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Veterinary parasitology2017; 247; 85-92; doi: 10.1016/j.vetpar.2017.10.005

Evaluation of accuracy and precision of a smartphone based automated parasite egg counting system in comparison to the McMaster and Mini-FLOTAC methods.

Abstract: Fecal egg counts are emphasized for guiding equine helminth parasite control regimens due to the rise of anthelmintic resistance. This, however, poses further challenges, since egg counting results are prone to issues such as operator dependency, method variability, equipment requirements, and time commitment. The use of image analysis software for performing fecal egg counts is promoted in recent studies to reduce the operator dependency associated with manual counts. In an attempt to remove operator dependency associated with current methods, we developed a diagnostic system that utilizes a smartphone and employs image analysis to generate automated egg counts. The aims of this study were (1) to determine precision of the first smartphone prototype, the modified McMaster and ImageJ; (2) to determine precision, accuracy, sensitivity, and specificity of the second smartphone prototype, the modified McMaster, and Mini-FLOTAC techniques. Repeated counts on fecal samples naturally infected with equine strongyle eggs were performed using each technique to evaluate precision. Triplicate counts on 36 egg count negative samples and 36 samples spiked with strongyle eggs at 5, 50, 500, and 1000 eggs per gram were performed using a second smartphone system prototype, Mini-FLOTAC, and McMaster to determine technique accuracy. Precision across the techniques was evaluated using the coefficient of variation. In regards to the first aim of the study, the McMaster technique performed with significantly less variance than the first smartphone prototype and ImageJ (p<0.0001). The smartphone and ImageJ performed with equal variance. In regards to the second aim of the study, the second smartphone system prototype had significantly better precision than the McMaster (p<0.0001) and Mini-FLOTAC (p<0.0001) methods, and the Mini-FLOTAC was significantly more precise than the McMaster (p=0.0228). Mean accuracies for the Mini-FLOTAC, McMaster, and smartphone system were 64.51%, 21.67%, and 32.53%, respectively. The Mini-FLOTAC was significantly more accurate than the McMaster (p<0.0001) and the smartphone system (p<0.0001), while the smartphone and McMaster counts did not have statistically different accuracies. Overall, the smartphone system compared favorably to manual methods with regards to precision, and reasonably with regards to accuracy. With further refinement, this system could become useful in veterinary practice.
Copyright © 2017 Elsevier B.V. All rights reserved.
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Publication Date: 2017-10-12 PubMed ID: 29080771DOI: 10.1016/j.vetpar.2017.10.005Google Scholar: Lookup
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  • Comparative Study
  • Evaluation Study
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The study explores the use of a smartphone-based system for analyzing fecal egg counts in equine animals, comparing its accuracy and precision to other manual methods like the McMaster and Mini-FLOTAC techniques. The paper discusses results showing the smartphone system presenting satisfactory precision, and reasonable accuracy.

Study Objectives and Methods

This research primarily purposed to:

  • Analyze the precision of the first smartphone prototype and compare it to the modified McMaster and ImageJ techniques.
  • Evaluate the precision, accuracy, sensitivity, and specificity of the second smartphone prototype in comparison to the modified McMaster, and Mini-FLOTAC methods.

The researchers performed multiple counts on fecal samples infected with equine strongyle eggs utilizing each technique to evaluate precision. For checking accuracy, they conducted triplicate counts on 36 egg count negative samples and 36 samples with strongyle eggs at different concentration levels. The coefficient of variation was used to assess precision across the techniques.

Results

In the first objective of the study, the McMaster technique exhibited significantly less variance than both ImageJ and the first smartphone prototype. Secondly, the updated smartphone system prototype demonstrated notably better precision than the McMaster and Mini-FLOTAC methods. However, when it came to accuracy, the Mini-FLOTAC technique significantly outperformed both the smartphone system and the McMaster method. The accuracy of the smartphone and McMaster counts was not statistically different.

Conclusions

The smartphone-based diagnostic system developed for this study compared particularly well to manual counting methods in terms of precision and demonstrated reasonable accuracy. However, it was less accurate than the Mini-FLOTAC method. The researchers suggest that with more refinement, the smartphone system could become a valuable tool in veterinary practice, aiding in the effective control of equine helminth parasites, particularly with the growing challenge of anthelmintic resistance.

Cite This Article

APA
Scare JA, Slusarewicz P, Noel ML, Wielgus KM, Nielsen MK. (2017). Evaluation of accuracy and precision of a smartphone based automated parasite egg counting system in comparison to the McMaster and Mini-FLOTAC methods. Vet Parasitol, 247, 85-92. https://doi.org/10.1016/j.vetpar.2017.10.005

Publication

Veterinary parasitology
ISSN: 1873-2550
NlmUniqueID: 7602745
Country: Netherlands
Language: English
Volume: 247
Pages: 85-92

Researcher Affiliations

Scare, J A
  • M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA. Electronic address: Jessica.scare@uky.edu.
Slusarewicz, P
  • M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA; MEP Equine Solutions, 3905 English Oak Circle, Lexington, KY 40514, USA.
Noel, M L
  • M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA.
Wielgus, K M
  • College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN, USA.
Nielsen, M K
  • M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA.

MeSH Terms

  • Animals
  • Anthelmintics / therapeutic use
  • Automation
  • Feces / parasitology
  • Horse Diseases / parasitology
  • Horses
  • Parasite Egg Count / methods
  • Parasite Egg Count / veterinary
  • Sensitivity and Specificity
  • Smartphone

Citations

This article has been cited 23 times.
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