The Role and Comparison of Imaging Modalities (Ultrasonography, Radiography, and Infrared Thermography) in the Diagnosis and Monitoring of Lameness in Dairy Cows

Background and Study Type: Lameness is one of the most important health and economic problems in dairy cows, associated with reduced animal welfare, decreased milk production, and increased culling rates. This Review Study was conducted with the aim of investigating the role of imaging modalities in the differential diagnosis, treatment monitoring, and prevention of lameness.
Objective: The main objective was to analyze the capabilities and limitations of various imaging modalities, including Radiography (X-ray), Ultrasonography (USG), Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Infrared Thermography (IRT), in identifying bone and soft tissue lesions associated with lameness.
Methods: This article systematically reviewed scientific literature published between 1980 and 2025, collecting and analyzing key findings on the application of imaging in veterinary medicine. The focus was on studies that evaluated diagnostic accuracy, suitability for treatment monitoring, and feasibility for use in farm settings.
Results: Ultrasonography was identified as the most practical and efficient method (Cost–Effectiveness Ratio: 0.85) due to its field-use capability and soft tissue assessment. It demonstrated a sensitivity of 0.97 in diagnosing septic arthritis. Radiography maintained its primary role in diagnosing phalangeal fractures and chronic bone lesions. Infrared Thermography (IRT), as a non-invasive and rapid screening tool, was able to detect inflammation (hoof surface temperature increase up to approximately $34.5^\circ\text{C}$) with a sensitivity of 80% and a specificity of 92.4%. Advanced methods like CT and MRI offered the highest accuracy (95% to 98%) in structural detail of bone and soft tissue but their widespread use is limited to complex and research cases. Furthermore, a significant correlation was found between reduced digital cushion thickness in USG and MRI with a low BCS, and increased bone lesions in radiography with a high Lameness Score (LS).
Conclusion: Integrating multiple imaging modalities can significantly enhance the diagnostic accuracy and prognosis of lameness. The use of novel technologies such as Artificial Intelligence in image analysis promises a bright future for automated and preventive monitoring of dairy cow health.