetic resonance imaging with the signal intensity of the regions of interest used to calculate the VBQ score and EBQ score. VBQ: vertebral bone quality; EBQ: endplate bone quality.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6040618/v1/03f7f3031b5b152c128ae368.jpg"},{"id":77615895,"identity":"91d92f6c-32cb-493d-9267-3e6c0fdee6c7","added_by":"auto","created_at":"2025-03-03 15:01:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37817,"visible":true,"origin":"","legend":"\u003cp\u003eThe segmental height is calculated as the distance between the upper endplate of the upper vertebral body and the lower endplate of the lower vertebral body.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6040618/v1/42b73638daca4fd9d1a22854.jpg"},{"id":77618522,"identity":"ab4f77b8-b6b0-4c0d-8057-e9edb96752f2","added_by":"auto","created_at":"2025-03-03 15:17:04","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":126766,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver-operating characteristic curve (ROC) analysis was used to evaluate the performance of BMD in distinguishing cage subsidence. V-upper: upper vertebral body; E-upper: endplate of the upper vertebral body; E-lower: endplate of the lower vertebral body; V-lower: lower vertebral body; VBQ: vertebral bone quality; EBQ: endplate bone quality.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6040618/v1/deb053432458e80f47412abe.jpg"},{"id":81050986,"identity":"68fb8651-4397-4e00-85b6-1495c006d1f3","added_by":"auto","created_at":"2025-04-21 16:09:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2333581,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6040618/v1/8330c9bf-9354-4444-accb-38869513eaf6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive value of vertebral specificity of bone mineral density for cage subsidence among patients undergoing anterior cervical diskectomy and fusion","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAnterior cervical discectomy and fusion (ACDF) has emerged as a prevalent surgical intervention for the treatment of cervical spondylosis[1]. Despite its widespread adoption, postoperative complications such as cage subsidence remain a notable concern[2]. The correlation between low bone mineral density (BMD) and the increased risk of cage subsidence following ACDF is well-documented in the literature[3]. This association underscores the necessity for diligent preoperative assessment of BMD as a critical step in the surgical planning for patients undergoing ACDF to mitigate the risk of this complication. The current gold standard for assessing BMD is dual-energy X-ray absorptiometry (DXA)[4]. However, it routinely measures the lumbar spine and hip, not the cervical spine. Sometimes the BMD of lumbar spine and hip joint can not fully reflect the BMD of cervical spine.\u003c/p\u003e \u003cp\u003eHounsfield unit (HU) values obtained by computed tomography (CT) are considered to be a useful method for assessing BMD[5]. Previous studies found that the HU value of cervical vertebrae obtained by cervical CT was significantly correlated with the T-score, and a series of HU thresholds was established for diagnosing osteoporosis[6]. It has been found that the HU value can predict the occurrence of cage subsidence[2, 7]. Recently, another new method for assessing bone quality is the vertebral bone quality (VBQ) score, which is obtained using MRI and also has a good diagnostic capacity for osteoporosis and osteoporosis-related complications [2, 8].\u003c/p\u003e \u003cp\u003eOne of the common advantages of the HU value and VBQ score is that they can be used to measure the region of interest (ROI) and therefore the cervical spine site can be measured directly. With the continuation of BMD research, some studies began to focus on the prediction of site-specific BMD for site-specific complications[2, 9]. For example, studies have shown that endplate BMD is more closely related to cage subsidence[2, 10].\u003c/p\u003e \u003cp\u003eIn clinical work, we have found that cage subsidence often occurs on one side (upper or lower). However, the current studies were all based on the BMD of the whole cervical spine or the average of the upper and lower vertebrae to predict cage subsidence and did not focus on a single specific vertebral BMD. In this study, we reviewed and explored the predictive value of different vertebrae for cage subsidence, highlighting the importance of BMD of single vertebrae.