Area-based cell colony surviving fraction evaluation: A novel fully automatic approach using general-purpose...

Area of Science:

• Cell Biology
• Biotechnology
• Medical Imaging

Background:

• Clonogenic assays are vital for assessing anti-proliferative treatment effects on cell cultures.
• Manual Surviving Fraction (SF) measurement is operator-dependent, prone to errors, and struggles with merging colonies.
• Traditional methods neglect colony size, a factor correlated with treatment efficacy.

Purpose of the Study:

• To develop and validate a fully automatic, computer-assisted method for Surviving Fraction (SF) quantification.
• To improve the accuracy and reproducibility of SF measurements in clonogenic assays.
• To address the limitations of manual colony counting, including operator variability and colony merging.

Main Methods:

• A novel approach utilizes Circle Hough Transform for automatic well detection.
• Local adaptive thresholding calculates the Area Covered by Colony (ACC) for SF quantification.
• The method relies on ACC percentage, bypassing manual colony counting and its associated issues.

Main Results:

• The automated ACC-based method demonstrated high correlation with traditional manual counting.
• Correlation coefficients (r) of 0.9791 for MCF7 and 0.9682 for MCF10A cells were achieved.
• Results indicate the robustness and accuracy of the proposed automated approach.

Conclusions:

• The developed computer-assisted methodology offers a reliable alternative for SF evaluation.
• This approach can enhance the precision and efficiency of clonogenic assays in laboratory settings.
• Integration as an expert system can standardize SF measurements in research and clinical practice.