title: Detecting infection-related changes in peripheral blood smears with image analysis techniques.
abstract: High-resolution image analysis has the potential to flag subtle changes in white blood cell morphology that may indicate the presence of certain diseases. A study was made of the feasibility of identifying patients with hematologic bacterial infections (sepsis) using measurements on Wright-Giemsa-stained peripheral blood smears. Neutrophils and lymphocytes from a group of patients with sepsis and from a control group were digitized, and parameters quantifying geometry, color, texture and shape were extracted. While color parameters differed the most between the infected and control samples, substantial differences in geometric, texture and shape parameters also were observed. Analysis of the data showed that individual neutrophils and lymphocytes from patients with sepsis were distinguishable from those of the control group with better than 84% accuracy. When average parameters were calculated from all cells of one type for each specimen, 100% accurate classification was obtained. These studies demonstrate that the image-analysis techniques used are sensitive enough to detect disease-related changes in cell morphology that are generally too subtle for reliable detection by the human eye. Future experiments will determine the specificity of this test for bacterial infections and will explore the possibility of using image analysis techniques on peripheral blood to detect and monitor a wide variety of diseases.
mesh_terms: D003581:Cytodiagnosis / Q000379:methods; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D008214:Lymphocytes / Q000473:pathology*; D009504:Neutrophils / Q000473:pathology*; D018805:Sepsis / Q000097:blood* / Q000175:diagnosis; D013194:Staining and Labeling / Q000379:methods; D013223:Statistics as Topic