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Development of New Staining Procedures for Diagnosing Cryptosporidium spp. in Fecal Samples by Computerized Image Analysis

Published online by Cambridge University Press:  15 October 2021

Saulo Hudson Nery Loiola ,
Felipe Lemes Galvão ,
Bianca Martins dos Santos ,
Stefany Laryssa Rosa ,
Felipe Augusto Soares ,
Sandra Valéria Inácio ,
Celso Tetsuo Nagase Suzuki ,
Edvaldo Sabadini ,
Katia Denise Saraiva Bresciani  and
Alexandre Xavier Falcão
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Saulo Hudson Nery Loiola*
Affiliation:
School of Medical Sciences, University of Campinas, 126 Tessália Vieira de Camargo St., Campinas, São Paulo 13083-887, Brazil
Felipe Lemes Galvão
Affiliation:
University of Campinas, Institute of Computing, 573, IC-3,5 Saturnino de Brito St., Room 364, Campinas, São Paulo 13083-852, Brazil
Bianca Martins dos Santos
Affiliation:
School of Medical Sciences, University of Campinas, 126 Tessália Vieira de Camargo St., Campinas, São Paulo 13083-887, Brazil
Stefany Laryssa Rosa
Affiliation:
School of Medical Sciences, University of Campinas, 126 Tessália Vieira de Camargo St., Campinas, São Paulo 13083-887, Brazil
Felipe Augusto Soares
Affiliation:
School of Medical Sciences, University of Campinas, 126 Tessália Vieira de Camargo St., Campinas, São Paulo 13083-887, Brazil
Sandra Valéria Inácio
Affiliation:
School of Veterinary Medicine, São Paulo State University (UNESP), 793 Clóvis Pestana St., Araçatuba, São Paulo 16050-680, Brazil
Celso Tetsuo Nagase Suzuki
Affiliation:
University of Campinas, Institute of Computing, 573, IC-3,5 Saturnino de Brito St., Room 364, Campinas, São Paulo 13083-852, Brazil
Edvaldo Sabadini
Affiliation:
University of Campinas, Institute of Chemistry, 126 Josué de Castro St., Campinas, São Paulo 13083-861, Brazil
Katia Denise Saraiva Bresciani
Affiliation:
School of Veterinary Medicine, São Paulo State University (UNESP), 793 Clóvis Pestana St., Araçatuba, São Paulo 16050-680, Brazil
Alexandre Xavier Falcão
Affiliation:
University of Campinas, Institute of Computing, 573, IC-3,5 Saturnino de Brito St., Room 364, Campinas, São Paulo 13083-852, Brazil
Jancarlo Ferreira Gomes
Affiliation:
School of Medical Sciences, University of Campinas, 126 Tessália Vieira de Camargo St., Campinas, São Paulo 13083-887, Brazil University of Campinas, Institute of Computing, 573, IC-3,5 Saturnino de Brito St., Room 364, Campinas, São Paulo 13083-852, Brazil
*
*Corresponding author: Saulo Hudson Nery Loiola, E-mail: [email protected]
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Abstract

Interpretation errors may still represent a limiting factor for diagnosing Cryptosporidium spp. oocysts with the conventional staining techniques. Humans and machines can interact to solve this problem. We developed a new temporary staining protocol associated with a computer program for the diagnosis of Cryptosporidium spp. oocysts in fecal samples. We established 62 different temporary staining conditions by studying 20 experimental protocols. Cryptosporidium spp. oocysts were concentrated using the Three Fecal Test (TF-Test®) technique and confirmed by the Kinyoun method. Next, we built a bank with 299 images containing oocysts. We used segmentation in superpixels to cluster the patches in the images; then, we filtered the objects based on their typical size. Finally, we applied a convolutional neural network as a classifier. The trichrome modified by Melvin and Brooke, at a concentration use of 25%, was the most efficient dye for use in the computerized diagnosis. The algorithms of this new program showed a positive predictive value of 81.3 and 94.1% sensitivity for the detection of Cryptosporidium spp. oocysts. With the combination of the chosen staining protocol and the precision of the computational algorithm, we improved the Ova and Parasite exam (O&P) by contributing in advance toward the automated diagnosis.

Keywords

Cryptosporidium spp.fecesmachine learningoocystsstain
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 27 , Issue 6 , December 2021 , pp. 1518 - 1528
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

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