Artificial intelligence in orthodontics: Where are we now? A scoping review

Abstract

Objective This scoping review aims to determine the applications of Artificial Intelligence (AI) that are extensively employed in the field of Orthodontics, to evaluate its benefits, and to discuss its potential implications in this speciality. Recent decades have witnessed enormous changes in our profession. The arrival of new and more aesthetic options in orthodontic treatment, the transition to a fully digital workflow, the emergence of temporary anchorage devices and new imaging methods all provide both patients and professionals with a new focus in orthodontic care. Materials and methods This review was performed following the Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR) guidelines. The electronic literature search was performed through MEDLINE/PubMed, Scopus, Web of Science, Cochrane and IEEE Xplore databases with a 11‐year time restriction: January 2010 till March 2021. No additional manual searches were performed. Results The electronic literature search initially returned 311 records, and 115 after removing duplicate references. Finally, the application of the inclusion criteria resulted in 17 eligible publications in the qualitative synthesis review. Conclusion The analysed studies demonstrated that Convolution Neural Networks can be used for the automatic detection of anatomical reference points on radiological images. In the growth and development research area, the Cervical Vertebral Maturation stage can be determined using an Artificial Neural Network model and obtain the same results as expert human observers. AI technology can also improve the diagnostic accuracy for orthodontic treatments, thereby helping the orthodontist work more accurately and efficiently.

Automatic Classification for Sagittal Craniofacial Patterns Based on Different Convolutional Neural Networks

“…Yoon used cascaded CNNs for landmark detection in cephalometric analyses with a database of 600 samples [ 7 ]. CNNs have been proven to have remarkable potential for assisting in many orthodontic diagnoses processes, and more research should be carried out [ 8 ].…”

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

“…Of all skeletal and soft-tissue structures available for orthodontic diagnostics, the face is among the most important, albeit the most difficult for humans to scientifically comprehend [ 30 ]. Now AI automated facial surface analysis sourcing from CBCT, Lidar from ubiquitous smartphones, or any other face scanner can be utilized for increased diagnostic precision and efficiency [ 44 , 59 , 86 , 87 , 88 ]. Facial growth and aging predictions represent another specialty leaving the human domain as AI algorithms are taking over prediction and planning [ 55 , 89 , 90 ].…”

“…The results of the second objective of this paper, visualized by means of the Venn diagrams in Figure 7 , show that a significant proportion of dental AI utilization is not focused on any particular dental field (17.1%). AI is most often implemented in orthodontics, especially in treatment planning, where automation for CBCT segmentation and 3D cephalometric analysis based on advanced 3D CNN algorithms is used [ 30 , 44 , 55 , 59 , 85 , 86 , 87 , 88 , 89 , 90 ]. It is also possible to predict aging and facial growth by AI prediction and planning.…”

Predicting Interest in Orthodontic Aligners: A Google Trends Data Analysis

“…With growing awareness of the esthetic appearance of the face and teeth, patients are seeking orthodontic treatment to improve their appearance. Modern and more esthetically pleasing options for orthodontic treatment, innovative fully digital workflows, and new imaging methods provide patients and professionals with a new focus in orthodontic care [ 1 ]. Treatment can be accomplished using many types of appliances, including visibly inconspicuous esthetic brackets, lingual appliances, or clear aligners.…”