Logo of the Physikalisch-Technische Bundesanstalt

Optical Medical Imaging

Working Group 8.31

Imaging Flow Cytometry

Development of techniques to image single cells and particles in flow cytometry

Fluorescence images and light scatter patterns of spherical microparticles recorded during passage through the laser beam in a flow cell. Top row: Fluorescence images for different particles sizes and examples of double detection; Center row: related light scatter patterns in forward direction (1 quadrant, laser beam blocked); Bottom row: simulated forward light scatter patterns.

The fluorescence images of the flowing particles detected in sideward direction enable a clear differentiation between single particles (columns 1 and 2) and particle coincidences (columns 3 and 4). Coincidences are additionally characterized by specific interference patterns overlaid to the interference rings of the single particles, which are sensitive to the relative locations of the particles. These interferences can be explained by computer simulations, performed with the discrete dipole approximation (DDA) or T-matrix methods.

Optical flow cytometry is a well-established technique to analyze cell populations in laboratory medicine. Cells of the sample under investigation are guided one after the other through a laser beam. They are counted and differentiated according to the intensity of the scattered laser light or by detecting fluorescence from labels bound to cell subgroups of the sample. Accuracy and uncertainty of the technique are mainly determined by the occurrence of coincidences (two or more particles pass the laser beam simultaneously) or by cell agglomerates. Often, these events cannot safely be distinguished from single cells of larger size.

The research project „Imaging Flow Cytometry“ aims at the development of methods to record microscopic images of the cells when passing the optical beam. In this way, morphological information can be gained for each cell. The method offers even the chance to localize sources of fluorescence inside the cells, depending on cell size, spatial resolution and sensitivity of the image acquisition. Moreover, the technique measures the angular pattern of the light scattered by the cells which is then compared to and analyzed by simulations of light scattering. Using both, image and scatter pattern information, rare cells can be counted more precisely. The research is of particular interest for the development of new and advanced reference techniques for cell counting in laboratory medicine.