Prediction of Pedicle Screw Loosening for Lumbar Fusion Surgery with Preoperative Volume of Interest- Based Hounsfield Units in Lumbar Vertebral Bodies on Computed Tomography

Prediction of Pedicle Screw Loosening for Lumbar Fusion Surgery with Preoperative Volume of Interest- Based Hounsfield Units in Lumbar Vertebral Bodies on Computed Tomography | 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 Prediction of Pedicle Screw Loosening for Lumbar Fusion Surgery with Preoperative Volume of Interest- Based Hounsfield Units in Lumbar Vertebral Bodies on Computed Tomography Masashi Fujimoto, Takahiro Miyazaki, Atsushi Yamamoto, Shota Ito, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6181766/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective This study aimed to evaluate the relationship between pedicle screw loosening and Hounsfield unit (HU) values measured using the volume of interest (VOI) method on preoperative computed tomography (CT) scans in patients undergoing lumbar spinal fusion surgery. Methods A retrospective cohort study was conducted on 82 patients who underwent single-level lumbar interbody fusion with bilateral pedicle screw fixation between October 2015 and October 2022 at four medical institutions. HU values at L1-L5 were measured using the VOI method. All measurements were performed by a single independent observer blinded to screw loosening status. Receiver operating characteristic curve analysis was used to determine the optimal HU cutoff values for predicting screw loosening. Results Of the 82 patients, 26 developed pedicle screw loosening. The loosening group had significantly lower HU values at all vertebral levels (p < 0.05). The mean HU across L1-L5 was 235.7 ± 35.2 in the loosening group and 283.2 ± 65.6 in the non-loosening group (p < 0.001). HU values at all vertebral levels demonstrated predictive value for screw loosening. The mean HU value over L1-L5 showed moderate predictive ability, with an area under the curve of 0.723, a sensitivity of 88.5% and a specificity of 50.0%. Conclusions Preoperative HU measurement using the VOI method on CT scans provides valuable insight into bone quality and demonstrates moderate predictive ability for assessing the risk of pedicle screw loosening. This method may serve as a practical tool for preoperative planning, guiding surgical strategies, and improving outcomes in lumbar fusion surgery. pedicle screw loosening lumbar fusion surgery Hounsfield unit volume of interest Figures Figure 1 Figure 2 Introduction Pedicle screws are widely recognized as the standard method for vertebral fixation in spinal fusion surgery, a common treatment for various spinal disorders, such as degenerative diseases, deformities, and traumatic injuries [ 1 ]. These screws provide crucial mechanical stability, which is essential for promoting bone fusion and improving clinical outcomes [ 1 ]. Although pedicle screws are widely used, loosening of these screws remains a significant complication that can result in clinical problems [ 2 , 3 ]. Radiographically, pedicle screw loosening is typically identified by a radiolucent zone surrounding the screw, indicating compromised fixation [ 4 , 5 ]. Clinically, these can cause serious issues such as persistent back pain, screw breakage, nonunion, pseudarthrosis, and spinal deformities like kyphosis [ 5 , 6 ]. These complications often necessitate revision surgery, which presents substantial challenges for both patients and clinicians. Identifying the key risk factors associated with pedicle screw loosening is essential for developing effective preventive strategies and improving surgical outcomes. The risk factors contributing to pedicle screw loosening can be broadly classified into surgical and patient-related factors [ 2 , 7 ]. Surgical factors include screw design, diameter, insertion technique, and accuracy of screw positioning [ 8 , 9 ]. In particular, improper surgical techniques, such as inaccurate screw trajectories, significantly increase the risk of loosening [ 2 , 10 ]. Patient-related factors, such as advanced age, female sex, smoking, and comorbidities like diabetes, can negatively affect the bone-screw interface, further increasing the risk of instability [ 2 , 5 ]. Among these risk factors, osteoporosis and reduced bone strength play particularly important roles, because they weaken the bone structure and compromise the stability of screw fixation [ 8 , 11 ]. In osteoporotic patients, the incidence of pedicle screw loosening has been reported to reach as high as 60% [ 3 , 12 ]. Given the essential role of bone strength in maintaining screw fixation, preoperative assessment of bone quality is essential to predict the risk of pedicle screw loosening. Traditionally, bone mineral density (BMD) has been evaluated using dual-energy X-ray absorptiometry (DEXA), which is a gold standard tool for diagnosing osteoporosis and estimating fracture risk [ 13 , 14 ]. Recently, computed tomography (CT)-derived Hounsfield units (HU) have emerged as a more accurate method for assessing vertebral bone density [ 15 , 16 ]. Additionally, magnetic resonance imaging (MRI)-based scores, such as the vertebral bone quality (VBQ) score, have proven valuable for assessing bone quality by detecting fat infiltration in vertebral trabecular bone [ 12 , 17 ]. These advanced imaging modalities offer improved precision in predicting screw loosening, particularly in patients with osteoporosis or compromised bone quality. Recent advancements in CT imaging have introduced a novel method for evaluating HU measurements, particularly through the development of volumetric approaches such as the volume of interest (VOI) method [ 18 – 20 ]. Unlike the traditional region of interest (ROI) technique, which typically focuses on two-dimensional slices of specific regions, the VOI approach allows for a comprehensive three-dimensional assessment of the vertebral body [ 20 ]. This volumetric approach captures a broader and more representative section of bone, providing a more precise and clinically meaningful measurement of bone quality [ 18 – 20 ]. Studies have shown that HU values obtained using the VOI technique correlate more strongly with BMD measured by DEXA than HU values obtained using the ROI technique, suggesting a more robust indicator of bone health [ 20 ]. While some studies have reported on the association between ROI-based HU measurements and the risk of pedicle screw loosening, no study to date has employed the VOI method to evaluate HU values for preoperative risk assessment of pedicle screw loosening. The purpose of this study is to investigate the relationship between pedicle screw loosening and HU values measured using the VOI method on CT scans. Through the analysis of VOI-based HU measurements, this study aims to determine their effectiveness in predicting the risk of screw loosening and to establish a more reliable assessment tool for preoperative planning in spinal fusion surgery. Materials and Methods Ethical Review and Approval This study was conducted according to the ethical principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board (IRB) of Mie University Graduate School of Medicine (approval number: 3164). Given the retrospective design of this study, the