A new study published in Bone was based on the hypotheses – 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; and a careful choice of cortical-specific density-elasticity relationship may improve model accuracy.

Here, a procedure was implemented 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 optimized density-elasticity relationship.
• Thereafter, the hypotheses were tested, in terms of elastic strain estimates, failure load and location prediction, by comparing with a published cohort of 14 femurs.
• In these femurs, strain and strength in stance and fall loading configuration were experimentally measured and estimated through the reference FE models that did not explicitly model the cortical compartment.

The findings supported 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).

In inference, it was recommended to include local estimates of cortical thickness and density in FE models to estimate bone strains in physiological conditions, particularly, when designing exercise studies to promote bone strength.

Source: Bone. 2020 Mar 30:115348. doi: 10.1016/j.bone.2020.115348.