A method for quantifying cell size from differential interference contrast images: validation and application to...

Area of Science:

• Cell biology
• Microscopy
• Image analysis

Background:

• Accurate measurement of cell shape and size is crucial for understanding cellular processes.
• Differential Interference Contrast (DIC) microscopy offers high contrast for unstained biological samples.
• Automated methods are needed to improve the efficiency and objectivity of cell size analysis.

Purpose of the Study:

• To develop and validate an automatic image analysis method for determining spheroidal cell shape and size from DIC time-series images.
• To assess the accuracy and limitations of the developed method concerning focal planes and image resolution.
• To apply the method for quantifying cell volume changes under osmotic stress.

Main Methods:

• Development of an automatic image analysis program incorporating edge detection and dynamic programming for edge linking.
• Comparison of results from DIC images with confocal microscopy images of fluorescently labeled cell membranes.
• Evaluation of the method's performance across different focal planes and resolutions.

Main Results:

• A 1-micrometer focal drift can overestimate cell volume by up to 14.1% due to DIC shadowing effects.
• Accurate measurements are achievable when the focal plane is slightly above the cell center, yielding a 1.9% volume error.
• The method successfully quantified cell volume changes induced by acute osmotic stress.

Conclusions:

• The developed automatic image analysis method provides accurate cell volume measurements from DIC images under optimal focal conditions.
• Understanding and controlling focal plane is critical for minimizing errors in DIC-based cell volume analysis.
• This method is a valuable tool for studying dynamic cellular responses, such as those to osmotic stress.