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Field-Portable Leukocyte Classification Device Based on Lens-Free Shadow Imaging Technique

Authors
Seo, D.Han, E.Kumar, S.Jeon, E.Nam, M.-H.Jun, H.S.Seo, S.
Issue Date
2월-2022
Publisher
MDPI
Keywords
Blood cell classification; CMOS image sensor; Diagnostics; Lens-free shadow imaging technique (LSIT); Leukocytes
Citation
Biosensors, v.12, no.2
Indexed
SCIE
SCOPUS
Journal Title
Biosensors
Volume
12
Number
2
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/136598
DOI
10.3390/bios12020047
ISSN
2079-6374
Abstract
The complete blood count (CBC) is one of the most important clinical steps in clinical diagnosis. The instruments used for CBC are usually expensive and bulky and require well-trained operators. Therefore, it is difficult for medical institutions below the tertiary level to provide these instruments, especially in underprivileged countries. Several reported on-chip blood cell tests are still in their infancy and do not deviate from conventional microscopic or impedance measurement methods. In this study, we (i) combined magnetically activated cell sorting and the differential density method to develop a method to selectively isolate three types of leukocytes from blood and obtain samples with high purity and concentration for portable leukocyte classification using the lens-free shadow imaging technique (LSIT), and (ii) established several shadow parameters to identify the type of leukocytes in a complete leukocyte shadow image by shadow image analysis. The purity of the separated leukocytes was confirmed by flow cytometry. Several shadow parameters such as the “order ratio” and “minimum ratio” were developed to classify the three types of leukocytes. A shadow image library corresponding to each type of leukocyte was created from the tested samples. Compared with clinical reference data, a correlation index of 0.98 was obtained with an average error of 6% and a confidence level of 95%. This technique offers great potential for biological, pharmaceutical, environmental, and clinical applications, especially where point-of-care detection of rare cells is required. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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