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

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.

The EORTC QLQ43 and FACT H&N questionnaires of quality of life at 1 and 5 years after treatment and dental care in head and neck cancer patients: a pilot study.

PURPOSE: This study aimed to examine health-related quality of life (HRQoL) in head and neck cancer patients at 1 and 5 years after successful treatment of their tumors, and to explore the usefulness of 2 instruments for assessing the need of dental care services. METHODS: This cross-sectional pilot study included 20 adult patients with head and neck cancer who completed the Functional Assessment of Cancer Therapy-Head and Neck (FACT H&N) Symptom Index and the European Organization for Research and Treatment of Cancer Quality of Life Head and Neck Module (EORTC QLQ-H&N43) after 1 and 5 years of treatment. RESULTS: Mean (standard deviation, SD) scores of the FACT H&N Symptom Index were higher (better HRQoL) at 5 years than at 1 year (24.1 [4.4] vs. 21.1 [6.4]; p = 0.236). Only three of the ten items of FACT H&N (swallow, pain in mouth/throat or neck, and solid foods) evaluated oral health. In the EORTC QLQ-H&N43 questionnaire, scores were lower at 5 years (better HRQoL) in almost all multi- and single-item symptoms. This questionnaire includes four multi-item scales (pain in the mouth, social eating, swallowing, and problems with teeth) measuring dental and orthodontic needs. CONCLUSION: HRQoL in patients with head and neck cancer improved with the length of follow-up. The EORTC QLQ-H&N43 has more items addressing oral health compared to the FACT H&N Symptom Index and may be more adequate to assess the need of dental therapy in clinical practice.