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.
Publication Date: 2017-10-12 PubMed ID: 29080771DOI: 10.1016/j.vetpar.2017.10.005Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- 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
Researcher Affiliations
- M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA. Electronic address: Jessica.scare@uky.edu.
- 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.
- M.H. Gluck Equine Research Center, Department of Veterinary Science, University of Kentucky, Lexington, KY, USA.
- College of Veterinary Medicine, Lincoln Memorial University, Harrogate, TN, USA.
- 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.- González-Garduño R, Higuera-Piedrahita RI, Cuéllar-Ordaz JA, Villa-Mancera A, Mendoza-de Gives P, Torres-Acosta JF. Systematic review of the prevalence of Gastrointestinal helminths in ruminants in Mexico. Vet Res Commun 2025 Nov 15;50(1):33.
- Beasley A, Abbas G, Hughes K, El-Hage C, Jacobson C, Bauquier J, Wilkes E, Carrigan P, Cudmore L, Hurley J, Beveridge I, Nielsen M, Jabbar A. Australian guidelines for equine internal parasite management. Aust Vet J 2025 Apr;103(4):151-158.
- Kruth PS, Whale J, Léveillé AN, Brisbin J, Barta JR. Development of a molecular assay for the determination of Eimeria tenella oocyst viability. Parasitol Res 2024 Dec 28;123(12):422.
- Steuer A, Fritzler J, Boggan S, Daniel I, Cowles B, Penn C, Goldstein R, Lin D. Validation of Vetscan Imagyst(®), a diagnostic test utilizing an artificial intelligence deep learning algorithm, for detecting strongyles and Parascaris spp. in equine fecal samples. Parasit Vectors 2024 Nov 12;17(1):465.
- Capuozzo S, Marrone S, Gravina M, Cringoli G, Rinaldi L, Maurelli MP, Bosco A, Orrù G, Marcialis GL, Ghiani L, Bini S, Saggese A, Vento M, Sansone C. Automating parasite egg detection: insights from the first AI-KFM challenge. Front Artif Intell 2024;7:1325219.
- Castle TG, Britton L, Ripley B, Ubelhor E, Slusarewicz P. Evaluation of Parasight All-in-One system for the automated enumeration of helminth ova in canine and feline feces. Parasit Vectors 2024 Jun 27;17(1):275.
- Britton L, Ripley B, Slusarewicz P. Relative egg extraction efficiencies of manual and automated fecal egg count methods in equines. Helminthologia 2024 Mar;61(1):20-29.
- Nagamori Y, Scimeca R, Hall-Sedlak R, Blagburn B, Starkey LA, Bowman DD, Lucio-Forster A, Little SE, Cree T, Loenser M, Larson BS, Penn C, Rhodes A, Goldstein R. Multicenter evaluation of the Vetscan Imagyst system using Ocus 40 and EasyScan One scanners to detect gastrointestinal parasites in feces of dogs and cats. J Vet Diagn Invest 2024 Jan;36(1):32-40.
- Boelow H, Krücken J, Thomas E, Mirams G, von Samson-Himmelstjerna G. Comparison of FECPAK(G2), a modified Mini-FLOTAC technique and combined sedimentation and flotation for the coproscopic examination of helminth eggs in horses. Parasit Vectors 2022 May 12;15(1):166.
- Ghafar A, Abbas G, King J, Jacobson C, Hughes KJ, El-Hage C, Beasley A, Bauquier J, Wilkes EJA, Hurley J, Cudmore L, Carrigan P, Tennent-Brown B, Nielsen MK, Gauci CG, Beveridge I, Jabbar A. Comparative studies on faecal egg counting techniques used for the detection of gastrointestinal parasites of equines: A systematic review. Curr Res Parasitol Vector Borne Dis 2021;1:100046.
- Steuer AE, Anderson HP, Shepherd T, Clark M, Scare JA, Gravatte HS, Nielsen MK. Parasite dynamics in untreated horses through one calendar year. Parasit Vectors 2022 Feb 8;15(1):50.
