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Comparisons of the reliability of airway measurements on cone beam computed tomography scans among human raters and a
Steven Dorris1, Sindhura Anamali1, Juan P Castro1
1Department of Oral Pathology, Radiology and Medicine, College of Dentistry, The University of Iowa, Iowa City, IA, USA.
Objective:
To evaluate the performance of commercially available AI tools in airway evaluation in clinical conditions.
Study Design:
100 anonymized cone beam computed tomography datasets obtained from the records of the University of Iowa were oriented and analyzed by 2 calibrated oral and maxillofacial radiology residents using InVivo software (InVivo6). Measurements made were total airway volume and minimum cross-sectional surface area of the airway. These measurements were then compared to those produced by uploading the same datasets to Diagnocat AI software (Diagnocat).
Results:
The results indicate that all comparisons showed good to excellent reliability (ICC > 0.75), suggesting high agreement between raters. Specifically: The intraclass correlation coefficients of 0.954 (CI: 0.757-0.983) and .944 (CI: 0.732-0.978) between the human and Diagnocat measurements indicate excellent reliability.
Conclusion:
Diagnocat (Diagnocat) artificial intelligence software is capable of analyzing patients' oropharyngeal airway volume and minimum cross-sectional area in cone beam computed tomography datasets with minimal to moderate motion artifact at a level comparable to qualified human practitioners.
