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High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

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A fully automated system to study skin surface patterns.

P Corcuff¹, F Chatenay, J L Leveque

¹Laboratoires de Recherche Fondamentale, L'Oreal, Avenue de Saint-Germain, 93601 Aulnay-sous-Bois Cédex, France.

International Journal of Cosmetic Science

|May 27, 2009

Summary

This summary is machine-generated.

This study introduces an automated image analysis system for measuring human skin microrelief, revealing deep facial wrinkles emerge by age 30. The technology quantifies furrow depth, density, and direction for aging skin research.

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Area of Science:

Dermatology
Image Analysis
Biophysics

Background:

Human skin microrelief, including wrinkles, is a key indicator of aging and environmental damage.
Previous methods for skin microrelief analysis were manual and time-consuming.
Automating skin replica analysis offers potential for more efficient and objective measurements.

Purpose of the Study:

To automate the image analysis of human skin replicas for quantitative microrelief measurement.
To assess the feasibility of using automated analysis for different skin features like forearm microrelief and facial wrinkles.
To investigate the onset of deep wrinkles in human facial skin.

Main Methods:

An automated system utilizing a Quantimet 900 and a motorized specimen stage was developed.
The system analyzes Silflo(R) replicas, processing forty replicas in six hours.
Variable angle lighting (26 and 38 degrees) was employed to measure furrows of different depths (5-100 µm and 50-1000 µm).

Main Results:

The automated system successfully quantified furrow direction, density, and mean depth.
Analysis of volar forearm skin revealed microrelief characteristics.
Deep facial wrinkles were observed to form as early as age 30.

Conclusions:

Automated image analysis provides an efficient method for quantifying skin microrelief.
The study highlights the early appearance of deep wrinkles, suggesting significant cumulative effects of aging and environmental factors.
This technology can aid in understanding skin aging and the impact of stressors.