Paul Slusarewicz, Stefanie Pagano, Christopher Mills, Gabriel Popa, K. Martin Chow, Michael Mendenhall, David W. Rodgers, Martin. K. Nielsen
Intestinal parasites are a concern in veterinary medicine worldwide and for human health in the developing world. Infections are identified by microscopic visualisation of parasite eggs in faeces, which is time-consuming, requires technical expertise and is impractical for use on-site. For these reasons, recommendations for parasite surveillance are not widely adopted and parasite control is based on administration of rote prophylactic treatments with anthelmintic drugs. This approach is known to promote anthelmintic resistance, so there is a pronounced need for a convenient egg counting assay to promote good clinical practice.
J.A. Scare, P. Slusarewicz, M.L. Noel, K.M. Wielgus, M.K. Nielsen
Fecal egg counts are emphasized for guiding equine helminth parasite control regimens due to the rise of an-thelmintic 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 count.
Intestinal worms are among the most common types of parasitic infections worldwide. Despite technological advances in other areas of medical diagnostics, the procedure for identifying worm infection, the faecal egg count, has remained largely unchanged since its debut nearly a century ago. Dr Paul Slusarewicz and the team at MEP Equine Solutions are revolutionising the way veterinarians detect and quantify worm infections using a tool many of us already carry on a daily basis – our smartphone…
Paul Slusarewicz, PhD, adjunct professor at the University of Kentucky Gluck Equine Research Center, and cofounder and chief scientific officer at MEP Equine Solutions LLC, is developing a method to rapidly detect and count the number of parasite eggs in feces. Slusarewicz, who began this work as a visiting scholar at UK, has been collaborating with and working in the lab of Martin Nielsen, DVM, PhD, DEVPC, DACVM, assistant professor in the Department of Veterinary Science at the Gluck Center…
The idea for an easier method of fecal egg counting came in March 2014, and he began work in Nielsen’s lab in June 2014, after Hauck raised
research money from investors. The product takes a fecal sample, treats it with various chemicals that make the eggs glow green when illuminated
with blue light, and then uses an iPhone to photograph and count the parasite eggs. The whole process takes less than five minutes. This
technology can also identify parasite eggs of different parasite classes, such as ascarids and strongyles, in horses.
The Parasight System was developed to be simple and precise and useable both on-site and in any veterinary practice. It is an alternative to the current McMaster and Stoll egg counting methods, which require a lab and lab technician to perform microscopy and manually count each
individual egg with a clicker. The product prototype received an overwhelming response at the American Association of Equine Practitioners Annual Convention…
Megan Slusarewicz, Paul Slusarewicz, Martin K. Nielsen
Fecal egg counts are the primary diagnostic tools of equine parasitology, and use of the McMaster test and its variants in clinical practice is widely recommended. Manual counting is, however, prone to various sources of human error. For example, in real-world situations analysts can be under significant pressure to process high numbers of samples in a limited time. This practice could affect test result quality, and yet no studies have determined whether this is the case. This study’s purpose was to assess the effect of shortened counting duration (from either restricting counting time or counting only one grid of a slide) on McMaster test performance, and to compare the results to those of an automated test whose output is not subject to such limitations