Detection of circulating tumor cells using imaging flow cytometry

Abstract

An automated identification of the types of white blood cells in a blood sample facilitates the manual identification of cancerous or other abnormal blood cells in the sample. Classifiers are predetermined for each type of white blood cell and subsequently used to automatically process images of cells in a sample stained with a nuclear dye or stain. The classifiers each comprise a linear weighted combination of morphometric and photometric features previously selected for white blood cells that were identified using monoclonal antibody stains. Red blood cells and excess fluid are removed from a sample being processed upstream of an imaging region of the imaging system. A plurality of different types of images are produced for each cell by the imaging system enabling automated identification of the white blood cells. Images of any cells not thus identified are manually reviewed to detect cancerous or abnormal cells.