Fully integrated point-of-care blood cell count using multi-frame morphology analysis

Wenchang Zhang; Ya Li; Bing Chen; Yuan Zhang; Ziqiang Du; Feibin Xiang; Yu Hu; Xiaochen Meng; Chunliang Shang; Shengfa Liang; Xiaonan Yang; Weihua Guan

doi:10.1016/j.bios.2022.115012

Fully integrated point-of-care blood cell count using multi-frame morphology analysis

Biosens Bioelectron. 2023 Mar 1:223:115012. doi: 10.1016/j.bios.2022.115012. Epub 2022 Dec 17.

Authors

Wenchang Zhang¹, Ya Li², Bing Chen², Yuan Zhang³, Ziqiang Du⁴, Feibin Xiang⁵, Yu Hu⁴, Xiaochen Meng⁶, Chunliang Shang⁷, Shengfa Liang⁵, Xiaonan Yang⁸, Weihua Guan⁹

Affiliations

¹ Key Lab of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China. Electronic address: zhangwenchang@ime.ac.cn.
² Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
³ Key Clinical Laboratory of Henan Province, Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
⁴ School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
⁵ Key Lab of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.
⁶ Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science & Technology University, Beijing, 100192, China.
⁷ Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
⁸ School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China. Electronic address: iexnyang@zzu.edu.cn.
⁹ 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.

PMID: 36542936
DOI: 10.1016/j.bios.2022.115012

Abstract

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.

Keywords: Blood cell count; Multi-frame morphological analysis; Point-of-care testing; Shrinkage-expansion structure; “In-flow” imaging.

MeSH terms

Biosensing Techniques*
Blood Cell Count
Erythrocytes
Humans
Leukocyte Count
Point-of-Care Systems*
Point-of-Care Testing