IRB granted a waiver of informed consent for each patient. All patient data were anonymized, and confidentiality was strictly maintained throughout the study in accordance with both institutional and national ethical guidelines. Study Design The purpose of this retrospective cohort study was to investigate the association between HU values in the VOI obtained from preoperative CT scans and the incidence of lumbar pedicle screw loosening. The study included patients who underwent lumbar interbody fusion surgery with bilateral pedicle screw fixation at a single intervertebral level. Eligible cases were identified from multiple institutions, including Mie University Hospital, Mie Chuo Medical Center, Suzuka Kaisei Hospital, and Mie Central Medical Center, where surgeries were performed between October 2015 and October 2022. Only patients with a minimum follow-up period of 12 months after surgery were included. Exclusion criteria were multilevel fusion surgery, vertebral infections, and vertebral fractures. CT Protocol and HU Measurements Imaging for this study was performed using multiple CT scanners, including but not limited to the Discovery CT750 HD (GE), LightSpeed VCT VISION (GE), Revolution CT (GE), SOMATOM Definition Flash (Siemens), SOMATOM Force (Siemens), and Aquilion ONE (Canon). CT parameters were standardized to ensure consistency across scans, with a slice thickness of either 1.0 mm or 1.25 mm, an interval of 0.5 mm or 0.625 mm, a tube voltage of 120 kVp, and a bone reconstruction algorithm. HU measurements in the VOI were performed using commercially available 3D medical image segmentation software (Mimics version 24.0; Materialise, Leuven, Belgium). To ensure methodological consistency, the evaluator underwent practical training prior to conducting the analyses. The analysis involved the following steps [ 20 ]: CT scan data were exported in Digital Imaging and Communications in Medicine format and imported into the 3D imaging software. The lumbar vertebra of interest was identified and segmented using the region-growing method within the 3D volume rendering protocol. The VOI was defined by isolating the posterior aspect of the vertebral body on the segmented 3D image. The vertebral VOI was verified on 2D images to confirm the complete inclusion of the intended bone structure. The software automatically calculated the mean HU values within the defined VOI (Fig. 1). All HU measurements were performed by a single independent observer who was blinded to the presence or absence of pedicle screw loosening on postoperative CT images. Evaluation of Screw Loosening Screw loosening was assessed using postoperative CT imaging. Loosening was defined as the presence of a radiolucent zone greater than 1.0 mm surrounding the screw. CT images were evaluated at least 12 months after surgery. A board-certified spine surgeon with extensive experience in spinal imaging independently reviewed all CT images. Based on these evaluations, patients were categorized into either the loosening group or the non-loosening group. Statistical Analysis All statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria). The independent samples t-test was used to compare continuous variables being presented as a mean ± standard deviation between the screw loosening and non-loosening groups. Categorical data were analyzed using χ² test or Fisher's exact test. The diagnostic efficacy of HU values obtained from the VOI in each vertebral body for predicting pedicle screw loosening was evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was calculated, with an AUC greater than 0.7 considered to indicate strong predictive value. A p-value of less than 0.05 was considered statistically significant in all analyses. Results Patient Characteristics A total of 82 patients were included in this study, with a mean age of 68.2 ± 10.4 years. Of these patients, 29 (35.4%) were female and 53 (64.6%) were male. The mean body mass index (BMI) was 24.5 ± 4.0 kg/m². Among the study participants, 21 (25.6%) were current smokers, and 19 (23.2%) had a history of diabetes. The mean follow-up period was 679.4 ± 464.5 days. Lumbar fusion surgeries were performed at various levels, with the following distribution: L2/3 (7 patients), L3/4 (17 patients), L4/5 (42 patients), and L5/S1 (16 patients). Regarding the surgical technique, posterior lumbar interbody fusion (PLIF) was used in 35 cases (42.7%), while transforaminal lumbar interbody fusion (TLIF) was used in 47 cases (57.3%) (Table 1 ). Table 1 Patient Characteristics Characteristics All (n = 82) Age (years) 68.2 ± 10.4 Sex Female 29 Male 53 BMI (kg/m 2 ) 24.5 ± 4.0 Smoker 21 Diabetes 19 Follow-up (days) 679.4 ± 464.5 Fusion level L2/3 7 L3/4 17 L4/5 42 L5/S1 16 Fusion type PLIF 35 TLIF 47 Values are presented as mean ± standard deviation or number. BMI: body mass index, PLIF: posterior lumbar interbody fusion, TLIF: transforaminal lumbar interbody fusion Comparison Between the Loosening and Non-Loosening Groups Among the 82 patients, pedicle screw loosening was observed in 26 cases (31.7%), while 56 patients (68.3%) did not experience loosening. The mean age was slightly higher in the loosening group (70.2 ± 9.4 years) compared to the non-loosening group (67.3 ± 10.8 years), though this difference was not statistically significant (p = 0.237). Other demographic and clinical characteristics, such as sex distribution (p = 0.458), BMI (p = 0.832), smoking status (p = 0.102), and history of diabetes (p = 0.276), showed no significant differences between the two groups. Furthermore, there was no significant difference in the distribution of fusion techniques between the loosening and non-loosening groups (p = 0.347). HU values were evaluated from vertebral levels across L1-L5, with significantly lower values observed in the loosening group compared to the non-loosening group at each level. For instance, at L1, the mean HU was 212.3 ± 41.7 in the loosening group and 252.8 ± 65.8 in the non-loosening group (p < 0.05). Similar significant differences in HU values were found at L2 (223.1 ± 38.9 vs. 267.5 ± 73.0, p < 0.05), L3 (233.2 ± 43.6 vs. 273.8 ± 69.6, p < 0.05), L4 (244.6 ± 42.7 vs. 292.1 ± 69.5, p < 0.05), and L5 (265.3 ± 42.6 vs. 329.6 ± 87.2, p < 0.05). When the mean HU value was calculated across L1-L5, the HU value was 235.7 ± 35.2 in the loosening group, compared to 283.2 ± 65.6 in the non-loosening group, representing a highly statistically significant difference (p < 0.001) (Table 2 ). Table 2 Comparison of characteristics between pedicle screw loosening and non-loosening groups Characteristics Loosening (n = 26) Non-loosening (n = 56) P Value Age (years) 70.2 ± 9.4 67.3 ± 10.8 0.237 a Sex 0.458 b Female 11 18 Male 15 39 BMI (kg/m 2 ) 24.4 ± 4.1 24.6 ± 4.0 0.832 a Smoker 10 11 0.102 b Diabetes 8 10 0.276 b Fusion level L2/3 1 6 L3/4 5 12 L4/5 15 27 L5/S1 5 11 Fusion type 0.347 b PLIF 9 26 TLIF 17 30 HU value L1 212.3 ± 41.7 252.8 ± 65.8 < 0.05 a L2 223.1 ± 38.9 267.5 ± 73.0 < 0.05 a L3 233.2 ± 43.6 273.8 ± 69.6 < 0.05 a L4 244.6 ± 42.7 292.1 ± 69.5 < 0.05 a L5 265.3 ± 42.6 329.6 ± 87.2 < 0.05 a L1-5 (average) 235.7 ± 35.2 283.2 ± 65.6 < 0.001 a Values are presented as mean ± standard deviation or number. a t value; b x 2 . BMI: body mass