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThe Institutional Review Board of our hospital approved this retrospective cohort study (Ke-2024-077-1), and the requirement for informed consent was waived due to its retrospective design. We conducted a retrospective review of the electronic medical records of patients who underwent ACDF at our hospital between January 2021 and December 2022. Be careful when handling the endplate during the operation to avoid damaging the upper and lower endplates. The surface area of cage in contact with the endplate was uniform. All patients underwent anterior plate fixation. The cages used by all patients are made of PEEK, and the plates and screws are made of titanium alloy, and the brand is the same. During the surgery, all patients used cages of the same length and width (with equal contact area), while the height of the cage was selected based on the appropriate specifications determined by the intraoperative cage trialing.Inclusion criteria were as follows: 1) patient age\u0026thinsp;\u0026gt;\u0026thinsp;18 years; 2) patients with preoperative cervical CT or T1-weighted MRI within 1 week before operation;3)patients underwent cervical spine radiography at two postoperative time points: within one week and at a minimum of six months following the surgical procedure. The demographic data collected included age, sex, body mass index (BMI), smoking history, diabetes history, and cage height. Exclusion criteria were patients with a history of cervical trauma, malignant tumors, infections, or previous neck surgery.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBMD evaluation by CT\u003c/h3\u003e\n\u003cp\u003eAs in the previous protocol[5, 11], PACS was used to measure the HU value. All CT scans were done on the same unit with the same settings. Briefly, the HU value of the upper or lower vertebral body of the surgical site is measured by placing the elliptic ROI in the axial mid-body of the target vertebral body (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition to the HU values of the vertebral body, we also measured the HU values of the lower endplate of the upper vertebral body and the upper endplate of the lower vertebral body. Referring to previous studies[2], the subchondral bone area 0.6 mm from the upper and lower endplates of the surgical segment was used as ROI (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Include trabeculae as much as possible in the ROI and avoid cortical bone and heterogeneous areas.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eBone quality evaluation by MRI\u003c/h3\u003e\n\u003cp\u003eAs previous protocol[2], BMD was measured using either vertebral bone quality (VBQ) scores or endplate bone quality (EBQ) scores. Briefly, for the measurement of VBQ scores, the ROI was placed in a mid-sagittal section to measure the signal intensity (SI) of the upper or lower vertebral body of the surgical site. Subsequently, the SI from these vertebral bodies was divided by the signal intensity of the cerebrospinal fluid (CSF) in the foramen magnum to derive a comparative ratio (Formula 1; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{V}\\text{B}\\text{Q}\\:\\text{s}\\text{c}\\text{o}\\text{r}\\text{e}=\\frac{{\\text{S}\\text{I}}_{targeted\\:vertebral\\:body\\:}}{{\\text{S}\\text{I}}_{\\:CSF}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor measuring EBQ, the subchondral bone area 0.6 mm from the upper or lower endplate was determined as the ROI; In addition, ensure that the area is parallel to the endplates. The SI of these endplates is then divided by the SI of the CSF to obtain EBQ scores (Formula 2; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{E}\\text{B}\\text{Q}\\:\\text{s}\\text{c}\\text{o}\\text{r}\\text{e}=\\frac{{\\text{S}\\text{I}}_{targeted\\:endplates\\:}}{{\\text{S}\\text{I}}_{\\:CSF}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003ch3\u003eCage Subsidence Assessment\u003c/h3\u003e\n\u003cp\u003eSegmental height was measured on lateral X-rays as the distance from the inferior endplate of the inferior fused vertebral body to the superior endplate of the superior fused vertebral body. Cage subsidence was defined as a loss of segmental height of \u0026ge;\u0026thinsp;3 mm at the fusion site. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eIBM SPSS version 25 (IBM Corp.) software was used for statistical analysis. After an agreement was reached between the observers, each parameter was independently measured twice by 2 orthopedic spine surgeons, and the intraclass correlation coefficient (ICC) was analyzed. Intra- and interobserver agreement were assessed via the ICC, and ICC values of 0.8 to 1.0, 0.6 to 0.79, and less than 0.6 indicated excellent, good, and poor agreement, respectively. Independent sample t-test was used to compare variables between groups. The quantitative data were analyzed by the Chi-square test or Fisher exact test. The relationship between BMD and cage subsidence was analyzed by logistic regression. Receiver operating characteristic curve (ROC) analysis was used to evaluate the value of the BMD in predicting cage subsidence. The area under the ROC curve (AUC) was computed to evaluate the diagnostic performance of the BMD of different vertebrae.