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Establishing good screw-bone structural stability is conducive to reducing the risk of postoperative screw loosening. Screw insertion torque is an objective index for evaluating screw-bone structural stability. Therefore, accurate prediction of screw insertion torque can improve the preoperative evaluation of patients, optimize the surgical plan, and improve the surgical effect. At present, the correlation between different bone assessment methods and screw insertion torque is unclear. The aim of this study was to evaluate the correlation between different bone assessment methods and screw insertion torque and to optimize the predictive performance of screw insertion torque through mathematical modeling combined with different radiology methods. Prospective cross-sectional study. Seventy-seven patients with preoperatively available DXA, CT and MRI data who underwent spinal fixation surgeries between October 2022 and September 2023 and 357 sets of screw data were included in this analysis. Spinal, vertebrae-specific and screw trajectory's BMD were measured preoperatively by different imaging modalities. Intraoperative screw insertion torque was measured using an electronic torque wrench. Pearson linear correlation, scatter plots and univariate linear regression were used to evaluate the correlation between different bone evaluation methods and screw insertion torque. Different bone evaluation methods were fitted into the prediction model of screw torque and the related equations were obtained. Screw insertion torque had the strongest positive correlation with the volumetric bone mineral density (vBMD) of the screw trajectory (Pedicle screw insertion torque (PSIT): R = 0.618, p<.001; Terminal screw insertion torque (TSIT): R = 0.735, p<.001). A weak negative correlation was found between the screw insertion torque and level specific vertebral bone quality (VBQ) (PSIT: R = -0.178, p=.001; TSIT: R = -0.147, p=.006). We also found that the PSIT was strongly correlated with the TSIT (R = 0.812, p<.001). Compared to other bone quality assessment methods, screw trajectory vBMD may be better predict the magnitude of screw insertion torque. In addition, we further optimized preoperative assessments by constructing a mathematical model to better predict screw insertion torque. In conclusion, clinicians should select appropriate preoperative bone quality assessment methods, identify potential low-torque patients, optimize surgical plans, and ultimately improve screw insertion accuracy and reduce postoperative screw loosening rate. [ABSTRACT FROM AUTHOR]

In this study, we aim to evaluate the correlation between T score measured by dual X-ray absorptiometry (DXA), volumetric bone mineral density (vBMD) derived from quantitative computed tomography (QCT) and MRI-based vertebral bone quality (VBQ), explore the diagnostic performance of VBQ in osteoporosis and determine the recognition value of VBQ in osteoporotic fracture in a relatively large cohort of elderly patients scheduled to undergo spinal surgery. A total of 260 patients were enrolled in the study. DXA and QCT were used to evaluate osteoporotic status. We calculated the lumbar VBQ score, analyzed the correlation between T score, vBMD and VBQ, and explored whether VBQ was an influential factor of bone quality and fracture by binary logistic regression as well as the diagnostic performance of VBQ in osteoporosis and fracture by ROC curve. VBQ was negatively correlated with vBMD and T score. (r = − 0.487 vs. r = − 0.220). The VBQ score was a risk factor for osteoporosis under the QCT diagnostic criteria (OR = 2.245, 95% CI 1.456–3.460) and osteoporotic fractures (OR = 1.496, 95% CI 1.097–2.040). It exhibited superior discriminant performance for osteoporosis diagnosed by QCT, with a cutoff value of 3.70 and an AUC of 0.7354. Its cutoff value for osteoporotic fractures was 3.72, and its AUC was 0.6717. In a cohort of elderly patients scheduled to undergo spinal surgery, the VBQ score was more strongly associated with vBMD than the T score and could identify patients with osteoporosis and corresponding vertebral compression fracture (VCF). [ABSTRACT FROM AUTHOR]