index, PLIF: posterior lumbar interbody fusion, TLIF: transforaminal lumbar interbody fusion, HU: Hounsfield unit Cutoff Values and Diagnostic Accuracy for Predicting Screw Loosening ROC curve analysis was conducted to determine the predictive accuracy of HU values at each vertebral level for pedicle screw loosening. The optimal HU cutoff values for each level were as follows: 238.5 for L1, 270.2 for L2, 239.3 for L3, 271.9 for L4, and 300.2 for L5. HU values across all vertebral levels demonstrated predictive accuracy for pedicle screw loosening, with AUCs ranging from 0.668 to 0.725 for L1 to L5. The mean HU value across L1-L5 showed comparable predictive capability, with an optimal cutoff of 263.5, a sensitivity of 88.5%, and a specificity of 50.0%, and an AUC of 0.723 (Table 3 ). Table 3 Cutoff values, sensitivity and specificity in Hounsfield unit values in volume of interest for predicting screw loosening Vertebral Level Cutoff HU Sensitivity Specificity AUC (95% CI) L1 238.5 0.846 0.518 0.672 (0.552–0.792) L2 270.2 0.962 0.339 0.668 (0.547–0.790) L3 239.3 0.615 0.679 0.670 (0.546–0.795) L4 271.9 0.846 0.571 0.701 (0.587–0.815) L5 300.2 0.846 0.571 0.725 (0.616–0.835) L1-5 (average) 263.5 0.885 0.500 0.723 (0.611–0.835) HU: Hounsfield unit, AUC: area under the curve, CI: confidence interval Discussion In this study, we investigated the relationship between HU values in the VOI on preoperative CT scans and pedicle screw loosening in patients undergoing lumbar fusion surgery. The results showed that the HU values at each vertebral level across L1-L5 and the mean value across L1-L5 were lower in the group with pedicle screw loosening. The cut-off value for the mean HU value across L1-L5 was 263.5, and the AUC was 0.723, indicating that the diagnostic accuracy for predicting screw loosening was moderate. Various factors, such as patient characteristics, surgical techniques, and spinal alignment, have been reported in the literature as contributing to the risk of pedicle screw loosening. Among these, HU measurement based on the VOI, which has not been previously reported as a predictive tool, shows potential as a novel and valuable method for identifying patients at high risk of screw loosening. These results suggest that HU measurement based on VOI can be a valuable predictive tool for identifying patients at high risk for screw loosening. It has been previously reported that BMD using DEXA, HU values in the ROI using CT, and VBQ scores using MRI are each associated with pedicle screw loosening. However, each of these assessment methods has specific limitations in comprehensively assessing bone density and quality. DEXA is widely recognized as the gold standard for BMD assessment [ 21 , 22 ]. As DEXA is a two-dimensional measurement method that estimates bone density as areal BMD based on the projection area of the bone, this method does not account for the true three-dimensional structure of the bone [ 21 , 23 ]. Additionally, DEXA readings can be influenced by surrounding structures, such as aortic calcifications, spinous processes, laminae, and even bowel contents, which can misrepresent the actual bone quality [ 20 , 21 , 23 ]. ROI-based measurements, including HU values on CT and VBQ scoring on MRI, have several limitations, primarily due to reproducibility issues [ 18 , 24 ]. Even small variations in slice positioning or ROI placement and size can significantly affect HU values and VBQ scores, making it difficult to achieve consistent evaluations of bone quality across different observers [ 18 , 24 ]. Furthermore, ROI-based measurements in both CT and MRI typically focus on trabecular bone while potentially overlooking cortical bone. This focus limits the ability of ROI-based approaches to fully represent bone quality. In addition, VBQ scoring evaluates marrow fat content as an indirect measure of bone integrity, but it does not directly capture bone quality, which is essential for assessing structural strength [ 12 , 17 , 22 ]. VBQ scoring's dependence on T1-weighted image signal intensities introduces further variability, as machine calibration and technical factors can affect results, further limiting reproducibility across different settings [ 25 ]. The utilization of HU measurement based on the VOI in this study enables a more thorough three-dimensional assessment of bone quality, surpassing the capabilities of DEXA, ROI-based CT, and MRI-based VBQ scoring analyses. This method has demonstrated significant reproducibility in 3D volumetric measurements [ 18 , 19 ], thereby enhancing its reliability as a predictor of screw loosening risk and confirming its utility as a preoperative tool for evaluating bone quality in spinal fusion procedures. Despite the strengths of this study, certain limitations should be noted. First, the retrospective design may introduce selection bias, as only patients with preoperative CT scans were included. Additionally, this study was limited to patients who underwent single-level lumbar fusion with a minimum follow-up of 12 months, which may affect the generalizability of the findings to patients undergoing multilevel fusions or other spinal procedures. Future research should aim to address these limitations through prospective studies with larger, more diverse patient cohorts and standardized imaging protocols to further validate the predictive value of HU measurements for predicting screw loosening. Conclusion This study highlights the potential utility of VOI-based HU values on preoperative CT as a predictive tool for assessing the risk of pedicle screw loosening in lumbar fusion surgery. By providing a more comprehensive evaluation of bone quality compared to traditional ROI-based and other imaging methods, the VOI approach offers improved predictive accuracy. Incorporating HU measurements into preoperative planning may assist clinicians in identifying high-risk patients and tailoring surgical strategies, ultimately enhancing clinical outcomes and reducing the need for revision surgeries. Abbreviations AUC = area under the curve; BMD = bone mineral density; CT = computed tomography; DEXA = dual-energy x-ray absorptiometry; HU = Hounsfield unit; IRB = Institutional Review Board; MRI = magnetic resonance imaging; PLIF = posterior lumbar interbody fusion; ROC = receiver operating characteristic; ROI = region of interest; TLIF = transforaminal lumbar interbody fusion; VBQ = vertebral bone quality; VOI = volume of interest. Declarations Author Contribution MF wrote the manuscript text, and prepared figures and table. All authors reviewed the manuscript. Data Availability Sequence data that support the findings of this study have been deposited in the Mie University Graduate School of Medicine with the primary accession code 3164. References de Kater EP, Sakes A, Edstrom E, et al. (2022) Beyond the pedicle screw-a patent review. Eur Spine J 31:1553-1565. https://doi.org/10.1007/s00586-022-07193-z Zou D, Muheremu A, Sun Z, et al. 