Artificial Intelligence in Detecting Temporomandibular Joint Osteoarthritis on Orthopantomogram

Abstract

Orthopantomogram (OPG) is still important in primary diagnosis of temporomandibular joint osteoarthritis (TMJOA), because of cost and radiation of computed tomogram (CT). The aims of this study were to develop an artificial intelligence (AI) model and compare its TMJOA diagnostic performance on OPG 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 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 the expert and was most accordant with CBCT read when the indeterminate OA 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 on OPGs in most general practice clinics where OMFR experts or CT are not available.

Artificial intelligence in positioning between mandibular third molar and inferior alveolar nerve on panoramic radiography

“…Artificial intelligence (AI) models have reported excellent performance, mimicking the precision and accuracy of trained specialists in dentistry 6 . Various studies have applied AI algorithms to read panoramic radiographs for clinical conditions such as age estimation 7 , osteoporosis 8 , 9 , vertical root fracture 10 , automatic teeth detection and numbering 11 , apical lesions 12 , maxillary sinusitis 13 , detecting and segmenting the approximation of the inferior alveolar nerve and mandibular third molar 14 , periodontal bone loss 15 , gender determination 16 , and temporomandibular joint osteoarthritis 17 , 18 . Although some studies evaluate the relationship between M3 and IAN, those studies usually determine whether AI could determine M3 and IAN on panoramic radiograph or CBCT, which was easily discernible in human eyes 4 , 14 , 19 , 20 .…”

Artificial intelligence to support early diagnosis of temporomandibular disorders: A preliminary case study

“…In our big data era, artificial intelligence (AI) and specifically machine learning (ML) techniques, used to extract, combine and understand hidden information, 8 are regarded as ways to improve the diagnostic process of TMDs 9 . In fact, in the last 2 years, ML‐AI techniques, which are extensively used in healthcare, faced an increasing adoption also in dentistry, 9 and more specifically in TMD diagnosis 10–14 …”

“…As ML requires large datasets for appropriate training, the literature mostly reports the use of automated techniques for the interpretation of bioimages, mostly Computerised Tomography (CT) or Magnetic Resonance Imaging scans 10–15 . These are used in TMD diagnosis as quantitative tools to appropriately classify the type of disk displacement, with high accuracy.…”

“…9 In fact, in the last 2 years, ML-AI techniques, which are extensively used in healthcare, faced an increasing adoption also in dentistry, 9 and more specifically in TMD diagnosis. [10][11][12][13][14] As ML requires large datasets for appropriate training, the literature mostly reports the use of automated techniques for the interpretation of bioimages, mostly Computerised Tomography (CT) or Magnetic Resonance Imaging scans. [10][11][12][13][14][15] These are used in TMD diagnosis as quantitative tools to appropriately classify the type of disk displacement, with high accuracy.…”

Application of Artificial Intelligence for the Management of Oral Diseases

“…Additionally, a machine learning approach was used to detect specific strains of Candida albicans [13]. An AIbased diagnosis of temporomandibular joint osteoarthritis has been performed using radiographic images obtained via cone beam computed tomography or panoramic radiography [14,15]. Nonetheless, a comprehensive multicenter study is required to validate these results and expand their application.…”