Using HALO digital image analysis for automated detection of bovine viral diarrhea virus antigen in ear-notch specimens.

Abstract

Detecting calves that are persistently infected with bovine viral diarrhea virus (BVDV) is essential to disease prevention. Immunohistochemistry (IHC) performed on formalin-fixed, paraffin-embedded ear-notch samples is commonly used for surveillance detection of BVDV antigens. However, due to the low percentage of positive samples in most submissions, the current workflow often entails considerable time reviewing negative results. Herein we aimed to utilize digital pathology and whole-slide imaging, coupled with advanced image analysis software, to enhance the efficiency of positive IHC detection in surveillance. Despite some challenges encountered during the implementation phase, the benefits of the reduced potential for human error and significant time savings for technicians and pathologists are evident. The screening of 518 slides, containing 2,884 ear notches, reached 97.4% sensitivity and 89.4% specificity compared to the gold standard of direct human assessment. The time taken for the personnel to operate the software and organize results was significantly shorter than the time needed for technicians and pathologists to manually examine the slides. Future refinements in software integration, staining protocols, and QC measures promise to further optimize this approach.