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J Neurosurg Spine 38:436-445. https://doi.org/10.3171/2022.11.spine22875 Link TM (2016) Radiology of Osteoporosis. Can Assoc Radiol J 67:28-40. https://doi.org/10.1016/j.carj.2015.02.002 Braunagel M, Radler E, Ingrisch M, et al. (2015) Dynamic contrast-enhanced magnetic resonance imaging measurements in renal cell carcinoma: effect of region of interest size and positioning on interobserver and intraobserver variability. Invest Radiol 50:57-66. https://doi.org/10.1097/rli.0000000000000096 Liu XG, Chen X, Chen B, et al. (2023) Vertebral bone quality different in magnetic resonance imaging parameters. J Orthop Surg Res 18:772. https://doi.org/10.1186/s13018-023-04268-5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Center","correspondingAuthor":false,"prefix":"","firstName":"Munenari","middleName":"","lastName":"Ikezawa","suffix":""},{"id":433208846,"identity":"67c8aa83-f3eb-4cf8-be2c-c508682e5189","order_by":5,"name":"Satoru Tanioka","email":"","orcid":"","institution":"Charité Universitätsmedizin Berlin","correspondingAuthor":false,"prefix":"","firstName":"Satoru","middleName":"","lastName":"Tanioka","suffix":""},{"id":433208847,"identity":"94750c3e-8c2e-4e1f-844a-c89a63162544","order_by":6,"name":"Hirofumi Nishikawa","email":"","orcid":"","institution":"Mie University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hirofumi","middleName":"","lastName":"Nishikawa","suffix":""},{"id":433208849,"identity":"bf52f3ad-28b8-4647-86f9-bc798adbad5b","order_by":7,"name":"Yusuke Kamei","email":"","orcid":"","institution":"Mie Prefectural General Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Kamei","suffix":""},{"id":433208853,"identity":"7ae64d48-35fb-49f6-8a24-e53dcb438d1c","order_by":8,"name":"Masaki Mizuno","email":"","orcid":"","institution":"Suzuka Kaisei Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masaki","middleName":"","lastName":"Mizuno","suffix":""},{"id":433208856,"identity":"7a9f4ecd-271f-446b-b926-f9da30d6060a","order_by":9,"name":"Hidenori Suzuki","email":"","orcid":"","institution":"Mie University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hidenori","middleName":"","lastName":"Suzuki","suffix":""}],"badges":[],"createdAt":"2025-03-08 03:53:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6181766/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6181766/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79575204,"identity":"49cb4c1e-2854-41e9-9c9d-551266013c79","added_by":"auto","created_at":"2025-03-31 11:13:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":103017,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional segmentation of the volume of interest in preoperative computed tomography scans.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6181766/v1/84d66bef2bfe784ffdb59f6d.jpg"},{"id":79573315,"identity":"acfb5e75-6926-4ba2-921e-9414b887491a","added_by":"auto","created_at":"2025-03-31 11:05:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35163,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic curves for Hounsfield units at individual vertebral levels (L1 to L5, \u003cstrong\u003eA\u003c/strong\u003e to \u003cstrong\u003eE\u003c/strong\u003e, respectively) and the mean across L1-L5 (\u003cstrong\u003eF\u003c/strong\u003e) to predict pedicle screw loosening.\u003c/p\u003e","description":"","filename":"Figure21.png","url":"https://assets-eu.researchsquare.com/files/rs-6181766/v1/6a616108865d4dadc246c14d.png"},{"id":81513684,"identity":"24301610-9ad3-4017-a420-4796768e04e6","added_by":"auto","created_at":"2025-04-28 06:40:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":875663,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6181766/v1/92310b60-6b25-4733-ad42-338e469cebec.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of Pedicle Screw Loosening for Lumbar Fusion Surgery with Preoperative Volume of Interest- Based Hounsfield Units in Lumbar Vertebral Bodies on Computed Tomography","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePedicle screws are widely recognized as the standard method for vertebral fixation in spinal fusion surgery, a common treatment for various spinal disorders, such as degenerative diseases, deformities, and traumatic injuries [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These screws provide crucial mechanical stability, which is essential for promoting bone fusion and improving clinical outcomes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although pedicle screws are widely used, loosening of these screws remains a significant complication that can result in clinical problems [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Radiographically, pedicle screw loosening is typically identified by a radiolucent zone surrounding the screw, indicating compromised fixation [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Clinically, these can cause serious issues such as persistent back pain, screw breakage, nonunion, pseudarthrosis, and spinal deformities like kyphosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These complications often necessitate revision surgery, which presents substantial challenges for both patients and clinicians.\u003c/p\u003e \u003cp\u003eIdentifying the key risk factors associated with pedicle screw loosening is essential for developing effective preventive strategies and improving surgical outcomes. The risk factors contributing to pedicle screw loosening can be broadly classified into surgical and patient-related factors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Surgical factors include screw design, diameter, insertion technique, and accuracy of screw positioning [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In particular, improper surgical techniques, such as inaccurate screw trajectories, significantly increase the risk of loosening [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Patient-related factors, such as advanced age, female sex, smoking, and comorbidities like diabetes, can negatively affect the bone-screw interface, further increasing the risk of instability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong these risk factors, osteoporosis and reduced bone strength play particularly important roles, because they weaken the bone structure and compromise the stability of screw fixation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In osteoporotic patients, the incidence of pedicle screw loosening has been reported to reach as high as 60% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given the essential role of bone strength in maintaining screw fixation, preoperative assessment of bone quality is essential to predict the risk of pedicle screw loosening. Traditionally, bone mineral density (BMD) has been evaluated using dual-energy X-ray absorptiometry (DEXA), which is a gold standard tool for diagnosing osteoporosis and estimating fracture risk [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recently, computed tomography (CT)-derived Hounsfield units (HU) have emerged as a more accurate method for assessing vertebral bone density [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, magnetic resonance imaging (MRI)-based scores, such as the vertebral bone quality (VBQ) score, have proven valuable for assessing bone quality by detecting fat infiltration in vertebral trabecular bone [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These advanced imaging modalities offer improved precision in predicting screw loosening, particularly in patients with osteoporosis or compromised bone quality.