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

Dongmin Seo1,2, Euijin Han1, Samir Kumar1

  • 1Department of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.

Biosensors
|February 24, 2022
PubMed

Insights

A novel method combines magnetic sorting and lens-free shadow imaging for portable leukocyte classification. This technique accurately identifies white blood cell types, offering a low-cost alternative for clinical diagnosis.

Area of Science:

  • Biomedical Engineering
  • Clinical Diagnostics
  • Cellular Imaging

Background:

  • Complete blood count (CBC) instruments are expensive and complex, limiting access in resource-limited settings.
  • Existing on-chip blood cell tests lack innovation and rely on conventional methods.
  • There is a need for accessible, portable, and accurate methods for leukocyte analysis.

Purpose of the Study:

  • To develop a portable method for selective isolation and classification of leukocytes.
  • To utilize lens-free shadow imaging technique (LSIT) for differential leukocyte identification.
  • To establish shadow image analysis parameters for accurate cell classification.

Main Methods:

  • Combined magnetically activated cell sorting and differential density for leukocyte isolation.
  • Employed lens-free shadow imaging technique (LSIT) for high-purity leukocyte samples.
  • Developed and applied shadow parameters (e.g., "order ratio", "minimum ratio") for leukocyte classification.

Main Results:

  • Achieved high purity and concentration of isolated leukocytes, confirmed by flow cytometry.
  • Established a shadow image library for classifying three types of leukocytes.
  • Demonstrated high correlation (0.98 index) with clinical data, with 6% average error and 95% confidence.

Conclusions:

  • The developed LSIT-based method offers a promising, portable solution for leukocyte classification.
  • This technique has significant potential for point-of-care diagnostics, especially for rare cell detection.
  • The approach is suitable for diverse applications including biological, pharmaceutical, environmental, and clinical fields.