Using digital image correlation to determine bone surface strains during loading and after adaptation of the mouse...

Area of Science:

• Biomechanics
• Skeletal Biology
• Biomaterials

Background:

• Cortical bone adaptation models traditionally estimate tissue strains using methods like strain gauges or finite element analysis.
• Understanding local strain distribution is crucial for elucidating bone's adaptive response to mechanical loading.

Purpose of the Study:

• To employ digital image correlation (DIC) for precise measurement of surface strains in murine tibias under compressive loading.
• To investigate the modification of these surface strains after a two-week period of load-induced bone adaptation.

Main Methods:

• Digital image correlation (DIC) was utilized to track surface deformation on murine tibias during knee-joint compressive loading.
• Strain patterns were analyzed before and after a two-week load-induced adaptation period, with contralateral limbs serving as controls.

Main Results:

• Non-uniform strain distributions were observed, with localized high strain areas (0.5%) predominantly on the medial side.
• DIC measurements demonstrated high reproducibility and agreement with strain gauge data.
• Following adaptation, strains became more uniform, with peak medial strains decreasing from 0.5% to 0.3%.

Conclusions:

• DIC provides a comprehensive method for assessing local bone surface strains, offering superior spatial resolution compared to traditional methods.
• Load-induced bone adaptation leads to a more homogeneous strain distribution, particularly by reducing peak strains in specific regions.
• This enhanced understanding of strain distribution and adaptation is vital for future research into bone mechanobiology.