Quantitative analysis of cancer cell migration is critical for developing effective therapies to curb cancer metastasis. However, traditional methods are time-consuming and labor-intensive and lack quantitative capabilities. Cell volume change, a key physiological indicator of cell migration, is directly linked to phase change. In this work, we have developed a model that connects phase features from digital holographic microscopy (DHM) with cell healrate values from the wound healing assay. This approach aims to provide a rapid and quantitative evaluation of the breast cancer cell migration capability. Using DHM, six phase features of 231 cells treated with varying drug concentrations were extracted. It was observed that the rate of change of these phase features, termed characteristic parameters, showed a high linear correlation with cell healrate values from wound healing assays. Based on these linear correlations, a composite coefficient was derived by linearly combining the characteristic parameters of the six phase features. This composite coefficient was then linearly correlated with the cell healrate values to create a correlation model. This model establishes a strong connection between DHM-extracted morphological/biophysical features and cell migration metrics from a complementary assay. It provides a new, rapid, and quantitative method for assessing cancer cell migration in vitro and delivering valuable insights for cancer research.
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