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Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT
Published on: November 27, 2019
Label-free automated neutropenia detection and grading using deep-ultraviolet microscopy
Ashkan Ojaghi1,2, Paloma Casteleiro Costa3,2, Christina Caruso4
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
Abstract:
Neutropenia is a condition identified by an abnormally low number of neutrophils in the bloodstream and signifies an increased risk of severe infection. Cancer patients are particularly susceptible to this condition, which can be disruptive to their treatment and even life-threatening in severe cases. Thus, it is critical to routinely monitor neutrophil counts in cancer patients. However, the standard of care to assess neutropenia, the complete blood count (CBC), requires expensive and complex equipment, as well as cumbersome procedures, which precludes easy or timely access to critical hematological information, namely neutrophil counts. Here we present a simple, low-cost, fast, and robust technique to detect and grade neutropenia based on label-free multi-spectral deep-UV microscopy. Results show that the developed framework for automated segmentation and classification of live, unstained blood cells in a smear accurately differentiates patients with moderate and severe neutropenia from healthy samples in minutes. This work has significant implications towards the development of a low-cost and easy-to-use point-of-care device for tracking neutrophil counts, which can not only improve the quality of life and treatment-outcomes of many patients but can also be lifesaving.
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