Automatic quantification of angiogenesis in 2D sections: a precise and timesaving approach

Area of Science:

• Biomedical Engineering
• Tissue Engineering
• Regenerative Medicine

Background:

• Standardized characterization of angiogenesis is critical for tissue engineering success.
• Sufficient blood supply remains a limiting factor in engineered tissues.
• Existing methods for assessing new vessel formation lack observer independence and reliability.

Purpose of the Study:

• To develop an automatic, observer-independent quantitative method for analyzing vascularization.
• To provide a reliable algorithm for assessing new vessel formation in tissue engineering models.
• To offer downloadable source code for the proposed analysis method.

Main Methods:

• Utilized a rat arteriovenous loop model for vascularization.
• Employed two-dimensional (2D) microscopic images of histological cross-sections.
• Developed an advanced postprocessing algorithm based on 'positive- and negative-experts' and nearest neighbour classification.

Main Results:

• The automatic analysis yielded precise vessel count and area values comparable to manual data.
• Demonstrated a significant increase in vessel count and area over time (5, 10, 15 days).
• The 2D algorithm outperformed micro-computed tomography (μCT) in small vessel detection, cost, and time efficiency.

Conclusions:

• The developed method offers a user-independent, precise, time-, and cost-effective tool for analyzing vascularized constructs.
• The freely available algorithm excels in unambiguous vessel classification and statistical analysis.
• This approach advances the quantitative evaluation of angiogenesis in tissue engineering.