Simplified White Blood Cell Differential: An Inexpensive, Smartphone- and Paper-Based Blood Cell Count
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...
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Veröffentlicht in: | IEEE sensors journal 2019-09, Vol.19 (18), p.7822-7828 |
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description | 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. |
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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.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2019.2920235</identifier><identifier>PMID: 33223968</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acridine orange ; Autoimmune diseases ; Biomembranes ; Blood ; blood count ; Capillarity ; cell identification ; Counting ; Data acquisition ; Dyes ; Fluorescence ; Image analysis ; Image filters ; Leukocytes ; Lymphocytes ; Microfluidics ; Microscopy ; Optical fiber sensors ; Optical filters ; paper microfluidics ; Physicians ; Reagents ; Rinsing ; smartphone ; Smartphones ; Substrates</subject><ispartof>IEEE sensors journal, 2019-09, Vol.19 (18), p.7822-7828</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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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.</description><subject>Acridine orange</subject><subject>Autoimmune diseases</subject><subject>Biomembranes</subject><subject>Blood</subject><subject>blood count</subject><subject>Capillarity</subject><subject>cell identification</subject><subject>Counting</subject><subject>Data acquisition</subject><subject>Dyes</subject><subject>Fluorescence</subject><subject>Image analysis</subject><subject>Image filters</subject><subject>Leukocytes</subject><subject>Lymphocytes</subject><subject>Microfluidics</subject><subject>Microscopy</subject><subject>Optical fiber sensors</subject><subject>Optical filters</subject><subject>paper microfluidics</subject><subject>Physicians</subject><subject>Reagents</subject><subject>Rinsing</subject><subject>smartphone</subject><subject>Smartphones</subject><subject>Substrates</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkV9rFDEUxYMotq5-AOlLwJc-OGv-TTLpQ6Fdq7YUFVbRt5CZvemmzCbTZKbotzfLLqX2KRfyu-eew0HoLSVzSon-cLW8-DpnhOo504wwXj9Dh7Sum4oq0TzfzpxUgqvfB-hVzrekkKpWL9EB54xxLZtD5JZ-M_TeeVjhX2s_Aj7vY1zhBfQ9_uidgwRh9LY_wWcBXwb4M0DI_h7e4-XGpnFYxwAVtmGFv9sBUnVuc5F6JLKIUxhfoxfO9hne7N8Z-vnp4sfiS3X97fPl4uy66gQTY9XqDrRwYFvWKiFq6aSmraSUSkdqSi2UeNbVkjANylpJLAFoJGs1EYQDn6HTne4wtRtYdcV7sr0Zki9m_5povfn_J_i1uYn3RknVNFQUgeO9QIp3E-TRbHzuSg4bIE7ZMCF5uV4LXdB3T9DbOKVQ4hnGVPFImwLPEN1RXYo5J3APZigx2xbNtkWzbdHsWyw7R7sdDwAPfKOYEkTzf-_qlrs</recordid><startdate>20190915</startdate><enddate>20190915</enddate><creator>Bills, Matthew V.</creator><creator>Nguyen, Brandon T.</creator><creator>Yoon, Jeong-Yeol</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9305-0204</orcidid><orcidid>https://orcid.org/0000-0001-6371-1027</orcidid><orcidid>https://orcid.org/0000-0002-9720-6472</orcidid></search><sort><creationdate>20190915</creationdate><title>Simplified White Blood Cell Differential: An Inexpensive, Smartphone- and Paper-Based Blood Cell Count</title><author>Bills, Matthew V. ; Nguyen, Brandon T. ; Yoon, Jeong-Yeol</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-b9ce94feab2b74456f691b61116f0511ae155af56029e7aa60a0ee862b90403e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Acridine orange</topic><topic>Autoimmune diseases</topic><topic>Biomembranes</topic><topic>Blood</topic><topic>blood count</topic><topic>Capillarity</topic><topic>cell identification</topic><topic>Counting</topic><topic>Data acquisition</topic><topic>Dyes</topic><topic>Fluorescence</topic><topic>Image analysis</topic><topic>Image filters</topic><topic>Leukocytes</topic><topic>Lymphocytes</topic><topic>Microfluidics</topic><topic>Microscopy</topic><topic>Optical fiber sensors</topic><topic>Optical filters</topic><topic>paper microfluidics</topic><topic>Physicians</topic><topic>Reagents</topic><topic>Rinsing</topic><topic>smartphone</topic><topic>Smartphones</topic><topic>Substrates</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bills, Matthew V.</creatorcontrib><creatorcontrib>Nguyen, Brandon T.</creatorcontrib><creatorcontrib>Yoon, Jeong-Yeol</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>IEEE sensors journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bills, Matthew V.</au><au>Nguyen, Brandon T.</au><au>Yoon, Jeong-Yeol</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simplified White Blood Cell Differential: An Inexpensive, Smartphone- and Paper-Based Blood Cell Count</atitle><jtitle>IEEE sensors journal</jtitle><stitle>JSEN</stitle><date>2019-09-15</date><risdate>2019</risdate><volume>19</volume><issue>18</issue><spage>7822</spage><epage>7828</epage><pages>7822-7828</pages><issn>1530-437X</issn><eissn>1558-1748</eissn><coden>ISJEAZ</coden><abstract>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. 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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.</abstract><cop>New York</cop><pub>IEEE</pub><pmid>33223968</pmid><doi>10.1109/JSEN.2019.2920235</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-9305-0204</orcidid><orcidid>https://orcid.org/0000-0001-6371-1027</orcidid><orcidid>https://orcid.org/0000-0002-9720-6472</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Acridine orange Autoimmune diseases Biomembranes Blood blood count Capillarity cell identification Counting Data acquisition Dyes Fluorescence Image analysis Image filters Leukocytes Lymphocytes Microfluidics Microscopy Optical fiber sensors Optical filters paper microfluidics Physicians Reagents Rinsing smartphone Smartphones Substrates |
title | Simplified White Blood Cell Differential: An Inexpensive, Smartphone- and Paper-Based Blood Cell Count |
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