Abstract: To investigate the ability of medical infrared imaging to differentiate between normal canine elbows and those with abnormal elbows (elbow dysplasia).
Study design: Prospective cohort study.
Animals: Dogs with normal (n = 15) and abnormal (n = 14) elbows.
Methods: Infrared imaging was performed on all dogs and data analyzed via descriptive statistics and image pattern analysis software. Animals with elbow dysplasia had arthroscopic procedures to confirm the presence of elbow disease.
Results: Computer recognition pattern analysis was up to 100% correct in identifying abnormal elbows and normal elbows, with the medial images most consistent. The caudal, lateral, and cranial images correctly identified 83-100% abnormal elbows. The caudal and lateral images correctly identified 83% normal elbows. A significant difference in temperature was found between normal and abnormal elbows for the cranial full region of interest, lateral images, and each quadrant.
Conclusion: Medical infrared imaging was able to correctly identify known abnormal and known normal elbows in dogs.
Reference: Lauren McGowan , Catherine A Loughin , Dominic J Marino, Scott E Umbaugh , Peng Liu, Maryam Amini, Patrick Solt, Martin L Lesser, Meredith Akerman. (2015) Vet Surg. Oct;44(7):874-82.
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