Despite evidence of the biomechanical role of cortical bone, current state of the art finite element models of the proximal femur built from clinical CT data lack a subject-specific representation of the bone cortex. Our main research hypothesis is that the subject-specific modelling of cortical bone layer from CT images, through a deconvolution procedure known as Cortical Bone Mapping (CBM, validated for cortical thickness and density estimates) can improve the accuracy of CT-based FE models of the proximal femur, currently limited by partial volume artefacts. Our secondary hypothesis is that a careful choice of cortical-specific density-elasticity relationship may improve model accuracy. We therefore: - implemented a procedure to include subject-specific CBM estimates of both cortical thickness and density in CT-based FE models. - defined alternative models that included CBM estimates and featured a cortical-specific or an independently optimised density-elasticity relationship. - tested our hypotheses in terms of elastic strain estimates and failure load and location prediction, by comparing with a published cohort of 14 femurs, where strain and strength in stance and fall loading configuration were experimentally measured, and estimated through reference FE models that did not explicitly model the cortical compartment. Our findings support the main hypothesis: an explicit modelling of the proximal femur cortical bone layer including CBM estimates of cortical bone thickness and density increased the FE strains prediction, mostly by reducing peak errors (average error reduced by 30%, maximum error and 95th percentile of error distribution halved) and especially when focusing on the femoral neck locations (all error metrics at least halved). We instead rejected the secondary hypothesis: changes in cortical density-elasticity relationship could not improve validation performances. From these improved baseline strain estimates, further work is needed to achieve accurate strength predictions, as models incorporating cortical thickness and density produced worse estimates of failure load and equivalent estimates of failure location when compared to reference models. In summary, we recommend including local estimates of cortical thickness and density in FE models to estimate bone strains in physiological conditions, and especially when designing exercise studies to promote bone strength.

中文翻译：

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皮质骨映射提高了股骨近端有限元应变预测的准确性

尽管有证据表明皮质骨具有生物力学作用，但根据临床 CT 数据构建的股骨近端最新有限元模型缺乏骨皮质的特定主题表示。我们的主要研究假设是，从 CT 图像对皮质骨层进行特定主题建模，通过称为皮质骨映射（CBM，已验证皮质厚度和密度估计）的去卷积程序可以提高基于 CT 的 FE 模型的准确性股骨近端，目前受到部分体积伪影的限制。我们的次要假设是谨慎选择特定于皮质的密度-弹性关系可能会提高模型的准确性。因此，我们： - 实施了一个程序，以在基于 CT 的 FE 模型中包括皮层厚度和密度的特定主题 CBM 估计。- 定义了包含 CBM 估计值的替代模型，并具有特定于皮质或独立优化的密度-弹性关系。- 通过与已发表的 14 个股骨队列进行比较，测试了我们在弹性应变估计和失效载荷和位置预测方面的假设，其中通过实验测量了站立和坠落载荷配置的应变和强度，并通过参考有限元模型进行了估计明确模拟皮质隔室。我们的研究结果支持主要假设：股骨近端皮质骨层的显式建模包括皮质骨厚度和密度的 CBM 估计增加了 FE 应变预测，主要是通过减少峰值误差（平均误差减少 30%，最大误差和误差分布的第 95 个百分位数减半），尤其是在关注股骨颈位置时（所有误差指标至少减半）。相反，我们拒绝了次要假设：皮质密度-弹性关系的变化无法提高验证性能。从这些改进的基线应变估计中，需要进一步的工作来实现准确的强度预测，因为与参考模型相比，结合皮质厚度和密度的模型产生了更差的失效载荷估计和失效位置的等效估计。总之，我们建议在 FE 模型中包括对皮质厚度和密度的局部估计，以估计生理条件下的骨应变，尤其是在设计运动研究以提高骨强度时。