TY - JOUR
T1 - Simplified White Blood Cell Differential
T2 - An Inexpensive, Smartphone- and Paper-Based Blood Cell Count
AU - Bills, Matthew V.
AU - Nguyen, Brandon T.
AU - Yoon, Jeong Yeol
N1 - Funding Information:
Manuscript received March 18, 2019; revised May 15, 2019; accepted May 29, 2019. Date of publication May 31, 2019; date of current version August 15, 2019. This work was supported by the Biomedical Imaging and Spectroscopy Training Grant from the U.S. National Institutes of Health, under Grant T32-EB000809. The associate editor coordinating the review of this paper and approving it for publication was Dr. Gymama Slaughter. (Corresponding author: Jeong-Yeol Yoon.) The authors are with the Department of Biomedical Engineering, The University of Arizona, Tucson, AZ 85721 USA (e-mail: billsm@ email.arizona.edu; btnguyen@email.arizona.edu; jyyoon@email.arizona.edu). Digital Object Identifier 10.1109/JSEN.2019.2920235
Publisher Copyright:
© 2001-2012 IEEE.
PY - 2019/9/15
Y1 - 2019/9/15
N2 - Sorting and measuring blood by cell type is extremely valuable clinically and provides physicians with key information for diagnosing many different disease states including: leukemia, autoimmune disorders, and bacterial infections. Despite the value, the present methods are unnecessarily costly and inhibitive particularly in resource poor settings, as they require multiple steps of reagent and/or dye additions and subsequent rinsing followed by manual counting using a hemocytometer, or they require a bulky, expensive equipment such as a flow cytometer. While direct on-paper imaging has been considered challenging, paper substrate offers a strong potential to simplify such reagent/dye addition and rinsing. In this paper, three-layer paper-based device is developed to automate such reagent/dye addition and rinsing via capillary action, and separating white blood cells (WBCs) from whole blood samples. Direct on-paper imaging is demonstrated using a commercial microscope attachment to a smartphone coupled with a blue LED and 500 nm long pass optical filter. Image analysis is accomplished using an original MATLAB code, to evaluate the total WBC count, and differential WBC count, i.e., granulocytes (primarily neutrophils) versus agranulocytes (primarily lymphocytes). Only a finger-prick of whole blood is required for this assay. The total assay time from finger-prick to data collection is under five minutes. Comparison with a hemocytometry-based manual counting corroborates the accuracy and effectiveness of the proposed method. This approach could be potentially used to help make blood cell counting technologies more readily available, especially in resource poor and point-of-care settings.
AB - Sorting and measuring blood by cell type is extremely valuable clinically and provides physicians with key information for diagnosing many different disease states including: leukemia, autoimmune disorders, and bacterial infections. Despite the value, the present methods are unnecessarily costly and inhibitive particularly in resource poor settings, as they require multiple steps of reagent and/or dye additions and subsequent rinsing followed by manual counting using a hemocytometer, or they require a bulky, expensive equipment such as a flow cytometer. While direct on-paper imaging has been considered challenging, paper substrate offers a strong potential to simplify such reagent/dye addition and rinsing. In this paper, three-layer paper-based device is developed to automate such reagent/dye addition and rinsing via capillary action, and separating white blood cells (WBCs) from whole blood samples. Direct on-paper imaging is demonstrated using a commercial microscope attachment to a smartphone coupled with a blue LED and 500 nm long pass optical filter. Image analysis is accomplished using an original MATLAB code, to evaluate the total WBC count, and differential WBC count, i.e., granulocytes (primarily neutrophils) versus agranulocytes (primarily lymphocytes). Only a finger-prick of whole blood is required for this assay. The total assay time from finger-prick to data collection is under five minutes. Comparison with a hemocytometry-based manual counting corroborates the accuracy and effectiveness of the proposed method. This approach could be potentially used to help make blood cell counting technologies more readily available, especially in resource poor and point-of-care settings.
KW - Acridine orange
KW - blood count
KW - cell identification
KW - paper microfluidics
KW - smartphone
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U2 - 10.1109/JSEN.2019.2920235
DO - 10.1109/JSEN.2019.2920235
M3 - Article
AN - SCOPUS:85070966515
SN - 1530-437X
VL - 19
SP - 7822
EP - 7828
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 18
M1 - 8727409
ER -