CellViCAM--Cell viability classification for animal cell cultures using dark field micrographs

Area of Science:

• Biotechnology
• Cell Biology
• Image Analysis

Background:

• Online monitoring of cell density and viability is crucial for biotechnical processes, especially in animal cell culture.
• Current methods often rely on dyes or fluorescent labeling, which can be cumbersome or interfere with cell function.

Purpose of the Study:

• To introduce CellViCAM, an optical approach for automated cell detection and viability classification of suspended mammalian cells.
• To develop a reagent-free method for assessing cell health and density in real-time.

Main Methods:

• Utilizing dark field microscopy combined with image processing and supervised machine learning.
• Establishing an efficient cell detection procedure for density estimation.
• Developing a semi-automatic training data generation for reagent-free viability analysis.

Main Results:

• The CellViCAM system accurately detects and classifies cell viability without dyes or fluorescent labels.
• The method provides cell density estimations comparable to established techniques.
• Validation demonstrates equivalence to staining-based methods and potential for differentiated cell state classification (living, necrotic, apoptotic).

Conclusions:

• CellViCAM offers a powerful, dye-free optical platform for real-time monitoring of mammalian cell cultures.
• This technology enables precise control and optimization of biotechnical processes.
• The system advances cell state analysis beyond simple viability to detailed apoptosis staging.