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Automated parasite faecal egg counting using fluorescence labelling, smartphone image capture and computational image
Paul Slusarewicz1, Stefanie Pagano1, Christopher Mills1
1MEP 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.
International Journal for Parasitology
|March 31, 2016
Summary
A new smartphone-based system can detect and count intestinal parasite eggs in feces. This convenient, low-cost method offers an alternative to traditional microscopy for veterinary diagnostics and public health surveillance.
Area of Science:
- Veterinary parasitology
- Biomedical diagnostics
- Mobile health technology
Background:
- Intestinal parasite infections pose global health risks in both veterinary and human medicine.
- Current diagnostic methods rely on time-consuming microscopy, hindering widespread surveillance and promoting anthelmintic resistance due to routine prophylactic treatments.
- There is a critical need for accessible, on-site diagnostic tools for accurate parasite egg counting.
Purpose of the Study:
- To develop and validate a novel, convenient, and automated method for detecting and enumerating parasite eggs in feces.
- To assess the utility of a smartphone as a portable platform for parasite diagnostics.
- To address the limitations of traditional microscopic fecal examination.
Main Methods:
- Utilized a fluorescent chitin-binding protein to detect parasite eggs (strongyle, ascarid, trichurid, coccidian) in feces.
- Employed a smartphone camera for imaging fluorescent eggs and its computational power for automated image analysis and egg counting.
- Compared smartphone-based egg counts with the established McMaster technique for correlation and precision.
Main Results:
- The smartphone system demonstrated a strong linear correlation (R²=0.98) with manual McMaster counts for strongyle eggs.
- The novel method exhibited significantly lower coefficients of variation compared to the McMaster technique, indicating higher precision.
- The system successfully differentiated between equine strongyle and ascarid eggs, comparable to the McMaster method but with superior precision.
Conclusions:
- A simple, automated, on-site test for detecting and enumerating parasite eggs in mammalian feces is feasible using smartphone technology.
- Smartphones offer a viable, inexpensive, and portable platform for sophisticated medical diagnostics, potentially revolutionizing field-based parasite surveillance.
- This technology can promote better clinical practices and combat anthelmintic resistance by enabling accurate, on-demand diagnostics.
