VETSCAN IMAGYST

VETSCAN IMAGYST detects and classifies fecal parasite eggs from canine and feline samples using automated slide scanning and a cloud-based deep learning algorithm to support standardized diagnostic assessment.

Key Features:

• System components: Comprises a sample preparation device, a commercially available scanner, and analysis software.
• Cloud-based deep learning algorithm: Locates, classifies, and identifies parasite eggs on fecal microscopic slides.
• Sample preparation methods: Includes VETSCAN IMAGYST centrifugal flotation and VETSCAN IMAGYST passive flotation.
• Comparative techniques: Performance was compared to conventional centrifugal flotation and passive flotation using OVASSAY® Plus.
• Evaluation dataset: Assessed using 100 pre-screened fecal samples from dogs and cats.
• Diagnostic performance: Reported sensitivity ranged from 75.8% to 100% and specificity from 91.8% to 100% for the VETSCAN IMAGYST methods.
• Agreement with experts: Qualitative agreement with parasitologists ranged from 93.8% to 94.5%.
• Correlation with parasitologists: Pearson's correlation coefficient (r) ranged from 0.83 to 0.99 across Ancylostoma, Toxocara, Trichuris, and Taeniidae.

Scientific Applications:

• In-clinic parasite detection: Detection and classification of fecal parasites in canines and felines for routine veterinary diagnostics.
• Standardization of fecal examinations: Reduces variability associated with sample preparation and human interpretation.
• Method comparison: Enables comparative assessment of centrifugal and passive flotation sample preparation methods versus conventional techniques.
• Taxon-specific identification: Applied for identifying Ancylostoma, Toxocara, Trichuris, and Taeniidae eggs.
• Qualitative and potential quantitative diagnostics: Provides qualitative screening with potential for quantitative assessment of parasite burden.

Methodology:

A cloud-based deep learning algorithm analyzes scanned fecal microscopic slide images to locate, classify, and identify parasite eggs, and algorithm performance was compared to parasitologists using Pearson's correlation coefficient (r) across Ancylostoma, Toxocara, Trichuris, and Taeniidae.