Automated cardiac sarcomere analysis from second harmonic generation images

Area of Science:

• Biomedical Engineering
• Cell Biology
• Medical Imaging

Background:

• Cardiac muscle properties provide insights into various diseases.
• Stain-free imaging techniques are desirable for biological tissue analysis.
• Automated quantification can improve the efficiency and reliability of tissue analysis.

Purpose of the Study:

• To develop and validate an automated methodology for quantifying cardiac muscle ultrastructure.
• To assess the performance of the automated method using simulated and real cardiac tissue images.
• To establish a reliable tool for systematic cardiac tissue characterization.

Main Methods:

• Utilized Second Harmonic Generation (SHG) imaging for stain-free visualization of cardiac fibers.
• Developed an automated measurement technique to extract quantitative image features.
• Evaluated the methodology using computer-generated models and manual measurements on rabbit cardiac tissue (fetal and adult).

Main Results:

• The automated methodology reliably computed sarcomere length, A-band length, thick-thin interaction length, and fiber orientation.
• The method demonstrated good performance at a high signal-to-noise ratio (20 dB).
• Validation against manual measurements in SHG images showed good agreement.

Conclusions:

• The automated measurements provide a reliable characterization of cardiac fiber tissues.
• This methodology enables systematic study of cardiac tissue across diverse conditions.
• The stain-free SHG imaging approach combined with automated analysis offers a powerful tool for cardiovascular research.