טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentWeigler Ariel
SubjectNoninvasive In-Vivo Leukocyte Microscopy in Human
DepartmentDepartment of Biomedical Engineering
Supervisor Professor Dvir Yelin
Full Thesis textFull thesis text - English Version


Abstract

Detailed classification and counting of leucocytes (white blood cells) is an important part of most blood tests, reliably indicating the status of the immune system. Differentiation between the various types of leucocytes is often required for diagnosing a variety of illnesses, including allergies, various malignancies and immunodeficiency diseases. The most common types of leucocytes in healthy adults are neutrophils and lymphocytes, typically comprising approximately 62% and 30% of the total leucocyte population, respectively. Differentiating between these cell types is often required for identifying sources of infection in ill patients; higher-than-normal neutrophil count may indicate active immune response to bacterial or fungal infection, while high lymphocyte count may indicate viral infection.

In the current study, we employ spectrally encoded flow cytometry (SEFC) for noninvasive imaging and counting of leucocytes in patients, including differentiation between granulocytes and mononuclear cells. By focusing a single transverse line within the cross section of a small blood vessel in a patient lip, and measuring the backscattered light with a high-speed spectrometer, a two-dimensional confocal image of flowing blood cells is acquired which allows the identification of leucocytes among the red cells background. Image data obtained from healthy human volunteers was analyzed and compared to the standard complete blood count for reference. The current study demonstrates the potential of SEFC to noninvasively analyze the immune system status at the point of care and study leucocyte morphology and dynamics in-vivo. In addition, we demonstrate in-vitro leukocyte differentiation using a custom image processing algorithm, establishing the potential of SEFC as a screening tool for blood samples.