Automated Classification of Breast Cancer Cells Using High-Throughput Holographic Cytometry - Chen, Cindy X.; Park, Han Sang; Price, Hillel; Wax, Adam (Frontiers in Physics, 2021)
Characterization of circulating tumor cells with quantitative phase imaging could provide a unique approach for identifying early biomarkers for cancer. However, current QPI cytometers have limitations which can prevent their use on heterogeneous tumor cell populations. Here we present our holographic cytometry approach applied to identifying carcinogen-exposed cells, namely, Cadmium-treated breast epithelial cells, in contrast to normal and cancerous cells. Based on single-cell phase images collected in high throughput by the holographic cytometer, we analyze the biophysical properties of different cell lines to discriminate by phenotype. Both phenotypic profiling and deep learning show comparable high accuracy levels and reveal key defining biophysical cellular features.