A retrospective study of the prevalence of pulmonary patterns in small animals referred to Shahrekord City: a report based on expert interpretation and artificial intelligence

Document Type : Original Article

Authors
Fatemeh Nasiri Dashtaki 1
Moosa Javdani 2
Amin Mohamadi 3
Mohammad Javad Kouhian Afzal 1
1 DVM Student, Faculty of Veterinary Medicine, Shahrekord University, Shahrekord, Iran
2 Department of Surgery and Radiology, Faculty of Veterinary Medicine, Shahrekord University, Shahrekord, Iran
3 DVM, Faculty of Veterinary Medicine, Islamic Azad University of Shahrekord, Shahrekord, Iran
10.22034/ijvcs.2026.14934.1093
Abstract
Chest radiography, as a non-invasive method, is the basis for the assessment of lung injuries and the diagnosis of respiratory diseases in veterinary medicine. Analysis and interpretation of pulmonary patterns are the basis for the diagnosis of chest diseases and enable veterinarians to differentiate different types of respiratory disorders and implement appropriate therapeutic interventions. According to the classification of Thrall et al., pulmonary patterns are divided into bronchial, alveolar, interstitial, vascular, and mixed. In this study, chest radiographs of small animals referred to a small animal clinic in Shahrekord city over one year (April to the end of March 2024) were used. Of the 112 referred animals, 78 cases (69.64%) showed pulmonary involvement on chest radiographs. The common pattern was the normal pattern, with a prevalence of 59.72% in dogs and 45% in cats. The Chi-square test results showed a significant difference in the frequency of pulmonary patterns between dogs and cats (P = 0.032). Also, the comparison of the results of expert interpretation and artificial intelligence in both species showed a statistically significant difference (dogs: P = 0.018, cats: P = 0.041). Comparing the results from radiologist interpretation and AI interpretation highlights the role of AI as an auxiliary tool, not a replacement.
Keywords
Pulmonary Patterns
Dog
Cat
Artificial Intelligence
Subjects
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Iranian Journal of Veterinary Clinical Sciences
Volume 20, Issue 1 - Serial Number 34
Spring &Summer 2026
September 2026
Pages 69-79