Simulation and Experimental Analysis of an Automated System for Magnetically Labeling and Collecting Rare Blood Cells

To test the ability of a point-of-care cell detector to automatically label and trap cells, simulations and laboratory experiments on cell labeling and separation were performed. A static mixer’s cell labeling efficiency and a magnetic trap’s capture ability were simulated using computational fluid dynamics and tested in cell labeling and trapping experiments in the presence and absence of whole blood to determine the effect of red blood cells on labeled tumor cells detection. After each cell labeling and separation test a particle tracking microscope was used to detect particle motion, size and magnetophoretic mobility distribution thereby identifying and counting magnetically labeled cells. A statistical analysis of data was obtained during the test allowing a better understanding of cell labeling. The results of cell counts indicated the immunomagnetic particles were able to perform tumor cell labeling and separation tasks with good capture efficiency. The static mixer proved to have a similar cell labeling efficiency to that of the traditional multistep methods using shake-bed labeling. The velocimeter plots showed cells were successfully labeled by magnetic beads in the static mixer, and the magnetic trap was capable of capturing labeled particles. Whole blood was found to hinder cell detection by the velocimeter, and a simple post- processing step was introduced to ensure unlabeled cells are washed away properly.

Keywords: cell labeling, magnetic particles, magnetic separation, Hyperflux^tm analysis, velocimetry, computational fluid dynamics