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Artificial intelligence in detecting temporomandibular joint osteoarthritis on orthopantomogram

 Eunhye Choi  ;  Donghyun Kim  ;  Jeong-Yun Lee  ;  Hee-Kyung Park 
 SCIENTIFIC REPORTS, Vol.11(1) : 10246, 2021-05 
Journal Title
Issue Date
Adult ; Artificial Intelligence / trends ; Cone-Beam Computed Tomography / methods ; Female ; Humans ; Image Processing, Computer-Assisted / methods* ; Male ; Osteoarthritis / diagnosis ; Osteoarthritis / diagnostic imaging* ; Radiography / methods ; Radiography, Panoramic / methods ; Sensitivity and Specificity ; Temporomandibular Joint / pathology ; Temporomandibular Joint Disorders / diagnosis* ; Temporomandibular Joint Disorders / diagnostic imaging ; Tomography, X-Ray Computed / methods
Orthopantomogram (OPG) is important for primary diagnosis of temporomandibular joint osteoarthritis (TMJOA), because of cost and the radiation associated with computed tomograms (CT). The aims of this study were to develop an artificial intelligence (AI) model and compare its TMJOA diagnostic performance from OPGs with that of an oromaxillofacial radiology (OMFR) expert. An AI model was developed using Karas' ResNet model and trained to classify images into three categories: normal, indeterminate OA, and OA. This study included 1189 OPG images confirmed by cone-beam CT and evaluated the results by model (accuracy, precision, recall, and F1 score) and diagnostic performance (accuracy, sensitivity, and specificity). The model performance was unsatisfying when AI was developed with 3 categories. After the indeterminate OA images were reclassified as normal, OA, or omission, the AI diagnosed TMJOA in a similar manner to an expert and was in most accord with CBCT when the indeterminate OA category was omitted (accuracy: 0.78, sensitivity: 0.73, and specificity: 0.82). Our deep learning model showed a sensitivity equivalent to that of an expert, with a better balance between sensitivity and specificity, which implies that AI can play an important role in primary diagnosis of TMJOA from OPGs in most general practice clinics where OMFR experts or CT are not available.
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Advanced General Dentistry (통합치의학과) > 1. Journal Papers
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