Study identifies prevalence estimates of clinically relevant canine thoracic radiographic findings and insights into interobserver variability.
Baumruck R, Tagudar J, Doyle P, Durgempudi P, Cortner CN, Schestopol B, Hossl AK, Coulter C, Ruth JD, Nagy J, De Haan CE, Fields E, Uerling M, Savage M, Szlosek D · American Journal of Veterinary Research · 1 August 2026
Pulmonary abnormalities are the most prevalent canine thoracic radiographic finding; standardized criteria are needed for subjective conditions.
This large-scale observational study estimated the prevalence of 17 clinically relevant thoracic radiographic findings in dogs and quantified interobserver variability among board-certified veterinary radiologists. A random sample of 4,000 lateral thoracic radiographic examinations from IDEXX Telemedicine Consultants' records (May–December 2023) was reviewed, with 2,761 studies ultimately analyzed. Up to 12 radiologists participated, with studies evaluated either in triplicate or quintuplicate, and prevalence was estimated using a latent class expectation-maximization statistical approach. The most prevalent finding was abnormal pulmonary pattern (60.9%), followed by redundant tracheal membrane (29.4%). The least prevalent were heart base mass (0.5%) and esophageal foreign body (0.3%). Interobserver agreement was highest for radiographically distinct, objective conditions—esophageal foreign body, heart base mass, and pneumothorax each achieved an AUC of 1.00. Agreement was lower for subjective or morphologically ambiguous conditions, including suspected tracheal chondromalacia (AUC 0.76) and cranial mediastinal widening as a breed variant or fat deposition (AUC 0.78). These findings confirm that pulmonary abnormalities are the most common thoracic radiographic finding in clinical canine patients. The study provides a robust prevalence framework useful for clinical benchmarking and quality assurance in veterinary radiology. It also highlights specific diagnostic categories where standardized interpretation criteria could meaningfully improve consistency and reduce interobserver variability, particularly for subjectively assessed conditions.
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