\u003c/p\u003e \u003cp\u003eRecent advancements in CT imaging have introduced a novel method for evaluating HU measurements, particularly through the development of volumetric approaches such as the volume of interest (VOI) method [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Unlike the traditional region of interest (ROI) technique, which typically focuses on two-dimensional slices of specific regions, the VOI approach allows for a comprehensive three-dimensional assessment of the vertebral body [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This volumetric approach captures a broader and more representative section of bone, providing a more precise and clinically meaningful measurement of bone quality [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Studies have shown that HU values obtained using the VOI technique correlate more strongly with BMD measured by DEXA than HU values obtained using the ROI technique, suggesting a more robust indicator of bone health [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile some studies have reported on the association between ROI-based HU measurements and the risk of pedicle screw loosening, no study to date has employed the VOI method to evaluate HU values for preoperative risk assessment of pedicle screw loosening. The purpose of this study is to investigate the relationship between pedicle screw loosening and HU values measured using the VOI method on CT scans. Through the analysis of VOI-based HU measurements, this study aims to determine their effectiveness in predicting the risk of screw loosening and to establish a more reliable assessment tool for preoperative planning in spinal fusion surgery.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthical Review and Approval\u003c/h2\u003e \u003cp\u003e This study was conducted according to the ethical principles outlined in the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board (IRB) of Mie University Graduate School of Medicine (approval number: 3164). Given the retrospective design of this study, the IRB granted a waiver of informed consent for each patient. All patient data were anonymized, and confidentiality was strictly maintained throughout the study in accordance with both institutional and national ethical guidelines.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eThe purpose of this retrospective cohort study was to investigate the association between HU values in the VOI obtained from preoperative CT scans and the incidence of lumbar pedicle screw loosening. The study included patients who underwent lumbar interbody fusion surgery with bilateral pedicle screw fixation at a single intervertebral level. Eligible cases were identified from multiple institutions, including Mie University Hospital, Mie Chuo Medical Center, Suzuka Kaisei Hospital, and Mie Central Medical Center, where surgeries were performed between October 2015 and October 2022. Only patients with a minimum follow-up period of 12 months after surgery were included. Exclusion criteria were multilevel fusion surgery, vertebral infections, and vertebral fractures.\u003c/p\u003e\n\u003ch3\u003eCT Protocol and HU Measurements\u003c/h3\u003e\n \u003cp\u003eImaging for this study was performed using multiple CT scanners, including but not limited to the Discovery CT750 HD (GE), LightSpeed VCT VISION (GE), Revolution CT (GE), SOMATOM Definition Flash (Siemens), SOMATOM Force (Siemens), and Aquilion ONE (Canon). CT parameters were standardized to ensure consistency across scans, with a slice thickness of either 1.0 mm or 1.25 mm, an interval of 0.5 mm or 0.625 mm, a tube voltage of 120 kVp, and a bone reconstruction algorithm.\u003c/p\u003e \u003cp\u003eHU measurements in the VOI were performed using commercially available 3D medical image segmentation software (Mimics version 24.0; Materialise, Leuven, Belgium). To ensure methodological consistency, the evaluator underwent practical training prior to conducting the analyses. The analysis involved the following steps [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCT scan data were exported in Digital Imaging and Communications in Medicine format and imported into the 3D imaging software.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe lumbar vertebra of interest was identified and segmented using the region-growing method within the 3D volume rendering protocol.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe VOI was defined by isolating the posterior aspect of the vertebral body on the segmented 3D image.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe vertebral VOI was verified on 2D images to confirm the complete inclusion of the intended bone structure.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eThe software automatically calculated the mean HU values within the defined VOI (Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eAll HU measurements were performed by a single independent observer who was blinded to the presence or absence of pedicle screw loosening on postoperative CT images.\u003c/p\u003e\n\u003ch3\u003eEvaluation of Screw Loosening\u003c/h3\u003e\n\u003cp\u003eScrew loosening was assessed using postoperative CT imaging. Loosening was defined as the presence of a radiolucent zone greater than 1.0 mm surrounding the screw. CT images were evaluated at least 12 months after surgery. A board-certified spine surgeon with extensive experience in spinal imaging independently reviewed all CT images. Based on these evaluations, patients were categorized into either the loosening group or the non-loosening group.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria). The independent samples t-test was used to compare continuous variables being presented as a mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation between the screw loosening and non-loosening groups. Categorical data were analyzed using χ\u0026sup2; test or Fisher's exact test. The diagnostic efficacy of HU values obtained from the VOI in each vertebral body for predicting pedicle screw loosening was evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was calculated, with an AUC greater than 0.7 considered to indicate strong predictive value. A p-value of less than 0.05 was considered statistically significant in all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient Characteristics\u003c/h2\u003e \u003cp\u003eA total of 82 patients were included in this study, with a mean age of 68.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4 years. Of these patients, 29 (35.4%) were female and 53 (64.6%) were male. The mean body mass index (BMI) was 24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0 kg/m\u0026sup2;. Among the study participants, 21 (25.6%) were current smokers, and 19 (23.2%) had a history of diabetes. The mean follow-up period was 679.4\u0026thinsp;\u0026plusmn;\u0026thinsp;464.5 days. Lumbar fusion surgeries were performed at various levels, with the following distribution: L2/3 (7 patients), L3/4 (17 patients), L4/5 (42 patients), and L5/S1 (16 patients). Regarding the surgical technique, posterior lumbar interbody fusion (PLIF) was used in 35 cases (42.7%), while transforaminal lumbar interbody fusion (TLIF) was used in 47 cases (57.3%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.2\u0026thinsp;\u0026plusmn;\u0026thinsp;10.