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 117 patients (182 intervertebral spaces) were included, with a mean age of 54.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9years. The mean follow-up was 12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 months. Of the 182 intervertebral spaces, subsidence was found in 85 (46.7%) intervertebral spaces (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There were no significant differences between the subsidence and non-subsidence groups in terms of age (p\u0026thinsp;=\u0026thinsp;0.674), sex(p\u0026thinsp;=\u0026thinsp;0.203), BMI (p\u0026thinsp;=\u0026thinsp;0.218), Smoking (p\u0026thinsp;=\u0026thinsp;0.051), diabetes (p\u0026thinsp;=\u0026thinsp;0.908), cage height(p\u0026thinsp;=\u0026thinsp;0.449) and follow-up period (p\u0026thinsp;=\u0026thinsp;0.766) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Regarding the cervical spine parameters, the intraobserver and interobserver reliability results showed excellent and good agreement, respectively (ICC\u0026thinsp;\u0026ge;\u0026thinsp;0.8).\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\u003eDemographic characteristics between the subsidence and non-subsidence groups\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo subsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e182 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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\u003e54.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.3\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76 (41.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (43.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34 (40.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21 (24.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (12.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCage height(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up period(m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.55\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.766\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\u003eTo compare the BMD in different groups, the BMD of the upper vertebral body (V-upper), the lower endplate of the upper vertebral body (E-upper), the lower vertebral body (V-lower), and the upper endplate of the lower vertebral body (E-lower) were measured by CT and MRI, respectively. The HU values in the subsidence group were significantly lower than those in the non-subsidence group (V-upper:361.8 vs. 285.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; V-lower:324.0 vs. 262.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; V-average:342.9 vs. 273.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; E-upper:612.9 vs. 514.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; E-upper:562.5 vs. 499.6, p\u0026thinsp;=\u0026thinsp;0.002; E-average:587.7 vs. 506.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, BMD on MRI measurements showed similar results (V-upper:2.19 vs. 2.69, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; V-lower:2.18 vs. 2.58, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; V-average:2.19 vs. 2.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; E-upper:2.42 vs.2.92, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; E-upper:2.44 vs.2.85, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; E-average:2.34 vs. 2.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eBone assessment using CT between the subsidence and non-subsidence groups\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=\"char\" char=\"\u0026plusmn;\" 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 \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\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo subsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVertebral body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e326.3\u0026thinsp;\u0026plusmn;\u0026thinsp;93.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e361.8\u0026thinsp;\u0026plusmn;\u0026thinsp;89.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e285.8\u0026thinsp;\u0026plusmn;\u0026thinsp;79.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e295.1\u0026thinsp;\u0026plusmn;\u0026thinsp;84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e324.0\u0026thinsp;\u0026plusmn;\u0026thinsp;82.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e262.1\u0026thinsp;\u0026plusmn;\u0026thinsp;73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e310.7\u0026thinsp;\u0026plusmn;\u0026thinsp;85.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e342.9\u0026thinsp;\u0026plusmn;\u0026thinsp;82.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e273.9\u0026thinsp;\u0026plusmn;\u0026thinsp;74.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndplate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e566.7\u0026thinsp;\u0026plusmn;\u0026thinsp;138.