- Bogdan G, Struți DI, Sima NF, Păpuc TA, Mihaela BA. A Comprehensive Method for the Evaluation of Hermetia illucens Egg Quality Parameters: Implications and Influence Factors. Insects 2021 Dec 23;13(1).
- Inácio SV, Gomes JF, Falcão AX, Martins Dos Santos B, Soares FA, Nery Loiola SH, Rosa SL, Nagase Suzuki CT, Bresciani KDS. Automated Diagnostics: Advances in the Diagnosis of Intestinal Parasitic Infections in Humans and Animals. Front Vet Sci 2021;8:715406.
- Ngwili N, Thomas L, Githigia S, Muloi D, Marshall K, Wahome R, Roesel K. Co-infection of pigs with Taenia solium cysticercosis and gastrointestinal parasites in Eastern and Western Uganda. Parasitol Res 2022 Jan;121(1):177-189.
- Lobos-Ovalle D, Navarrete C, Navedo JG, Peña-Espinoza M, Verdugo C. Improving the sensitivity of gastrointestinal helminth detection using the Mini-FLOTAC technique in wild birds. Parasitol Res 2021 Sep;120(9):3319-3324.
- Nagamori Y, Sedlak RH, DeRosa A, Pullins A, Cree T, Loenser M, Larson BS, Smith RB, Penn C, Goldstein R. Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm. Parasit Vectors 2021 Jan 29;14(1):89.
- Cringoli G, Amadesi A, Maurelli MP, Celano B, Piantadosi G, Bosco A, Ciuca L, Cesarelli M, Bifulco P, Montresor A, Rinaldi L. The Kubic FLOTAC microscope (KFM): a new compact digital microscope for helminth egg counts. Parasitology 2021 Apr;148(4):427-434.
- Maurelli MP, Dourado Martins OM, Morgan ER, Charlier J, Cringoli G, Mateus TL, Bacescu B, Chartier C, Claerebout E, de Waal T, Helm C, Hertzberg H, Hinney B, Höglund J, Kyriánová IA, Mickiewicz M, Petkevičius S, Simin S, Sotiraki S, Tosheska M, Toth M, Martínez-Valladares M, Varady M, Sekovska B, von Samson-Himmelstjerna G, Rinaldi L. A Qualitative Market Analysis Applied to Mini-FLOTAC and Fill-FLOTAC for Diagnosis of Helminth Infections in Ruminants. Front Vet Sci 2020;7:580649.
- Slusarewicz M, Slusarewicz P, Nielsen MK. The effect of counting duration on quantitative fecal egg count test performance. Vet Parasitol X 2019 Nov;2:100020.
- Nagamori Y, Hall Sedlak R, DeRosa A, Pullins A, Cree T, Loenser M, Larson BS, Smith RB, Goldstein R. Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm. Parasit Vectors 2020 Jul 11;13(1):346.
- Amadesi A, Bosco A, Rinaldi L, Cringoli G, Claerebout E, Maurelli MP. Cattle gastrointestinal nematode egg-spiked faecal samples: high recovery rates using the Mini-FLOTAC technique. Parasit Vectors 2020 May 6;13(1):230.
- Rinaldi L, Amadesi A, Dufourd E, Bosco A, Gadanho M, Lehebel A, Maurelli MP, Chauvin A, Charlier J, Cringoli G, Ravinet N, Chartier C. Rapid assessment of faecal egg count and faecal egg count reduction through composite sampling in cattle. Parasit Vectors 2019 Jul 16;12(1):353.
- Bosco A, Maurelli MP, Ianniello D, Morgoglione ME, Amadesi A, Coles GC, Cringoli G, Rinaldi L. The recovery of added nematode eggs from horse and sheep faeces by three methods. BMC Vet Res 2018 Jan 5;14(1):7.
Use Nutrition Calculator
Check if your horse's diet meets their nutrition requirements with our easy-to-use tool Check your horse's diet with our easy-to-use tool
Talk to a Nutritionist
Discuss your horse's feeding plan with our experts over a free phone consultation Discuss your horse's diet over a phone consultation
Submit Diet Evaluation
Get a customized feeding plan for your horse formulated by our equine nutritionists Get a custom feeding plan formulated by our nutritionists
