Journal of Clinical Densitometry最新文献

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IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

Analyzing the effect of osteoporosis drug treatments on femoral strength using 3D-DXA finite elements modelling 采用3D-DXA有限元模型分析骨质疏松药物治疗对股骨强度的影响。

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01 DOI: 10.1016/j.jocd.2025.101663

Carlos Ruiz Wills , Muhammad Qasim , Renaud Winzenrieth , Silvana Di Gregorio , Luis Del Río , Ludovic Humbert , Jérôme Noailly

Osteoporotic hip fracture represents a high social and economic burden in western countries. Pharmacological treatments aim to limit/reverse the loss of bone mineral density (BMD). BMD is monitored through dual energy X-ray absorptiometry (DXA). Biomechanical analysis, through 3D-DXA finite element (FE) femur models, has been shown to potentially improve fracture risk prediction. Yet, the capability of 3D-DXA FE simulations to capture the effects of pharmacological treatments on bone strength remains unexplored. Thus, this study aims to evaluate simulated changes in bone strength in subjects with different osteoporosis treatments using 3D-DXA FE models. A cohort of 155 subjects was used to generate the patient-specific FE models. Osteoporosis treatments included Alendronate (AL, n = 54), Denosumab (DMAB, n = 33), Teriparatide (TPTD, n = 31), and Naïve (NAÏVE, n = 37). Bone was modelled as BMD-dependent elasto-plastic material. Lateral fall was simulated, and bone FE-strength changes from baseline were assessed. Integral FE-strength significantly increased by 3.1% and 4.0% in the AL and DMAB groups, respectively. Trabecular and cortical FE-strength significantly increased by 2.2% and 1.9%, respectively with DMAB. Load-bearing capacity increased in both the cortical and trabecular bone of the femoral neck with DMAB and AL, while it only increased in the trabecular bone with TPTD. 3D-DXA FE analysis might help clinicians to better monitor the effects of pharmacological treatments and potentially improve personalised treatment plans for subjects with osteoporosis.

骨质疏松性髋部骨折在西方国家是一个很高的社会和经济负担。药物治疗的目的是限制/逆转骨密度（BMD）的损失。通过双能x射线吸收仪（DXA）监测骨密度。通过3D-DXA有限元（FE）股骨模型进行生物力学分析，已被证明有可能改善骨折风险预测。然而，3D-DXA FE模拟捕捉药物治疗对骨强度的影响的能力仍未被探索。因此，本研究旨在利用3D-DXA FE模型评估不同骨质疏松治疗受试者骨强度的模拟变化。155名受试者被用于生成患者特异性FE模型。治疗骨质疏松的药物包括阿仑膦酸钠（AL, n = 54）、Denosumab （DMAB, n = 33）、特立帕肽（TPTD, n = 31）和Naïve （NAÏVE, n = 37）。骨被建模为依赖于骨密度的弹塑性材料。模拟侧落，评估骨fe强度从基线的变化。AL组和DMAB组整体fe强度分别显著提高3.1%和4.0%。添加DMAB后，骨小梁和皮质fe强度分别显著提高2.2%和1.9%。DMAB和AL组股骨颈皮质骨和股骨小梁骨的承重能力均有增加，而TPTD组仅股骨小梁骨的承重能力有增加。3D-DXA FE分析可以帮助临床医生更好地监测药物治疗的效果，并有可能改善骨质疏松症患者的个性化治疗计划。

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引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

Osteoporosis prediction from Frontal Lumbar Spine X-rays 腰椎前位x线预测骨质疏松症

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01 DOI: 10.1016/j.jocd.2025.101666

Ryusei Inamori , Tomoya Kobayashi , Eichi Takaya , Junya Iwazaki , Carlos Makoto Miyauchi , Saori Ikumi , Yoshikazu Okamoto , Cheng Wei Lin , Sheng Che Hsiao , Qingzong Tseng , Shinya Sonobe

Background: This study aimed to evaluate the performance of DeepXray™ Spina, a software that estimates bone mineral density (BMD) and T-scores from frontal lumbar spine X-ray (FLS-X), in predicting osteoporosis.

Methodology: Patients from a Japanese cohort who underwent both FLS-X and dual-energy X-ray absorptiometry (DXA) using Hologic systems within 30 days at Tohoku University Hospital (May 2014-April 2024) were included. BMD was estimated from FLS-X using DeepXray™ Spina, which was developed using dataset from a Taiwanese Cohort. BMD assessed by DXA (observed BMD) and BMD estimated from FLS-X by DeepXray™ Spina (estimated BMD) were compared using Pearson’s correlation coefficient (PCC) and normalized root mean square error (NRMSE). T-scores were converted to osteoporosis classifications as normal, osteopenia, or osteoporosis following the World Health Organization criteria. Classification performance was evaluated by accuracy, sensitivity, specificity, Cohen’s kappa, and quadratic-weighted Cohen’s kappa.

Results: The correlation between estimated and observed BMD was strong, with a PCC of 0.901 and an NRMSE of 0.070. For osteoporosis classification, the accuracy, sensitivity, specificity, and Cohen’s kappa were as follows: 0.902, 1.000, 0.842, and 0.803 for normal; 0.854, 0.729, 0.924, and 0.673 for osteopenia; 0.951, 0.810, 1.000, and 0.863 for osteoporosis. The quadratic-weighted Cohen’s kappa was 0.884.

Conclusion: This study evaluated the performance of Deep Xray™ Spina in predicting osteoporosis from FLS-X. The software is a practical and reliable tool for predicting osteoporosis, with high performance and robustness.

背景：本研究旨在评估DeepXray™Spina的性能，DeepXray™Spina是一种评估骨矿物质密度（BMD）和腰椎前位x线（FLS-X） t评分的软件，用于预测骨质疏松症。方法：纳入2014年5月至2024年4月在东北大学医院（Tohoku University Hospital）接受FLS-X和双能x线吸收仪（DXA） 30天内使用Hologic系统的日本队列患者。使用DeepXray™Spina从FLS-X中估计BMD，该数据集使用来自台湾队列的数据集开发。采用Pearson相关系数（PCC）和标准化均方根误差（NRMSE）对DXA评估的骨密度（观察骨密度）和DeepXray™Spina从FLS-X估计的骨密度（估计骨密度）进行比较。按照世界卫生组织的标准，将t评分转换为骨质疏松症分类为正常、骨质减少或骨质疏松症。通过准确性、敏感性、特异性、Cohen’s kappa和二次加权Cohen’s kappa来评估分类效果。结果：BMD估计值与实测值相关性强，PCC为0.901，NRMSE为0.070。骨质疏松症分类的准确性、敏感性、特异性和Cohen’s kappa值分别为：正常为0.902、1.000、0.842、0.803；骨质减少为0.854、0.729、0.924、0.673；骨质疏松率分别为0.951、0.810、1.000、0.863。二次加权Cohen’s kappa为0.884。结论：本研究评估了Deep Xray™Spina在预测FLS-X骨质疏松症中的作用。该软件是预测骨质疏松症的实用可靠的工具，具有高性能和鲁棒性。

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引用次数: 0

IF 1.6 4区医学 Q4 ENDOCRINOLOGY & METABOLISM

Journal of Clinical Densitometry

Pub Date : 2026-01-01

引用次数: 0

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