Recently published studies have revealed a correlation between MRI-based vertebral bone quality (VBQ) score and bone mineral density (BMD) measured using dual X-ray absorptiometry (DXA) or quantitative computed tomography (QCT). However, no studies have determined if differences in field strength (1.5 vs 3.0 T) could affect the comparability of the VBQ score among different individuals. To compare the VBQ score obtained from 1.5 T and 3.0 T MRI (VBQ 1.5T vs VBQ 3.0T) in patients undergoing spine surgery and assess the predictive performance of VBQ for osteoporosis and osteoporotic vertebral fracture (VCF). A nested case‒control study based on an ongoing prospective cohort study of patients undergoing spine surgery. All older patients (men aged >60 years and postmenopausal women) with available DXA, QCT and MR images within 1 month were included. VBQ score, DXA T-score, and QCT derived vBMD. The osteoporotic classifications recommended by the World Health Organization and American College of Radiology were used to categorize the DXA T-score and QCT-derived BMD, respectively. For each patient, the VBQ score was calculated using T1-weighted MR images. Correlation analysis between VBQ and DXA/QCT was performed. Receiver operating characteristic (ROC) curve analysis, including determination of the area under the curve (AUC), was performed to assess the predictive performance of VBQ for osteoporosis. A total of 452 patients (98 men aged >60 years and 354 postmenopausal women) were included in the analysis. Across different BMD categories, the correlation coefficients between the VBQ score and BMD ranged from -0.211 to -0.511, and the VBQ 1.5T score and QCT BMD demonstrated the strongest correlation. The VBQ score was a significant classifier of osteoporosis detected by either DXA or QCT, with VBQ 1.5T showing the highest discriminative power for QCT-osteoporosis (AUC=0.744, 95% CI=0.685–0.803). In ROC analysis, the VBQ 1.5T threshold values ranged from 3.705 to 3.835 with a sensitivity between 48% and 55.6% and a specificity between 70.8% and 74.8%, while the VBQ 3.0T threshold values ranged from 2.59 to 2.605 with a sensitivity between 57.6% and 67.1% and a specificity between 67.8% and 69.7%. VBQ 1.5T exhibited better discriminability between patients with and without osteoporosis than VBQ 3.0T. Considering the non-negligible difference in osteoporosis diagnosis threshold values between the VBQ 1.5T and VBQ 3.0T scores, it is essential to clearly distinguish the magnetic field strength when assessing the VBQ score. [ABSTRACT FROM AUTHOR]

Background Context: Level-specific lumbar bone mineral density (BMD) evaluation of a single vertebral body can provide useful surgical planning and osteoporosis management information. Previous comparative studies have primarily focused on detecting spinal osteoporosis but not at specific levels.Purpose: To compare the detection rate of lumbar osteoporosis between quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA); to explore and analyze the distribution models of QCT-derived BMD and DXA T-score at the specific levels; and to evaluate the diagnostic accuracy of level-specific BMD thresholds for the prediction of osteoporotic vertebral compression fracture (OVCF) in postmenopausal women.Study Design/setting: A comparative analysis of prospectively collected data comparing QCT-derived BMD with DXA T-score.Patient Sample: A total of 296 postmenopausal women who were referred to the spine service of a single academic institution were enrolled.Outcome Measures: QCT-derived BMD and DXA T-score at specific levels, with or without osteoporotic vertebral compression fracture.Methods: Postmenopausal women who underwent QCT and DXA within a week of admission from May 2019 to June 2022 were enrolled. The diagnostic criteria for osteoporosis recommended by the World Health Organization and the American College of Radiology were used for lumbar osteoporotic diagnosis. To evaluate differences in lumbar BMD measurements at specific levels, a threshold of T score=-2.5 and QCT-derived BMD = 80 mg/cm3 were used to categorize level-specific lumbar BMD into low and high BMD. Disagreements in BMD categorization between DXA and QCT were classified as a minor or major discordance based on the definition by Woodson. Data between QCT and DXA were visualized in a stacked bar plot and analyzed. Correlations between DXA and QCT at the specific levels were evaluated using Pearson's linear correlation and scatter plots. Curve fitting of BMD distribution, receiver operating characteristic (ROC) and area under the curve (AUC) for each single vertebral level was performed.Results: Of the 296 patients, QCT diagnosed 61.1% as osteoporosis, 30.4% as osteopenia and 8.4% as normal. For those screened with DXA, 54.1% of the patients had osteoporosis, 29.4% had osteopenia and 16.6% had normal BMD. Diagnoses were concordant for 194 (65.5%) patients. Of the other 102 discordant patients, 5 (1.7%) were major and 97 (32.8%) were minor. Significant correlations in level-specific BMD between DXA and QCT were observed (p<.001), with Pearson's correlation coefficients ranging from 0.662 to 0.728. The correlation strength was in the order of L1 > L2 > L3 > L4. The low BMD detection rate for QCT was significantly higher than that for DXA at the L3 and L4 levels (65% vs. 47.9% and 68.1% vs 43.7, respectively, p<.001). Patients with OVCF showed significantly lower QCT-derived BMD (47.2 mg/cm3 vs. 83.2 mg/cm3, p<.001) and T-score (-3.39 vs. -1.98, p<.001) than those without OVCF. Among these patients, 82.8% (101/122) were diagnosed with osteoporosis by QCT measurement, while only 74.6% (91/122) were diagnosed by DXA. For discrimination between patients with and without OVCF, QCT-derived BMD showed better diagnosed performance (AUC range from 0.769 to 0.801) than DXA T-score (AUC range from 0.696 to 0.753).Conclusion: QCT provided a more accurate evaluation of lumbar osteoporosis than DXA. The QCT-derived BMD measurements at a specific lumbar level have a high diagnostic performance for OVCF. [ABSTRACT FROM AUTHOR]