Unraveling the effect of collagen damage on bone fracture using in situ synchrotron microtomography with deep learning

Unraveling the effect of collagen damage on bone fracture using in situ synchrotron microtomography with deep learning
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利用深度学习的原位同步加速器显微断层扫描揭示胶原蛋白损伤对骨折的影响

DOI:
10.1038/s43246-022-00296-6
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发表时间:
2022
影响因子:
7.8
通讯作者:
Acevedo, Claire
Acevedo, Claire
中科院分区:
--
文献类型:
--
作者:
Sieverts, Michael;Obata, Yoshihiro;Rosenberg, James L.;Woolley, William;Parkinson, Dilworth Y.;Barnard, Harold S.;Pelt, Daniël M.;Acevedo, Claire

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在研究骨脆性疾病时,很难确定哪些因素降低了骨对骨折的抵抗力,因为这些疾病在许多长度尺度上改变了骨。在这里,我们调查的贡献,纳米胶原蛋白的行为对宏观韧性和微观增韧机制,使用牛热处理脆性模型。该模型是通过开发一种原位韧性测试技术,同步辐射显微计算机断层扫描研究微尺度裂纹扩展的三维演变进行评估。低剂量成像与深度学习一起使用,以在保持骨骼固有机械特性的同时对图像进行降噪。我们发现,胶原蛋白损伤显着降低宏观韧性和屈服后性能。我们还发现,骨样品与受损的胶原网络有减少量的裂纹偏转,主要的微观机制的断裂阻力。这项研究表明,纳米级的胶原蛋白损伤会对微观尺度的骨增韧机制产生不利影响,并降低骨的整体韧性。
When studying bone fragility diseases, it is difficult to identify which factors reduce bone’s resistance to fracture because these diseases alter bone at many length scales. Here, we investigate the contribution of nanoscale collagen behavior on macroscale toughness and microscale toughening mechanisms using a bovine heat-treatment fragility model. This model is assessed by developing an in situ toughness testing technique for synchrotron radiation micro-computed tomography to study the evolution of microscale crack growth in 3D. Low-dose imaging is employed with deep learning to denoise images while maintaining bone’s innate mechanical properties. We show that collagen damage significantly reduces macroscale toughness and post-yield properties. We also find that bone samples with a compromised collagen network have reduced amounts of crack deflection, the main microscale mechanism of fracture resistance. This research demonstrates that collagen damage at the nanoscale adversely affects bone’s toughening mechanisms at the microscale and reduces the overall toughness of bone.
补充材料:在没有高质量参考数据的情况下对多维同步加速器 X 射线断层扫描进行深度去噪
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