ABSTRACT
There is a growing trend of artificial intelligence (AI) applications in veterinary medicine, with the potential to assist veterinarians in clinical decisions. A commercially available, AI-based software program (AISP) for detecting common radiographic dental pathologies in dogs and cats was assessed for agreement with two human evaluators. Furcation bone loss, periapical lucency, resorptive lesion, retained tooth root, attachment (alveolar bone) loss and tooth fracture were assessed. The AISP does not attempt to diagnose or provide treatment recommendations, nor has it been trained to identify other types of radiographic pathology. Inter-rater reliability for detecting pathologies was measured by absolute percent agreement and Gwet's agreement coefficient. There was good to excellent inter-rater reliability among all raters, suggesting the AISP performs similarly at detecting the specified pathologies compared to human evaluators. Sensitivity and specificity for the AISP were assessed using human evaluators as the reference standard. The results revealed a trend of low sensitivity and high specificity, suggesting the AISP may produce a high rate of false negatives and may not be a good tool for initial screening. However, the low rate of false positives produced by the AISP suggests it may be beneficial as a "second set of eyes" because if it detects the specific pathology, there is a high likelihood that the pathology is present. With an understanding of the AISP, as an aid and not a substitute for veterinarians, the technology may increase dental radiography utilization and diagnostic potential.
ABSTRACT
A retrospective study was conducted to determine the outcome of endodontic treatment of incisor teeth in dogs. Medical and dental records from four private veterinary specialty practices over an 8-year period (2013-2021) were reviewed. Forty-five incisor teeth from 41 dogs with ages from 1 to 11-years-old were included in the study. The indications for endodontic treatment were complicated crown fracture in 23 incisors (51.1%), non-vital tooth in 15 incisors (33.3%) and complicated crown-root fracture in seven incisors (15.5%). Evaluation criteria included availability of complete medical and dental records, patient demographics, and at least one follow-up visit as recent as 6 months after the initial root canal therapy. Endodontic treatment outcome was defined as successful, no evidence of failure, or failure. Root canal therapy was successful in 42 teeth (93.3%), no evidence of failure was found in three teeth (6.6%), and none of the cases showed failure of the treatment. Duration of follow-up ranged from 6 to 64 months. Only three variables appeared to have statistical significance: presence of preoperative periapical lucency (PAL) (P = .01), postoperative PAL (P < .001) and postoperative external inflammatory root resorption (P = .014). Based on this study, following "loose criteria" (success and no evidence of failure combined), 100% of the treatments were successful, making this option an excellent therapy choice in a veterinary specialty dentistry practice.
