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Related Experiment Video

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Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy (DHM)
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Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy (DHM)

Published on: November 1, 2017

An improved method for quantifying hematozoa by digital microscopy.

Lucas W Degroote1, Paul G Rodewald

  • 1School of Environment and Natural Resources, The Ohio State University, 210 Kottman Hall, 2021 Coffey Rd, Columbus, Ohio 43210, USA. degroote.1@gmail.com

Journal of Wildlife Diseases
|April 26, 2008
PubMed
Summary
This summary is machine-generated.

Quantifying hematozoan infections is challenging. This study introduces a digital method using ImageJ software to rapidly and precisely estimate parasite intensity in erythrocytes, improving accuracy for low to moderate infections.

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Area of Science:

  • Parasitology
  • Bioimaging
  • Computational Biology

Background:

  • Accurate quantification of hematozoan infection intensity is crucial but often hindered by the laborious manual counting of erythrocytes.
  • Traditional methods require visual assessment of parasites against a large number of red blood cells, limiting throughput and precision.

Purpose of the Study:

  • To develop and validate a rapid and precise digital method for quantifying hematozoan infection intensity.
  • To overcome the limitations of manual erythrocyte counting in determining parasite load.

Main Methods:

  • Utilized ImageJ software to count erythrocyte nuclei from digital images, circumventing manual erythrocyte quantification.
  • Calculated a field:image ratio to extrapolate erythrocyte counts from digital images to a microscope's larger field of view.
  • Estimated infection intensity by quantifying parasites relative to over 50,000 erythrocytes using the digital method.

Main Results:

  • Field:image ratios were consistently calculated across 10 slides, demonstrating reliability (resampling P = 0.049).
  • Digital quantification of 50,000 erythrocytes yielded significantly higher infection intensity estimates (0.46 times) compared to manual counts of 2,000 erythrocytes (bootstrap P = 0.02).
  • The digital method proved rapid and precise for estimating hematozoan infection intensity.

Conclusions:

  • Digital quantification using ImageJ offers a significant improvement over manual methods for assessing hematozoan infections.
  • This approach provides a rapid, precise, and scalable solution for quantifying low to moderate intensity hematozoan infections.
  • The proposed method enhances diagnostic capabilities in parasitology and related fields.