Search

Background: Robust evidence on whether diagnostic discordance exists between lumbar osteoporosis detected by quantitative computed tomography (QCT) vs. dual-energy X-ray absorptiometry (DXA) is still lacking. In this study involving a relatively large prospective cohort of older men (aged > 60 years) and postmenopausal women, we assessed lumbar QCT-derived volumetric bone mineral density (vBMD) and DXA-derived area BMD and evaluated their predictive performance for prevalent vertebral fracture (VF). Methods: A total of 501 patients who underwent spinal surgery from September 2020 to September 2022 were enrolled. The criteria recommended by the American College of Radiology and the World Health Organization were used for lumbar osteoporosis diagnosis. The osteoporosis detection rates between QCT and DXA were compared. QCT-vBMD was plotted against the DXA T score, and the line of best fit was calculated based on linear regression. Multivariate logistic regression was used to analyze the associations between risk factors and VF. Receiver operating characteristic curve analysis was performed, and the corresponding area under the curve (AUC) was calculated. Results: QCT screening showed that 60.7% of patients had osteoporosis, whereas DXA screening showed that 50.7% of patients had osteoporosis. Diagnoses were concordant for 325 (64.9%) patients. In all, 205 patients suffered a VF of at least one anatomic level. Of these, 84.4% (173/205) were diagnosed with osteoporosis by QCT, while only 73.2% (150/205) were diagnosed by DXA. Multivariate logistic regression showed that osteoporosis detected by QCT exhibited a stronger relationship with VF than that detected by DXA (unadjusted OR, 6.81 vs. 5.04; adjusted OR, 3.44 vs. 2.66). For discrimination between patients with and without VF, QCT-vBMD (AUC = 0.802) showed better performance than DXA T score (AUC = 0.76). Conclusion: In older patients undergoing spinal surgery, QCT-vBMD is more helpful than DXA in terms of osteoporosis detection rate and prediction of patients with prevalent VFs. [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]