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e612.9\u0026thinsp;\u0026plusmn;\u0026thinsp;141.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e514.0\u0026thinsp;\u0026plusmn;\u0026thinsp;115.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e533.1\u0026thinsp;\u0026plusmn;\u0026thinsp;137.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e562.5\u0026thinsp;\u0026plusmn;\u0026thinsp;137.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e499.6\u0026thinsp;\u0026plusmn;\u0026thinsp;129.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e549.9\u0026thinsp;\u0026plusmn;\u0026thinsp;122.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e587.7\u0026thinsp;\u0026plusmn;\u0026thinsp;120.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e506.7\u0026thinsp;\u0026plusmn;\u0026thinsp;109.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eBone assessment using MRI between the subsidence and non-subsidence groups\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=\"char\" char=\"\u0026plusmn;\" 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 \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\u003eAll\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo subsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubsidence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVertebral body\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndplate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUnivariate logistic regression analysis was performed for the HU values of cervical vertebrae at different positions (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The logistic regression analysis showed that BMD of the upper vertebral body (OR 0.989, 95% CI 0.984\u0026ndash;0.993; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower endplate of the upper vertebral body (OR 0.989, 95% CI 0.984\u0026ndash;0.994; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower vertebral body (OR 0.994, 95% CI 0.991\u0026ndash;0.996; p\u0026thinsp;=\u0026thinsp;0.001), upper endplate of the lower vertebral body (OR 0.996, 95% CI 0.994\u0026ndash;0.999; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly correlated with cage subsidence. The results of the MRI measurements were similar (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\u003eUnivariate Logistic Regression Analysis for Bone Assessment of Subsidence After Anterior Cervical Diskectomy fusions.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNagelkerke R\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.984\u0026ndash;0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.984\u0026ndash;0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.983\u0026ndash;0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.991\u0026ndash;0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.994\u0026ndash;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.991\u0026ndash;0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.655\u0026ndash;16.261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.544\u0026ndash;9.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.671\u0026ndash;17.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.341\u0026ndash;14.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.459\u0026ndash;9.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.540-21.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eROC curves were created to assess the BMD of cervical vertebrae at different positions for predicting cage subsidence, and their thresholds were calculated by the Youden index (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Whether measured by CT or MRI, BMD at different locations showed good predictive value for cage subsidence. Interestingly, we found that the AUCs based on the BMD of the upper vertebrae were significantly larger than that of the lower (vertebral body: 0.754\u0026thinsp;\u0026gt;\u0026thinsp;0.723, 0.755\u0026thinsp;\u0026gt;\u0026thinsp;0.717; endplate: 0.702\u0026thinsp;\u0026gt;\u0026thinsp;0.646, 0.766\u0026thinsp;\u0026gt;\u0026thinsp;0.712) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\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\u003eThe optimal threshold of the Bone Assessment for predicting cage subsidence constructed by the Youden index\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThreshold\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e293.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e259.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e263.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e533.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e547.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e545.