Diameter-dependent classification of dermal vasculature using optical coherence tomography angiography

Area of Science:

• Dermatology
• Medical Imaging
• Biomedical Engineering

Background:

• Dermal blood vessels are crucial for skin health and homeostasis.
• Optical Coherence Tomography Angiography (OCTA) enables non-invasive assessment of skin vasculature.
• Current OCTA methods have limitations in classifying different vessel types.

Purpose of the Study:

• To develop and validate a diameter-dependent algorithm for classifying dermal blood vessels using OCTA.
• To preserve three-dimensional (3D) information for detailed vascular analysis.
• To investigate age-related alterations in different dermal vessel types and their relationship with epidermal thickness.

Main Methods:

• OCTA data acquired using a swept-source OCT system.
• Application of optical microangiography (OMAG), vesselness, and diameter map filters.
• Visual classification of vessels into micro, intermediate, and thick types based on diameter thresholds (80 µm and 160 µm).
• Analysis of 124 female subjects aged 20-79 years.

Main Results:

• A 3D visualization of dermal vascular structure was achieved.
• Micro-vessels were found in the upper dermis, while thick vessels were in the deeper dermis.
• Micro-vessel volume density decreased with age (r=-0.36) and correlated positively with epidermal thickness (r=0.50).
• Thick vessel volume density increased with age (r=0.2) and showed no significant correlation with epidermal thickness (r=0.13).

Conclusions:

• A novel 3D quantification method for dermal blood vessels using OCTA was proposed.
• The diameter-dependent classification provides valuable vessel metrics like volume density.
• This approach can enhance the understanding of dermal vasculature function and diagnostic applications in skin aging.