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e679.4\u0026thinsp;\u0026plusmn;\u0026thinsp;464.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFusion level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL2/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5/S1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFusion type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or number.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eBMI: body mass index, PLIF: posterior lumbar interbody fusion, TLIF: transforaminal lumbar interbody fusion\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison Between the Loosening and Non-Loosening Groups\u003c/h3\u003e\n\u003cp\u003eAmong the 82 patients, pedicle screw loosening was observed in 26 cases (31.7%), while 56 patients (68.3%) did not experience loosening. The mean age was slightly higher in the loosening group (70.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4 years) compared to the non-loosening group (67.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8 years), though this difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.237). Other demographic and clinical characteristics, such as sex distribution (p\u0026thinsp;=\u0026thinsp;0.458), BMI (p\u0026thinsp;=\u0026thinsp;0.832), smoking status (p\u0026thinsp;=\u0026thinsp;0.102), and history of diabetes (p\u0026thinsp;=\u0026thinsp;0.276), showed no significant differences between the two groups. Furthermore, there was no significant difference in the distribution of fusion techniques between the loosening and non-loosening groups (p\u0026thinsp;=\u0026thinsp;0.347).\u003c/p\u003e \u003cp\u003eHU values were evaluated from vertebral levels across L1-L5, with significantly lower values observed in the loosening group compared to the non-loosening group at each level. For instance, at L1, the mean HU was 212.3\u0026thinsp;\u0026plusmn;\u0026thinsp;41.7 in the loosening group and 252.8\u0026thinsp;\u0026plusmn;\u0026thinsp;65.8 in the non-loosening group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Similar significant differences in HU values were found at L2 (223.1\u0026thinsp;\u0026plusmn;\u0026thinsp;38.9 vs. 267.5\u0026thinsp;\u0026plusmn;\u0026thinsp;73.0, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), L3 (233.2\u0026thinsp;\u0026plusmn;\u0026thinsp;43.6 vs. 273.8\u0026thinsp;\u0026plusmn;\u0026thinsp;69.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), L4 (244.6\u0026thinsp;\u0026plusmn;\u0026thinsp;42.7 vs. 292.1\u0026thinsp;\u0026plusmn;\u0026thinsp;69.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and L5 (265.3\u0026thinsp;\u0026plusmn;\u0026thinsp;42.6 vs. 329.6\u0026thinsp;\u0026plusmn;\u0026thinsp;87.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When the mean HU value was calculated across L1-L5, the HU value was 235.7\u0026thinsp;\u0026plusmn;\u0026thinsp;35.2 in the loosening group, compared to 283.2\u0026thinsp;\u0026plusmn;\u0026thinsp;65.6 in the non-loosening group, representing a highly statistically significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of characteristics between pedicle screw loosening and non-loosening groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoosening (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-loosening (n\u0026thinsp;=\u0026thinsp;56)\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\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.237\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\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 \u003cp\u003e0.458\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \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\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.832\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.102\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFusion level\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\u003eL2/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \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\u003eL3/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \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\u003eL4/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \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\u003eL5/S1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \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\u003eFusion type\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 \u003cp\u003e0.347\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \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\u003eTLIF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \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\u003eHU value\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\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e212.3\u0026thinsp;\u0026plusmn;\u0026thinsp;41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e252.8\u0026thinsp;\u0026plusmn;\u0026thinsp;65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223.1\u0026thinsp;\u0026plusmn;\u0026thinsp;38.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267.5\u0026thinsp;\u0026plusmn;\u0026thinsp;73.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e233.2\u0026thinsp;\u0026plusmn;\u0026thinsp;43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e273.8\u0026thinsp;\u0026plusmn;\u0026thinsp;69.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e244.6\u0026thinsp;\u0026plusmn;\u0026thinsp;42.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292.1\u0026thinsp;\u0026plusmn;\u0026thinsp;69.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265.3\u0026thinsp;\u0026plusmn;\u0026thinsp;42.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e329.6\u0026thinsp;\u0026plusmn;\u0026thinsp;87.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1-5 (average)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235.7\u0026thinsp;\u0026plusmn;\u0026thinsp;35.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e283.2\u0026thinsp;\u0026plusmn;\u0026thinsp;65.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or number. \u003csup\u003ea\u003c/sup\u003et value; \u003csup\u003eb\u003c/sup\u003ex\u003csup\u003e2\u003c/sup\u003e.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI: body mass index, PLIF: posterior lumbar interbody fusion, TLIF: transforaminal lumbar interbody fusion, HU: Hounsfield unit\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCutoff Values and Diagnostic Accuracy for Predicting Screw Loosening\u003c/h2\u003e \u003cp\u003eROC curve analysis was conducted to determine the predictive accuracy of HU values at each vertebral level for pedicle screw loosening. The optimal HU cutoff values for each level were as follows: 238.5 for L1, 270.2 for L2, 239.3 for L3, 271.9 for L4, and 300.2 for L5. HU values across all vertebral levels demonstrated predictive accuracy for pedicle screw loosening, with AUCs ranging from 0.668 to 0.725 for L1 to L5. The mean HU value across L1-L5 showed comparable predictive capability, with an optimal cutoff of 263.5, a sensitivity of 88.5%, and a specificity of 50.0%, and an AUC of 0.723 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCutoff values, sensitivity and specificity in Hounsfield unit values in volume of interest for predicting screw loosening\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\u003eVertebral Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCutoff HU\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e238.