Literature DB >> 33514412

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.

Yoko Nagamori1,2, Ruth Hall Sedlak3, Andrew DeRosa3, Aleah Pullins3, Travis Cree3, Michael Loenser4, Benjamin S Larson5, Richard Boyd Smith5, Cory Penn4, Richard Goldstein4.   

Abstract

BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST system was developed to provide simpler and easier fecal examinations which are less influenced by examiners' skills. This system consists of three components: a sample preparation device, an automated microscope scanner, and analysis software. The objectives of this study were to qualitatively evaluate the performance of the VETSCAN IMAGYST system on feline parasites (Ancylostoma and Toxocara cati) and protozoan parasites (Cystoisospora and Giardia) and to assess and compare the performance of the VETSCAN IMAGYST centrifugal flotation method to reference centrifugal and passive flotation methods.
METHODS: To evaluate the diagnostic performance of the scanning and algorithmic components of the VETSCAN IMAGYST system, fecal slides were prepared by the VETSCAN IMAGYST centrifugal flotation technique with pre-screened fecal samples collected from dogs and cats and examined by both an algorithm and parasitologists. To assess the performance of the VETSCAN IMAGYST centrifugal flotation technique, diagnostic sensitivity and specificity were calculated and compared to those of conventional flotation techniques.
RESULTS: The performance of the VETSCAN IMAGYST algorithm closely correlated with evaluations by parasitologists, with sensitivity of 75.8-100% and specificity of 93.1-100% across the targeted parasites. For samples with 50 eggs or less per slide, Lin's concordance correlation coefficients ranged from 0.70 to 0.95 across the targeted parasites. The results of the VETSCAN IMAGYST centrifugal flotation method correlated well with those of the conventional centrifugal flotation method across the targeted parasites: sensitivity of 65.7-100% and specificity of 97.6-100%. Similar results were observed for the conventional passive flotation method compared to the conventional centrifugal flotation method: sensitivity of 56.4-91.7% and specificity of 99.4-100%.
CONCLUSIONS: The VETSCAN IMAGYST scanning and algorithmic systems with the VETSCAN IMAGYST fecal preparation technique demonstrated a similar qualitative performance to the parasitologists' examinations with conventional fecal flotation techniques. Given the deep learning nature of the VETSCAN IMAGYST system, its performance is expected to improve over time, enabling it to be utilized in veterinary clinics to perform fecal examinations accurately and efficiently.

Entities:  

Keywords:  Ancylostoma; Cyst; Cystoisospora; Deep learning; Fecal egg identification; Giardia; Oocyst; Toxocara cati; Veterinary parasitology diagnostic

Year:  2021        PMID: 33514412     DOI: 10.1186/s13071-021-04591-y

Source DB:  PubMed          Journal:  Parasit Vectors        ISSN: 1756-3305            Impact factor:   3.876


  35 in total

Review 1.  Epidemiologic and zoonotic aspects of ascarid infections in dogs and cats.

Authors:  Alice C Y Lee; Peter M Schantz; Kevin R Kazacos; Susan P Montgomery; Dwight D Bowman
Journal:  Trends Parasitol       Date:  2010-02-19

2.  Prevalence of fecal-borne parasites detected by centrifugal flotation in feline samples from two shelters in upstate New York.

Authors:  Araceli Lucio-Forster; Dwight D Bowman
Journal:  J Feline Med Surg       Date:  2011-02-22       Impact factor: 2.015

Review 3.  Hookworm infection.

Authors:  Alex Loukas; Peter J Hotez; David Diemert; Maria Yazdanbakhsh; James S McCarthy; Rodrigo Correa-Oliveira; John Croese; Jeffrey M Bethony
Journal:  Nat Rev Dis Primers       Date:  2016-12-08       Impact factor: 52.329

Review 4.  Toxocara cati: an underestimated zoonotic agent.

Authors:  Maggie Fisher
Journal:  Trends Parasitol       Date:  2003-04

5.  Retrospective survey of parasitism identified in feces of client-owned cats in North America from 2007 through 2018.

Authors:  Yoko Nagamori; Mark E Payton; Emily Looper; Hadley Apple; Eileen M Johnson
Journal:  Vet Parasitol       Date:  2019-12-03       Impact factor: 2.738

Review 6.  The epidemiology and public health importance of toxocariasis: a zoonosis of global importance.

Authors:  Calum N L Macpherson
Journal:  Int J Parasitol       Date:  2013-08-14       Impact factor: 3.981

7.  Endoparasite prevalence and recurrence across different age groups of dogs and cats.

Authors:  Maureen C Gates; Thomas J Nolan
Journal:  Vet Parasitol       Date:  2009-08-03       Impact factor: 2.738

8.  High Prevalence of Covert Infection With Gastrointestinal Helminths in Cats.

Authors:  Susan Little; Chris Adolph; Kathryn Downie; Tim Snider; Mason Reichard
Journal:  J Am Anim Hosp Assoc       Date:  2015 Nov-Dec       Impact factor: 1.023

9.  Parasite prevalence in fecal samples from shelter dogs and cats across the Canadian provinces.

Authors:  Alain Villeneuve; Lydden Polley; Emily Jenkins; Janna Schurer; John Gilleard; Susan Kutz; Gary Conboy; Donald Benoit; Wolfgang Seewald; France Gagné
Journal:  Parasit Vectors       Date:  2015-05-21       Impact factor: 3.876

10.  Egg genotyping reveals the possibility of patent Ancylostoma caninum infection in human intestine.

Authors:  Luis Fernando Viana Furtado; Lucas Teixeira de Oliveira Dias; Thais de Oliveira Rodrigues; Vivian Jordania da Silva; Valéria Nayara Gomes Mendes de Oliveira; Élida Mara Leite Rabelo
Journal:  Sci Rep       Date:  2020-02-20       Impact factor: 4.379

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  2 in total

1.  Affordable artificial intelligence-based digital pathology for neglected tropical diseases: A proof-of-concept for the detection of soil-transmitted helminths and Schistosoma mansoni eggs in Kato-Katz stool thick smears.

Authors:  Peter Ward; Peter Dahlberg; Ole Lagatie; Joel Larsson; August Tynong; Johnny Vlaminck; Matthias Zumpe; Shaali Ame; Mio Ayana; Virak Khieu; Zeleke Mekonnen; Maurice Odiere; Tsegaye Yohannes; Sofie Van Hoecke; Bruno Levecke; Lieven J Stuyver
Journal:  PLoS Negl Trop Dis       Date:  2022-06-17

Review 2.  Worms and bugs of the gut: the search for diagnostic signatures using barcoding, and metagenomics-metabolomics.

Authors:  Marina Papaiakovou; D Timothy J Littlewood; Stephen R Doyle; Robin B Gasser; Cinzia Cantacessi
Journal:  Parasit Vectors       Date:  2022-04-01       Impact factor: 3.876

  2 in total

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