Optimization of Mitotic Index Quantification Using the Amnis ImageStream Imaging Flow Cytometer

The mitotic index is a critical indicator of the proliferative activity of cell populations and is widely used in oncology and stem cell research. One of the most promising methods for its assessment is imaging flow cytometry implemented on the Amnis ImageStream platform using the IDEAS software. A critical evaluation of the built-in Wizards, Cell Cycle-Mitosis algorithm revealed several limitations, including a high degree of operator-dependent variability in gate setting and difficulties in identifying the mitotic population in the absence of distinct peaks on the cell cycle histogram. An alternative approach, the Mean + xSD algorithm, was proposed. This method is based on automated quantitative assessment of the Bright Detail Intensity R3 parameter and excludes the need for manual gating and histogram interpretation. Using the Caco2 and HT-29 cell lines, we demonstrated that the proposed algorithm exhibits accuracy comparable to the classical IDEAS algorithm, and in some cases provides even more reproducible quantification of the mitotic index. These results demonstrate the potential of the new algorithm as a more objective and robust tool for analyzing mitotic activity in cultured cells.