QCT-based computational bone strength assessment updated with MRI-derived 'hidden' microporosity

Area of Science:

• Biomechanics
• Biomaterials Science
• Medical Imaging

Background:

• Bone microdamage from loading reduces stiffness and strength, contributing to fragility.
• Current clinical imaging cannot monitor in vivo microdamage, limiting fracture risk assessment.
• Existing computational methods do not account for microdamage present at specific timepoints.

Purpose of the Study:

• To propose and validate a computational method for quantifying in vivo bone microdamage using clinical imaging.
• To introduce 'hidden porosity' as a surrogate for pre-existing microdamage.
• To incorporate this microdamage quantification into a nonlinear constitutive model for bone tissue.

Main Methods:

• Combined quantitative computed tomography (QCT) and magnetic resonance imaging (MRI) on equine metacarpals.
• Utilized a patch-based similarity method on fluid-sensitive MRI sequences to quantify microdamage.
• Generated MRI-derived pseudoCT images to calculate a pre-existing damage (Dpex) variable.
• Integrated Dpex into a nonlinear constitutive bone model and finite element analysis.

Main Results:

• Detected Dpex values correlated with significant reductions in material stiffness (up to 35.3%) and yield stress (up to 35.3%).
• Finite element models incorporating Dpex showed significant correlations between damage and reduced condylar stiffness (p=0.001) and strength (p<0.001).
• The proposed method demonstrated the limitations of clinical CT in detecting microdamage due to partial volume effects.

Conclusions:

• The developed 'hidden porosity' method effectively quantifies in vivo bone microdamage using clinically available imaging.
• This approach enhances fracture risk assessment by accounting for accumulated microdamage.
• Findings support broader applications in human bone diseases like osteoarthritis, osteoporosis, and bone cancer.