• Comparisons of the reliability...

Treffer: Comparisons of the reliability of airway measurements on cone beam computed tomography scans among human raters and a convolutional neural network.

Title:
Comparisons of the reliability of airway measurements on cone beam computed tomography scans among human raters and a convolutional neural network.
Authors:
Dorris S; Department of Oral Pathology, Radiology and Medicine, College of Dentistry, The University of Iowa, Iowa City, IA, USA. Electronic address: steven-dorris@uiowa.edu., Anamali S; Department of Oral Pathology, Radiology and Medicine, College of Dentistry, The University of Iowa, Iowa City, IA, USA., Castro JP; Department of Oral Pathology, Radiology and Medicine, College of Dentistry, The University of Iowa, Iowa City, IA, USA., Dabdoub SM; Division of Biostatistics and Computational Biology, The University of Iowa, Iowa City, IA, USA. Electronic address: shareef-dabdoub@uiowa.edu., Allareddy T; Diagnostic Sciences, Adams School of Dentistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Source:
Oral surgery, oral medicine, oral pathology and oral radiology [Oral Surg Oral Med Oral Pathol Oral Radiol] 2026 Feb; Vol. 141 (2), pp. 255-264. Date of Electronic Publication: 2025 Oct 17.
Publication Type:
Journal Article; Comparative Study
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: United States NLM ID: 101576782 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2212-4411 (Electronic) NLM ISO Abbreviation: Oral Surg Oral Med Oral Pathol Oral Radiol Subsets: MEDLINE
Imprint Name(s):
Original Publication: New York, NY : Elsevier
MeSH Terms:
Cone-Beam Computed Tomography*/methods , Neural Networks, Computer* , Oropharynx*/diagnostic imaging, Humans ; Reproducibility of Results ; Software ; Observer Variation ; Convolutional Neural Networks
Entry Date(s):
Date Created: 20251114 Date Completed: 20260101 Latest Revision: 20260101
Update Code:
20260102
DOI:
10.1016/j.oooo.2025.10.001
PMID:
41238482
Database:
MEDLINE

Weitere Informationen

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.
(Copyright © 2025 Elsevier Inc. All rights reserved.)