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eV-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-upper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-lower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE-average\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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"},{"header":"DISCUSSION","content":"\u003cp\u003eTo the best of our knowledge, this study is the first to assess the value of vertebral specificity of BMD in predicting cage subsidence following ACDF. The results showed that the BMD of the upper vertebral body was more predictive of cage subsidence than that of the lower vertebral body. Our findings highlight the assessment of BMD in individual vertebrae, especially in the upper vertebrae at the surgical site. Measuring BMD by mean or median may overlook the possibility of some complications.\u003c/p\u003e \u003cp\u003eACDF has emerged as the foremost surgical intervention for managing degenerative cervical spondylosis. However, postoperative complications such as cage subsidence into the adjacent vertebral endplate are still unavoidable [1, 12]. Cage subsidence following ACDF can lead to several complications, such as a reduction in disc height, loss of segmental lordosis, and potential recurrence of neural compression[3, 13]. These issues may cause persistent or recurrent symptoms, diminished clinical outcomes, and may even necessitate revision surgery[14]. Therefore, preoperative evaluation of patients who will undergo ACDF is required to intervene early to prevent cage subsidence from occurring.\u003c/p\u003e \u003cp\u003eIn the present investigation, the assessment of cage subsidence was obtained by measuring segmental height and computed as the disparity between postoperative X-ray images captured within one week post-surgery and the most recent follow-up X-ray[15]. Cage subsidence was defined as \u0026ge;\u0026thinsp;3 mm loss of segmental height of the fusion, which has been demonstrated as a well-validated threshold in previous literature[16]. We found that cage subsidence occurred in 46.7% of all intervertebral spaces, which is similar to previous studies[2].\u003c/p\u003e \u003cp\u003eA large number of studies have clarified that BMD is one of the most important factors affecting cage subsidence[3, 7, 17]. However, the current gold standard for assessing BMD, DXA, does not specifically reflect the cervical spine. In addition, DXA measurements may be affected by proliferative osteophytes and degenerative changes[18]. CT-based HU value can be used to represent the density of the measured object[19]. It is found that the HU value has a good correlation with the T-score and can be used as an auxiliary tool to evaluate BMD[11, 20]. A key advantage of the HU value is the selection of ROI for bone density measurements at specific sites. Xu et al. found that BMD at specific sites could better predict the occurrence of osteoporotic-related complications[21]. The results of Wang et al. showed that preoperative HU values in the cervical spine could predict cage subsidence in patients after ACDF[22]. Similarly, MRI-based VBQ scores showed significant advantages in assessing bone quality. Initially, Ehresman et al. developed the VBQ score based on MRI T1-weighted imaging[23]. Numerous subsequent studies have also confirmed the effectiveness of the VBQ score in assessing BMD[24]. In addition, Li et al. also demonstrated the validity of the C-VBQ score in cage subsidence[2].\u003c/p\u003e \u003cp\u003eIn this study, BMD at the cervical spine surgical site was measured by CT and MRI, respectively. It was found that the BMD was significantly different in patients with and without cage subsidence, and it had a good predictive value for cage subsidence. There is growing interest in assessing BMD at specific sites to predict cage subsidence, such as end plates. Jones et al. demonstrated that BMD of endplate is an effective predictor of cage subsidence after lateral lumbar interbody fusion (LLIF)[25]. Similarly, Li et al. demonstrated that a low cervical BMD of the endplate is an independent predictor of cage subsidence[2]. Therefore, we also measured the BMD of the endplate and the results verified the value of low BMD in the endplate to the cage subsidence.\u003c/p\u003e \u003cp\u003eIn clinical work, we have found that cage subsidence often occurs on one side (upper or lower) of the surgical site. However, current studies have focused on predicting cage subsidence based on the BMD of the entire cervical spine or the average of the upper and lower vertebrae at the surgical site, without focusing on specific vertebral BMD. Interestingly, we found that BMD based on the upper vertebral body was a better predictor of cage subsidence than the lower vertebral body. The reason for this difference has not been studied, and we speculate that the narrowing of the intervertebral space may be more caused by the downward movement of the upper vertebral body at the surgical site. However, it is important to note that our study emphasizes the importance of specific vertebrae, rather than ignoring the overall BMD of the spine.