Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens.

Area of Science:

• Biomedical Engineering
• Materials Science
• Biomechanics

Background:

• Accurate characterization of soft tissue mechanical behavior is crucial for biomedical research and product development.
• Traditional methods using average strain measures can introduce errors due to strain field heterogeneity in soft tissues.
• Heterogeneity arises from sample geometry and gripping-induced stress concentrations, necessitating local strain measurement.

Purpose of the Study:

• To develop and demonstrate a novel biomechanical testing protocol for accurate local surface strain measurement in soft tissues.
• To improve the precision of experimental vascular biomechanics and related soft material characterization.
• To provide a versatile method applicable to native and engineered soft tissues, and hydrogel/polymeric materials.

Main Methods:

• Utilized a biomechanical testing device integrated with a high-resolution camera.
• Employed digital image correlation (DIC) technique to analyze surface image data.
• Acquired a series of surface images of a vascular tissue specimen under ramped uniaxial loading to quantify local strains.

Main Results:

• Successfully quantified local surface strains on a vascular tissue specimen.
• Demonstrated the capability of the novel protocol to capture strain field heterogeneity.
• Validated the accuracy improvement offered by local strain measurement over average strain methods.

Conclusions:

• The developed protocol enhances accuracy in experimental vascular biomechanics.
• This approach has broad applicability for characterizing various native soft tissues, engineered soft tissues, and soft materials.
• The study provides a practical demonstration of system setup and experimental execution for native vascular tissue analysis.