Spatiotemporal Characterizations of Spontaneously Beating Cardiomyocytes with Adaptive Reference Digital Image...

Area of Science:

• Biomedical Engineering
• Cell Biology
• Regenerative Medicine

Background:

• Accurate mechanical assessment of biological tissues is crucial for understanding development and disease.
• Existing methods often struggle with the dynamic and complex nature of moving biological samples like cardiomyocyte tissues.
• Quantifying tissue-level function requires sophisticated analysis of cellular-level mechanics.

Purpose of the Study:

• To develop and validate an Adaptive Reference-Digital Image Correlation (AR-DIC) method for unbiased and accurate mechanics measurements of moving biological tissues.
• To apply AR-DIC to spontaneously beating cardiomyocyte (CM) tissues for precise quantification of displacement and strain.
• To establish novel spatiotemporal parameters for assessing CM contraction homogeneity, synchronicity, and propagation.

Main Methods:

• Development of an Adaptive Reference-Digital Image Correlation (AR-DIC) technique.
• Application of AR-DIC to analyze spontaneously beating cardiomyocyte (CM) tissue.
• Utilization of sarcomere displacement length-based criteria for contraction analysis.
• Synthesis of data into novel spatiotemporal parameters.

Main Results:

• AR-DIC provides unbiased and accurate mechanics measurements for moving biological tissues.
• Correct quantification of tissue displacement and strain in beating CMs was achieved.
• Novel spatiotemporal parameters were derived to characterize CM beating homogeneity, synchronicity, and propagation.
• Demonstrated the potential for holistic assessment of functional myocardial tissue development.

Conclusions:

• The AR-DIC method offers advanced non-invasive characterization of spontaneously contracting CMs.
• This technique can assess functional myocardial tissue development.
• AR-DIC holds significant applicability in myocardial regenerative medicine research.