Automated image cytometry for detection of rare, viral antigen‐positive cells in peripheral blood

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Abstract
A cell detection method based upon automated screening is described for recognition of low frequencies (1 in 100,000) of immuno‐enzymatically labelled white blood cells in human peripheral blood. The used image cytometry instrumentation (LEYTAS) includes a wide‐field, fully automated microscope (Autoplan) and a modular image analysis computer (MIAC), both from Leica, Wetzlar, Germany. The MIAC contains image boards for optimum use of mathematical morphology algorithms. Communication with the MIAC is via a personal computer. Programs for automated cell analysis have been written in C language. Main features of the system are fast analysis of, large microscope fields including a count of all cells, selection of objects of interest (alarms), and display of digitally stored images of these alarms. We tested this system for the detection of white blood cells expressing antigen of cytomegalovirus (pp65) in 50 human blood smears from kidney transplant recipients. Immuno‐enzymatic (peroxidase) staining was performed with DAB and counterstaining with hematoxylin. For determination of the sensitivity, a series of dilutions of a positive sample with a negative sample was performed. The lowest frequency detected was 1 antigenpositive cell / 3 × 105 antigen‐negative cells. Screening time was about 60 min for one million cells.