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Multicenter evaluation of the Vetscan Imagyst system using Ocus 40 and EasyScan One scanners to detect gastrointestinal parasites in feces of dogs and cats.
Nagamori, Yoko; Scimeca, Ruth; Hall-Sedlak, Ruth; Blagburn, Byron; Starkey, Lindsay A; Bowman, Dwight D; Lucio-Forster, Araceli; Little, Susan E; Cree, Travis; Loenser, Michael; Larson, Benjamin S; Penn, Cory; Rhodes, Austin; Goldstein, Richard.
Afiliación
  • Nagamori Y; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Scimeca R; Oklahoma Animal Disease Diagnostic Laboratory, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA.
  • Hall-Sedlak R; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Blagburn B; Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA.
  • Starkey LA; Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA.
  • Bowman DD; Department of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
  • Lucio-Forster A; Department of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
  • Little SE; Department of Veterinary Pathobiology, College of Veterinary Medicine, Oklahoma State University, Stillwater, OK, USA.
  • Cree T; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Loenser M; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Larson BS; Techcyte, Lindon, UT, USA.
  • Penn C; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Rhodes A; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
  • Goldstein R; Zoetis, Global Diagnostics, Parsippany, NJ, USA.
J Vet Diagn Invest ; 36(1): 32-40, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38014739
The Vetscan Imagyst system (Zoetis) is a novel, artificial intelligence-driven detection tool that can assist veterinarians in the identification of enteric parasites in dogs and cats. This system consists of a sample preparation device, an automated digital microscope scanner, and a deep-learning algorithm. The EasyScan One scanner (Motic) has had good diagnostic performance compared with manual examinations by experts; however, there are drawbacks when used in veterinary practices in which space for equipment is often limited. To improve the usability of this system, we evaluated an additional scanner, the Ocus 40 (Grundium). Our objectives were to 1) qualitatively evaluate the performance of the Vetscan Imagyst system with the Ocus 40 scanner for identifying Ancylostoma, Toxocara, and Trichuris eggs, Cystoisospora oocysts, and Giardia cysts in canine and feline fecal samples, and 2) expand the assessment of the performance of the Vetscan Imagyst system paired with either the Ocus 40 or EasyScan One scanner to include a larger dataset of 2,191 fecal samples obtained from 4 geographic regions of the United States. When tested with 852 canine and feline fecal samples collected from different geographic regions, the performance of the Vetscan Imagyst system combined with the Ocus 40 scanner was correlated closely with manual evaluations by experts. Sensitivities were 80.0‒97.0% and specificities were 93.7‒100.0% across the targeted parasites. When tested with 1,339 fecal samples, the Vetscan Imagyst system paired with the EasyScan One scanner successfully identified the targeted parasite stages; sensitivities were 73.6‒96.4% and specificities were 79.7‒100.0%.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Parásitos / Enfermedades de los Gatos / Enfermedades de los Perros / Parasitosis Intestinales Límite: Animals Idioma: En Revista: J Vet Diagn Invest Asunto de la revista: MEDICINA VETERINARIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Parásitos / Enfermedades de los Gatos / Enfermedades de los Perros / Parasitosis Intestinales Límite: Animals Idioma: En Revista: J Vet Diagn Invest Asunto de la revista: MEDICINA VETERINARIA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos