The detection of tumor cells and clusters in pleural effusion assists in the diagnosis of lung cancer. The proportion of tumor cells and clusters to the total number of cells in each patient varies substantially due to individual differences and the severity of the disease. The identification of one tumor cell or cluster from a large number of pleural effusions is the main challenge for hydrothorax tumor cell detection techniques. In the present study, by using A549 lung cancer and Met-5A mesothelial cell lines, a label-free microfluidic chip based on cell cluster size was designed. By setting the parameters of the chip, individual cells and clusters were able to enter different microfluidic channels. Subsequent to non-specific staining, the recovered components were stained using acridine orange (AO). A charge-coupled device camera was used to captured images of the cell, and the features of these cells were analyzed in their R and G channels using Matlab software to establish the characteristics and finally differentiate between the tumor and non-tumor cell or clusters. According to the results, when inlet A and B were under a velocity of 10 and 8.5 ml/h, respectively, the tumor cell clusters were successfully collected through microfluidic channels III-V, with a recovery rate of ~80%. Subsequent to staining with AO, the feature values in the R and G channels were identified, and initial differentiation was achieved. The present study combined the microfluidic chip, which is based on cluster size, with a computer identification method for pleural effusion. The successful differentiation of tumor cell clusters from non-tumor clusters provides the basis for the identification of tumor clusters in hydrothorax.
Keywords: acridine orange; cell cluster; image processing; lung cancer; mesothelial cell; microfluidic chip; pleural effusion.