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.672 (0.552\u0026ndash;0.792)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e270.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.668 (0.547\u0026ndash;0.790)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e239.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.670 (0.546\u0026ndash;0.795)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e271.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.701 (0.587\u0026ndash;0.815)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e300.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.725 (0.616\u0026ndash;0.835)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL1-5 (average)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e263.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.723 (0.611\u0026ndash;0.835)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eHU: Hounsfield unit, AUC: area under the curve, CI: confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we investigated the relationship between HU values in the VOI on preoperative CT scans and pedicle screw loosening in patients undergoing lumbar fusion surgery. The results showed that the HU values at each vertebral level across L1-L5 and the mean value across L1-L5 were lower in the group with pedicle screw loosening. The cut-off value for the mean HU value across L1-L5 was 263.5, and the AUC was 0.723, indicating that the diagnostic accuracy for predicting screw loosening was moderate. Various factors, such as patient characteristics, surgical techniques, and spinal alignment, have been reported in the literature as contributing to the risk of pedicle screw loosening. Among these, HU measurement based on the VOI, which has not been previously reported as a predictive tool, shows potential as a novel and valuable method for identifying patients at high risk of screw loosening. These results suggest that HU measurement based on VOI can be a valuable predictive tool for identifying patients at high risk for screw loosening.\u003c/p\u003e \u003cp\u003eIt has been previously reported that BMD using DEXA, HU values in the ROI using CT, and VBQ scores using MRI are each associated with pedicle screw loosening. However, each of these assessment methods has specific limitations in comprehensively assessing bone density and quality. DEXA is widely recognized as the gold standard for BMD assessment [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. As DEXA is a two-dimensional measurement method that estimates bone density as areal BMD based on the projection area of the bone, this method does not account for the true three-dimensional structure of the bone [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, DEXA readings can be influenced by surrounding structures, such as aortic calcifications, spinous processes, laminae, and even bowel contents, which can misrepresent the actual bone quality [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. ROI-based measurements, including HU values on CT and VBQ scoring on MRI, have several limitations, primarily due to reproducibility issues [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Even small variations in slice positioning or ROI placement and size can significantly affect HU values and VBQ scores, making it difficult to achieve consistent evaluations of bone quality across different observers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, ROI-based measurements in both CT and MRI typically focus on trabecular bone while potentially overlooking cortical bone. This focus limits the ability of ROI-based approaches to fully represent bone quality. In addition, VBQ scoring evaluates marrow fat content as an indirect measure of bone integrity, but it does not directly capture bone quality, which is essential for assessing structural strength [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. VBQ scoring's dependence on T1-weighted image signal intensities introduces further variability, as machine calibration and technical factors can affect results, further limiting reproducibility across different settings [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe utilization of HU measurement based on the VOI in this study enables a more thorough three-dimensional assessment of bone quality, surpassing the capabilities of DEXA, ROI-based CT, and MRI-based VBQ scoring analyses. This method has demonstrated significant reproducibility in 3D volumetric measurements [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], thereby enhancing its reliability as a predictor of screw loosening risk and confirming its utility as a preoperative tool for evaluating bone quality in spinal fusion procedures.\u003c/p\u003e \u003cp\u003eDespite the strengths of this study, certain limitations should be noted. First, the retrospective design may introduce selection bias, as only patients with preoperative CT scans were included. Additionally, this study was limited to patients who underwent single-level lumbar fusion with a minimum follow-up of 12 months, which may affect the generalizability of the findings to patients undergoing multilevel fusions or other spinal procedures. Future research should aim to address these limitations through prospective studies with larger, more diverse patient cohorts and standardized imaging protocols to further validate the predictive value of HU measurements for predicting screw loosening.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the potential utility of VOI-based HU values on preoperative CT as a predictive tool for assessing the risk of pedicle screw loosening in lumbar fusion surgery. By providing a more comprehensive evaluation of bone quality compared to traditional ROI-based and other imaging methods, the VOI approach offers improved predictive accuracy. Incorporating HU measurements into preoperative planning may assist clinicians in identifying high-risk patients and tailoring surgical strategies, ultimately enhancing clinical outcomes and reducing the need for revision surgeries.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAUC = area under the curve; BMD = bone mineral density; CT = computed tomography; DEXA = dual-energy x-ray absorptiometry; HU = Hounsfield unit; IRB = Institutional Review Board; MRI = magnetic resonance imaging; PLIF = posterior lumbar interbody fusion; ROC = receiver operating characteristic; ROI = region of interest; TLIF = transforaminal lumbar interbody fusion; VBQ = vertebral bone quality; VOI = volume of interest.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMF wrote the manuscript text, and prepared figures and table. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eSequence data that support the findings of this study have been deposited in the Mie University Graduate School of Medicine with the primary accession code 3164.