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Fully integrated point-of-care blood cell count using multi-frame morphology analysis.
Zhang, Wenchang; Li, Ya; Chen, Bing; Zhang, Yuan; Du, Ziqiang; Xiang, Feibin; Hu, Yu; Meng, Xiaochen; Shang, Chunliang; Liang, Shengfa; Yang, Xiaonan; Guan, Weihua.
Afiliação
  • Zhang W; Key Lab of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China. Electronic address: zhangwenchang@ime.ac.cn.
  • Li Y; Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Chen B; Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Zhang Y; Key Clinical Laboratory of Henan Province, Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
  • Du Z; School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
  • Xiang F; Key Lab of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.
  • Hu Y; School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
  • Meng X; Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing, 100192, China.
  • Shang C; Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
  • Liang S; Key Lab of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.
  • Yang X; School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China. Electronic address: iexnyang@zzu.edu.cn.
  • Guan W; Department of Electrical Engineering, Pennsylvania State University, University Park, 16802, USA; Department of Biomedical Engineering, Pennsylvania State University, University Park, 16802, USA. Electronic address: wzg111@psu.edu.
Biosens Bioelectron ; 223: 115012, 2023 Mar 01.
Article em En | MEDLINE | ID: mdl-36542936
Point-of-care testing (POCT) of blood cell count (BCC) is an emerging approach that allows laypersons to identify and count whole blood cells through simple manipulation. To date, POCTs for BCC were mainly achieved by "stationary" images through blood smears or single-laity arranged cells in the microwell, making it difficult to obtain statistically sufficient numbers of cells. In this work, we present a fully integrated POCT device solely using "in-flow" imaging of 3 µL fingertip whole blood for improved identification and counting accuracy of BCC analysis. A miniaturized magnetic stirring module was integrated to maintain the temporal stability of cell concentration. A relatively high throughput (∼8000 cells/min) with a 30-fold dilution ratio of whole blood can be tested for as long as 1 h to examine sufficient numbers of cells, and the subclass cell concentration keeps constant. To improve the identification accuracy, multi-frame "in-flow" imaging was used to track the cell motion trails with multi-angle morphology analysis. This proof-of-concept was then validated with healthy whole blood samples and 75 cases of clinical patients with abnormal concentrations of red blood cells (RBCs), white blood cells (WBCs), and platelets (PLT). The average precision (AP) value of WBCs identification was improved from 0.8622 to 0.9934 using the multi-frame analysis method. And the high fitting degrees (>0.98) between our POCT device and the commercial clinical equipment indicated good agreement. This POCT device is user-friendly and cost-effective, making it a potential tool for diagnosing abnormal blood cell morphology or concentration in the field setting.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Sistemas Automatizados de Assistência Junto ao Leito Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Técnicas Biossensoriais / Sistemas Automatizados de Assistência Junto ao Leito Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article