\u003c/p\u003e"},{"header":"LIMITATIONS","content":"\u003cp\u003eThere are several limitations in our study. First, this is a retrospective study, and there are potential biases that may limit the generality of our findings. Secondly, Because of the limitation of retrospective study and the number of cases, we did not study the effect of surgical level and sagittal plane parameters on cage subsidence. Thirdly, our study focused on the relationship between BMD and cage subsidence, and some potential influencing factors, such as drug treatment and laboratory indicators, were not included in this study. Finally, we found the vertebral specificity in predicting cage subsidence in patients after ACDF, but did not explore the possible causes, and further exploration is needed in the future.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eBMD at the surgical site is a good predictor of cage subsidence in patients after ACDF. There are significant differences in the predictive value of BMD of different vertebrae for cage subsidence among patients undergoing ACDF. To assess BMD, we recommend that single specific vertebrae, especially the upper vertebrae, should not be ignored.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXiaozhe Zhou and Ranxu Yang equally participated in data collection and article writing. Xiong Zhang participated in statistical analysis. Yunsheng Wang participated in the language editing. Wenshuai Li participated in the design of the study and article writing. Linfeng Wang participated in the design of the study and the revision of the manuscript. All authors read and approve the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSoliman MAR, Aguirre AO, Kuo CC, Ruggiero N, Khan A, Ghannam MM, Rho K, Jowdy PK, Mullin JP, Pollina J: \u003cstrong\u003eA Novel Cervical Vertebral Bone Quality Score Independently Predicts Cage Subsidence After Anterior Cervical Diskectomy and Fusion\u003c/strong\u003e. \u003cem\u003eNeurosurgery\u003c/em\u003e 2023, \u003cstrong\u003e92\u003c/strong\u003e(4):779\u0026ndash;786.\u003c/li\u003e\n\u003cli\u003eLi J, Wang L, Li Q, Deng Z, Wang L, Song Y: \u003cstrong\u003eA novel MRI-based Cervical-Endplate Bone Quality score independently predicts cage subsidence after Anterior Cervical Discectomy and Fusion\u003c/strong\u003e. \u003cem\u003eEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society\u003c/em\u003e 2024, 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density (BMD) assessment in patients with lumbar degenerative diseases\u003c/strong\u003e. \u003cem\u003eBMC musculoskeletal disorders\u003c/em\u003e 2023, \u003cstrong\u003e24\u003c/strong\u003e(1):747.\u003c/li\u003e\n\u003cli\u003eFluss R, Lo Bu R, De la Garza Ramos R, Murthy SG, Yassari R, Gelfand Y: \u003cstrong\u003eNonquantitative CT scan Hounsfield unit as a determinant of cervical spine bone density\u003c/strong\u003e. \u003cem\u003eJournal of neurosurgery Spine\u003c/em\u003e 2024:1\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eWang Z, Mei J, Feng X, Deng C, Tian X, Lv J, Sun L: \u003cstrong\u003eLow cervical vertebral CT value increased early subsidence of titanium mesh cage after anterior cervical corpectomy and fusion\u003c/strong\u003e. \u003cem\u003eJournal of orthopaedic surgery and research\u003c/em\u003e 2022, \u003cstrong\u003e17\u003c/strong\u003e(1):355.\u003c/li\u003e\n\u003cli\u003eKadri A, Binkley N, Hernando D, Anderson PA: \u003cstrong\u003eOpportunistic Use of 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review\u003c/strong\u003e. \u003cem\u003eActa Neurochir (Wien)\u003c/em\u003e 2018, \u003cstrong\u003e160\u003c/strong\u003e(4):873\u0026ndash;880.\u003c/li\u003e\n\u003cli\u003eMilczynska WM, Ahmad A, Ahmed AI, Panchmatia JR, Fakouri B, Liantis P, Panteliadis P: \u003cstrong\u003eDoes titanium cage subsidence affect clinical outcomes in ACDF surgery? A tertiary centre experience\u003c/strong\u003e. \u003cem\u003eAnn R Coll Surg Engl\u003c/em\u003e 2023, \u003cstrong\u003e105\u003c/strong\u003e(4):378\u0026ndash;383.\u003c/li\u003e\n\u003cli\u003eCheung ZB, Gidumal S, White S, Shin J, Phan K, Osman N, Bronheim R, Vargas L, Kim JS, Cho SK: \u003cstrong\u003eComparison of Anterior Cervical Discectomy and Fusion With a Stand-Alone Interbody Cage Versus a Conventional Cage-Plate Technique: A Systematic Review and Meta-Analysis\u003c/strong\u003e. \u003cem\u003eGlobal Spine J\u003c/em\u003e 2019, \u003cstrong\u003e9\u003c/strong\u003e(4):446\u0026ndash;455.\u003c/li\u003e\n\u003cli\u003eLee JS, Son DW, Lee SH, Ki SS, Lee SW, Song GS, Woo JB, Kim YH: \u003cstrong\u003eThe Effect of Hounsfield Unit Value with Conventional Computed Tomography and Intraoperative Distraction on Postoperative Intervertebral Height Reduction in Patients Following Stand-Alone Anterior Cervical Discectomy and Fusion\u003c/strong\u003e. \u003cem\u003eJ Korean Neurosurg Soc\u003c/em\u003e 2022, \u003cstrong\u003e65\u003c/strong\u003e(1):96\u0026ndash;106.