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Clarifying and Imaging Candida albicans Biofilms
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Rapid discrimination of Candida species based on optical diffraction pattern.

Mitra Abedini1, Hojatollah Montazeri1, Ensieh Lotfali2

  • 1Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Journal of Photochemistry and Photobiology. B, Biology
|February 3, 2023
PubMed
Summary

Rapidly detect and differentiate common Candida species using optical elastic scattering diffraction patterns from their colonies. This method offers a semi-automatic approach for identifying fungal infections in immunocompromised patients.

Keywords:
Candida speciesElastic light scatteringImage processingK-nearest neighbors (k−NN) algorithmOptical diffraction pattern

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Area of Science:

  • Biophotonics
  • Medical Mycology
  • Spectroscopy

Background:

  • Candidiasis is a significant fungal infection, primarily affecting immunocompromised individuals.
  • Early detection and species identification of Candida are crucial for effective treatment and management.
  • Current diagnostic methods can be time-consuming, necessitating faster alternatives.

Purpose of the Study:

  • To develop and evaluate a novel optical method for rapid detection and discrimination of common Candida species.
  • To investigate the potential of using colony diffraction patterns for fungal identification.

Main Methods:

  • Utilized laser light (632 nm) and a custom optical system to capture diffraction patterns from colonies of five Candida species (C. albicans, C. tropicalis, C. glabrata, C. guilliermondii, C. parapsilosis).
  • Recorded, processed, and analyzed optical elastic scattering diffraction patterns.
  • Employed statistical feature extraction and classification techniques for semi-automatic identification.

Main Results:

  • Distinct optical diffraction patterns were observed for each of the five Candida species, correlating with their unique colony structures.
  • The technique demonstrated recognizable differences between the diffraction patterns.
  • Semi-automatic detection and discrimination were achieved through image analysis and classification.

Conclusions:

  • Optical elastic scattering diffraction patterns of Candida colonies provide a basis for species differentiation.
  • This biophotonic approach shows potential for rapid, semi-automatic detection and discrimination of clinically relevant Candida species.
  • Further development could lead to a valuable tool for diagnosing and monitoring candidiasis.