Non-contact strain measurement in the mouse forearm loading model using digital image correlation (DIC)

Area of Science:

• Biomechanics
• Biomaterials Science
• Orthopedics

Background:

• Accurate strain measurement is crucial for understanding bone adaptation and fracture mechanics.
• Traditional strain gages can alter bone mechanics due to surface adhesion.
• Non-contact methods offer potential for more physiological strain assessment.

Purpose of the Study:

• To evaluate Digital Image Correlation (DIC) as a non-contact method for measuring mouse forearm strains during axial compression.
• To compare DIC measurements with traditional strain gage data.
• To investigate factors influencing DIC accuracy, including ROI, magnification, noise, and motion.

Main Methods:

• A two-camera DIC system was employed to capture medial and lateral forearm displacements.
• DIC strain data were compared against strain gage readings from the ulna and radius.
• Analysis included variations in region-of-interest (ROI) location, lens magnification, system noise, and out-of-plane motion.
• Finite element (FE) simulations were used to assess the impact of out-of-plane motion.

Main Results:

• DIC successfully differentiated strain levels between the ulna and radius, and between medial (compressive) and lateral (tensile) bone surfaces.
• DIC revealed surface strain heterogeneity not detectable by strain gages.
• System noise was minimal (<4.5% of measurements).
• Out-of-plane motion did not significantly influence DIC measurements.
• DIC measurements on medial bone surfaces were 1.5-2 times greater than strain gage readings.

Conclusions:

• Digital Image Correlation (DIC) provides a more accurate and comprehensive assessment of mouse forearm strains during loading compared to strain gages.
• DIC's non-contact nature prevents artificial stiffening of the bone, leading to a more realistic strain response.
• This advanced imaging technique enhances biomechanical studies of bone loading and adaptation.