\u003c/li\u003e\n\u003cli\u003eFujibayashi S, Neo M, Nakamura T: \u003cstrong\u003eStand-alone interbody cage versus anterior cervical plate for treatment of cervical disc herniation: sequential changes in cage subsidence\u003c/strong\u003e. \u003cem\u003eJ Clin Neurosci\u003c/em\u003e 2008, \u003cstrong\u003e15\u003c/strong\u003e(9):1017\u0026ndash;1022.\u003c/li\u003e\n\u003cli\u003eFeng N, Li W, Yu X, Zhao H, Qiu Z, Guan J, Jiang G, Yang K: \u003cstrong\u003eCervical Vertebra Bone Quality Score Predicts Zero-Profile Anchored Spacer Interbody Fusion Cage Subsidence after Anterior Cervical Diskectomy and Fusion: A Retrospective Study\u003c/strong\u003e. \u003cem\u003eGlobal spine journal\u003c/em\u003e 2024:21925682241280258.\u003c/li\u003e\n\u003cli\u003eWang Y, Videman T, Boyd SK, Batti\u0026eacute; 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Cage subsidence was defined as \u0026ge;\u0026thinsp;3 mm loss of fusion segmental height. Logistic regression analysis was used to identify BMD at specific vertebrae associated with cage subsidence. Receiver operating characteristic curve analysis was used to evaluate the value of BMD of different vertebrae in predicting cage subsidence.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e117 patients (182 intervertebral spaces) were included, with a mean age of 54.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9years. The mean follow-up was 12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8months. Of the 182 intervertebral spaces, subsidence was found in 85 (46.7%) intervertebral spaces. The Hounsfield unit (HU) values measured by CT in the subsidence group were lower than those in the non-subsidence group. The bone quality scores measured by MRI in the subsidence group were higher than in the non- subsidence group. The logistic regression analysis showed that the HU values were significantly negatively correlated with subsidence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the bone quality scores were significantly positively correlated with subsidence (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Interestingly, the areas under the curve (AUCs) of BMD in the upper vertebrae were greater than that in the lower vertebrae, whether measured by CT.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere are significant differences in the predictive value of BMD of different vertebrae for cage subsidence among patients undergoing ACDF. For the assessment of BMD, we recommend that single specific vertebrae, especially the upper vertebrae, should not be ignored.\u003c/p\u003e","manuscriptTitle":"Predictive value of vertebral specificity of bone mineral density for cage subsidence among patients undergoing anterior cervical diskectomy and fusion","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-03 15:00:59","doi":"10.21203/rs.3.rs-6040618/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-11T17:19:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-03T20:06:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331143973680633532801240830612773005566","date":"2025-03-03T07:23:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-02T23:48:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162757518669415704005059367558061386801","date":"2025-03-02T23:17:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-01T07:48:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24051644774578121755271317479401891402","date":"2025-03-01T02:40:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"252153495136198301125731134589624326601","date":"2025-02-28T19:50:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-28T19:48:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-24T09:14:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-24T09:10:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Spine Journal","date":"2025-02-16T10:28:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6562b2c3-2c83-42d7-b02b-e781deb4255f","owner":[],"postedDate":"March 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-21T16:03:57+00:00","versionOfRecord":{"articleIdentity":"rs-6040618","link":"https://doi.org/10.1007/s00586-025-08859-0","journal":{"identity":"european-spine-journal","isVorOnly":false,"title":"European Spine Journal"},"publishedOn":"2025-04-15 15:57:07","publishedOnDateReadable":"April 15th, 2025"},"versionCreatedAt":"2025-03-03 15:00:59","video":"","vorDoi":"10.1007/s00586-025-08859-0","vorDoiUrl":"https://doi.org/10.1007/s00586-025-08859-0","workflowStages":[]},"version":"v1","identity":"rs-6040618","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6040618","identity":"rs-6040618","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}