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ede Kater EP, Sakes A, Edstrom E, et al. (2022) Beyond the pedicle screw-a patent review. Eur Spine J 31:1553-1565. https://doi.org/10.1007/s00586-022-07193-z\u003c/li\u003e\n\u003cli\u003eZou D, Muheremu A, Sun Z, et al. (2020) Computed tomography Hounsfield unit-based prediction of pedicle screw loosening after surgery for degenerative lumbar spine disease. J Neurosurg Spine 32:716-721. https://doi.org/10.3171/2019.11.spine19868\u003c/li\u003e\n\u003cli\u003eYuan L, Zhang X, Zeng Y, et al. (2023) Incidence, Risk, and Outcome of Pedicle Screw Loosening in Degenerative Lumbar Scoliosis Patients Undergoing Long-Segment Fusion. Global Spine J 13:1064-1071. https://doi.org/10.1177/21925682211017477\u003c/li\u003e\n\u003cli\u003eIshikawa Y, Katsumi K, Mizouchi T, et al. (2023) Importance of computed tomography Hounsfield units in predicting S1 screw loosening after lumbosacral fusion. J Clin Neurosci 113:1-6. https://doi.org/10.1016/j.jocn.2023.04.019 \u003c/li\u003e\n\u003cli\u003eShu L, Muheremu A, Ji Y, et al. (2024) Prediction of Lumbar Pedicle Screw Loosening Using Hounsfield Units in Computed Tomography. Curr Med Imaging 20:e260423216204. https://doi.org/10.2174/1573405620666230426123914\u003c/li\u003e\n\u003cli\u003eYao YC, Chao H, Kao KY, et al. (2023) CT Hounsfield unit is a reliable parameter for screws loosening or cages subsidence in minimally invasive transforaminal lumbar interbody fusion. Sci Rep 13:1620. https://doi.org/10.1038/s41598-023-28555-7 \u003c/li\u003e\n\u003cli\u003eDe Stefano F, Elarjani T, Warner T, et al. (2022) Hounsfield Unit as a Predictor of Adjacent-Level Disease in Lumbar Interbody Fusion Surgery. Neurosurgery 91:146-149. https://doi.org/10.1227/neu.0000000000002049 \u003c/li\u003e\n\u003cli\u003eXu F, Zou D, Li W, et al. (2020) Hounsfield units of the vertebral body and pedicle as predictors of pedicle screw loosening after degenerative lumbar spine surgery. Neurosurg Focus 49:E10. https://doi.org/10.3171/2020.5.focus20249 \u003c/li\u003e\n\u003cli\u003eKim KH, Kim TH, Kim SW, et al. (2022) Significance of Measuring Lumbar Spine 3-Dimensional Computed Tomography Hounsfield Units to Predict Screw Loosening. World Neurosurg 165:e555-e562. https://doi.org/10.1016/j.wneu.2022.06.104\u003c/li\u003e\n\u003cli\u003eLi J, Zhang Z, Xie T, et al. (2023) The preoperative Hounsfield unit value at the position of the future screw insertion is a better predictor of screw loosening than other methods. Eur Radiol 33:1526-1536. https://doi.org/10.1007/s00330-022-09157-9\u003c/li\u003e\n\u003cli\u003eZou D, Li W, Deng C, et al. (2019) The use of CT Hounsfield unit values to identify the undiagnosed spinal osteoporosis in patients with lumbar degenerative diseases. Eur Spine J 28:1758-1766. https://doi.org/10.1007/s00586-018-5776-9 \u003c/li\u003e\n\u003cli\u003eLi W, Zhu H, Hua Z, et al. (2023) Vertebral Bone Quality Score as a Predictor of Pedicle Screw Loosening Following Surgery for Degenerative Lumbar Disease. Spine (Phila Pa 1976) 48:1635-1641. https://doi.org/10.1097/brs.0000000000004577\u003c/li\u003e\n\u003cli\u003eLane NE (2006) Epidemiology, etiology, and diagnosis of osteoporosis. Am J Obstet Gynecol 194:S3-11. https://doi.org/10.1016/j.ajog.2005.08.047\u003c/li\u003e\n\u003cli\u003eKohan EM, Nemani VM, Hershman S, et al. (2017) Lumbar computed tomography scans are not appropriate surrogates for bone mineral density scans in primary adult spinal deformity. 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(2023) Alternatives to DEXA for the assessment of bone density: a systematic review of the literature and future recommendations. J Neurosurg Spine 38:436-445. https://doi.org/10.3171/2022.11.spine22875\u003c/li\u003e\n\u003cli\u003eLink TM (2016) Radiology of Osteoporosis. Can Assoc Radiol J 67:28-40. https://doi.org/10.1016/j.carj.2015.02.002\u003c/li\u003e\n\u003cli\u003eBraunagel M, Radler E, Ingrisch M, et al. (2015) Dynamic contrast-enhanced magnetic resonance imaging measurements in renal cell carcinoma: effect of region of interest size and positioning on interobserver and intraobserver variability. Invest Radiol 50:57-66. https://doi.org/10.1097/rli.0000000000000096\u003c/li\u003e\n\u003cli\u003eLiu XG, Chen X, Chen B, et al. (2023) Vertebral bone quality different in magnetic resonance imaging parameters. J Orthop Surg Res 18:772. https://doi.org/10.1186/s13018-023-04268-5\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"pedicle screw loosening, lumbar fusion surgery, Hounsfield unit, volume of interest","lastPublishedDoi":"10.21203/rs.3.rs-6181766/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6181766/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aimed to evaluate the relationship between pedicle screw loosening and Hounsfield unit (HU) values measured using the volume of interest (VOI) method on preoperative computed tomography (CT) scans in patients undergoing lumbar spinal fusion surgery.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective cohort study was conducted on 82 patients who underwent single-level lumbar interbody fusion with bilateral pedicle screw fixation between October 2015 and October 2022 at four medical institutions. HU values at L1-L5 were measured using the VOI method. All measurements were performed by a single independent observer blinded to screw loosening status. Receiver operating characteristic curve analysis was used to determine the optimal HU cutoff values for predicting screw loosening.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 82 patients, 26 developed pedicle screw loosening. The loosening group had significantly lower HU values at all vertebral levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The mean HU across L1-L5 was 235.7\u0026thinsp;\u0026plusmn;\u0026thinsp;35.2 in the loosening group and 283.2\u0026thinsp;\u0026plusmn;\u0026thinsp;65.6 in the non-loosening group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). HU values at all vertebral levels demonstrated predictive value for screw loosening. The mean HU value over L1-L5 showed moderate predictive ability, with an area under the curve of 0.723, a sensitivity of 88.5% and a specificity of 50.0%.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003ePreoperative HU measurement using the VOI method on CT scans provides valuable insight into bone quality and demonstrates moderate predictive ability for assessing the risk of pedicle screw loosening. This method may serve as a practical tool for preoperative planning, guiding surgical strategies, and improving outcomes in lumbar fusion surgery.\u003c/p\u003e","manuscriptTitle":"Prediction of Pedicle Screw Loosening for Lumbar Fusion Surgery with Preoperative Volume of Interest- Based Hounsfield Units in Lumbar Vertebral Bodies on Computed Tomography","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:05:41","doi":"10.21203/rs.3.rs-6181766/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a72bb4d3-c57c-409e-b0fa-04cfe7c1629b","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T06:24:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-31 11:05:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6181766","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6181766","identity":"rs-6181766","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}