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

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.

Smartphone- and Cloud-based Artificial Intelligence Quantitative Analysis System (SCAISY) for SARS-CoV-2-specific IgG Antibody Lateral Flow Assays

“…POCT devices are highly portable and automated diagnostic instruments that can be used in various settings such as hospitals, private homes, outpatient clinics, and remote locations [44][45][46]. These devices can be used in real-world scenarios such as outdoor or indoor camps and by individuals or groups in different environments.…”

Leukocyte differential based on an imaging and impedance flow cytometry of microfluidics coupled with deep neural networks

“…Meanwhile, based on microfluidic imaging flow cytometry, optical signals (e.g., scattered lights and optical images) of traveling single cells can be significantly improved than conventional hematology analyzers since cell positions can be better confined to specific focal planes due to microfabricated flow channels, leading to improved accuracies of leukocyte differentials [17][18][19][20][21]. More specifically, classification accuracies of 95% [20] and 70.3% [21] for 3-part and 8-part leukocyte differentials were reported based on lens-free shadow imaging and stain-free imaging plus machine learning, respectively.…”

Multiparameter mobile blood analysis for complete blood count using contrast-enhanced defocusing imaging and machine vision

“…[34][35][36][37][38][39] But most imaging blood analysis methods use complex or susceptible sample preparations, including fluorescence staining and density centrifugation, to achieve WBC subtype differential. Label-free imaging techniques, such as deep-ultraviolet microscopy [40][41][42] and lens-free microscopy, 43,44 can solve this problem by characterizing WBCs with their endogenic properties. And they will be suitable for application in point-of-care settings due to the convenient sample preparation.…”