High-throughput Image-based Matrix Analysis Platform Software: development of an algorithm for standardized...

Area of Science:

• Biomedical Engineering
• Computational Biology
• Materials Science

Background:

• Scanning electron microscopy (SEM) provides high-resolution biological images.
• SEM is increasingly used to study blood clots and link their properties to clinical outcomes.
• A standardized method for quantifying SEM images of biological samples is currently lacking.

Purpose of the Study:

• To develop and validate a novel, high-throughput, semiautomated computational pipeline for quantifying high-resolution SEM images.
• The pipeline, HIMAPS (High-throughput Image-based Matrix Analysis Platform Software), aims to standardize the analysis of biological sample images.

Main Methods:

• HIMAPS processes images by defining regions of interest and calibrating pixels to physical dimensions.
• It normalizes pixel intensity values and uses a stratification algorithm to partition images into layers.
• Fiber structures are enhanced, noise is reduced through morphologic refinement, and quantification of fiber thickness, network porosity, and density is performed.

Main Results:

• The pipeline's fiber thickness quantification was validated against a manual protocol, falling within the 95% confidence interval.
• Robust pore size quantification was achieved using intensity-stratified reconstruction.
• The method demonstrated accuracy in measuring key physical properties of clots.

Conclusions:

• HIMAPS offers an accurate, semiautomated, rapid, and unbiased method for quantifying physical properties of biological samples like blood clots.
• This tool can facilitate the association of clot properties with clinical outcomes.
• The developed pipeline addresses the need for a standardized quantification method in SEM-based biological imaging.