8 www.pigchamp.com Spring 2025 Osteochondrosis is a disease that is a major cause of lameness in pigs. Susceptibility to osteochondrosis is partially influenced by genetics, which is why Topigs Norsvin addresses susceptibility to osteochondrosis through the breeding program by scoring osteochondrosis lesions from the high-definition CT (computed tomography) image data. Scores are assigned by trained technicians using a subjective, 5-point scoring system. Research is currently underway to update this process by replacing visual appraisal and scoring with an automated detection, and scoring pipeline with the help of artificial intelligence (AI) models. Genetic Selection for Reduced Susceptibility to Osteochondrosis Topigs Norsvin has selected against susceptibility to osteochondrosis since 2012. Currently, osteochondrosis is scored by trained technicians based on visual observation of CT images. Osteochondrosis is scored for the lateral and medial condyle of both the elbow and knee joints, for a total of eight separate scores. Assigning scores consists of the following steps: 1. Identifying the joint or condyle of interest (from a 3D image); 2. Assessing the severity of the lesion, and 3. Recording a score. Scores are assigned at each individual location using a subjective, 5-point scoring system, then summed across all eight regions to calculate a combined score, ranging from 0 to 32. An individual’s genetic merit for susceptibility to osteochondrosis is estimated based on this combined score. Selection for a lower combined score has proven to be effective, resulting in substantial genetic and phenotypic improvement in this trait. For example, phenotypic trends reveal a 70% reduction in overall osteochondrosis score in the Norsvin Landrace line throughout the last decade (Figure 1). The next steps include improving the phenotyping pipeline by replacing the visual appraisal of osteochondrosis lesions with automated detection and scoring. Segmentation AI plays a significant role in medical image analysis, such as the identification and classification of pixels into different classes. This process, referred to as segmentation, is the same method that Topigs Norsvin uses to classify various tissue types from CT image data. Small Lesions in a Big Pig One of the main challenges of developing artifical intelligence models for osteochondrosis detection is the size of the lesion relative to the full-body image. For instance, a full-body 3D CT image consists of about 0.3 billion pixels, whereas the size of a large osteochondrosis lesion is only about 300 pixels. In general, the smaller the region of interest within an image, the more difficult it is to detect. The best way to overcome this challenge is to focus on specific regions within the pig where osteochondrosis is most likely to occur. OSTEOCHONDROSIS FROM CT IMAGES Towards Automated Detection of A look at the susceptibility of osteochondrosis in swine through genetics. Øyvind Nordbø, PhD, Researcher, Topigs Norsvin Figure 1 Ten-year phenotypic trend for combined osteochondrosis score in the Norsvin Landrace line. Birth-Date Osteochondrosis Score
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