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Flow cytometric analysis using digital signal processing

N A Zilmer1, M Godavarti, J J Rodriguez

  • 1Department of Electrical and Computer Engineering, University of Arizona, Tucson, USA.

Cytometry
|June 1, 1995
PubMed
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Digital pulse processing in flow cytometry captures more waveform data than analog methods. This advanced technique enhances particle analysis, enabling better discrimination of cells and improved optical alignment monitoring.

Area of Science:

  • Biotechnology
  • Analytical Chemistry
  • Cell Biology

Background:

  • Commercial flow cytometers use analog circuits for particle analysis, limiting measurements to pulse integral, height, and width.
  • This analog approach discards valuable information contained within the pulse waveform's shape.

Purpose of the Study:

  • To develop and evaluate a digital pulse waveform processing system for flow cytometry.
  • To demonstrate the advantages of digital processing over traditional analog methods for enhanced particle characterization.

Main Methods:

  • A digital pulse waveform processing system was developed, compatible with commercial flow cytometers and standard computational platforms.
  • Performance was compared against analog systems using synthetic waveforms, microspheres, and biological particles.

Related Experiment Videos

  • A protocol for quantitative optical alignment monitoring using digital pulse processing was designed.

    • Main Results:

    • The digital system accurately extracts additional waveform features like skewness, kurtosis, and Fourier properties.
    • Digital processing demonstrated superior accuracy and flexibility compared to analog methods.
    • The system enabled discrimination of particle classes and separation of single cells from doublets/aggregates, which were indistinguishable with analog processing.

    Conclusions:

    • Digital pulse waveform processing offers a significant advancement over analog methods in flow cytometry.
    • This technology provides richer data for particle analysis, improving cell discrimination and enabling new applications like optical alignment monitoring.