No abstract

: In recent years, good outcomes have been reported using transparent and removable orthodontic appliances known as aligners. However, unpredicted tooth movement that contradicted 3-dimensional image simulations was observed in some cases. These anomalies could relate to biomechanical factors ; in particular, the characteristics of mechanical loading applied to the periodontal ligament and the tooth crown by aligners remain unclear. This study examines the biomechanical characteristics of aligners by a new method as follows : 1 development of an experimental model using artificial teeth and plastic aligners ; 2 finite element FE modeling and analysis using computed tomography CT images of the experimental model ; and, 3 comparison among observations of this actual model and standard FE analysis results. Roots of two arti cial teeth were covered by silicone material at 1.0 mm intervals for each coronal proximal surface and plastic clear aligners were manufactured based on another model in which the interval was reduced to 0.0 mm to simulate bodily movement. An FE analysis model of this 1.0 mm teeth interval was reconstructed from the CT images. A virtual aligner based on the FE model was also generated with a 0.0 mm interval. Changes in space between the root surface and silicone in both the actual and FE model were compared with the aligner tted in the initial model. Identical tendencies of movement were observed in both experimental results -the arti cial teeth and computational results of FE analysis. Our method using an experimental and computational approach proved useful to examine aligner characteristics ; the use of such a biomechanical approach could further our understanding of aligner treatments.

The Invisalign system is widely used to treat mild to moderate tooth crowding. Recently, Invisalign appliances have been used in orthodontic patients with increasingly complex malocclusions. When using an Invisalign appliance to correct severe tooth crowding, root positions must be carefully controlled during extraction space closure. We report our treatment of a 34-year-old man who presented with a Class I relationship, a midline deviation, severe overjet, and severe tooth crowding in the maxillary and mandibular anterior regions. The treatment plan involved extraction of the maxillary and mandibular fi rst premolars on both sides. We treated this patient with severe anterior tooth crowding using an Invisalign appliance combined with a fi xed appliance with power arms and elastics. Treatment by Invisalign as an application of computational calculated result, especially in extraction cases, doctors should have professional skill and experience as an orthodontist.

Objectives: Simulation education close to actual practice is desirable to learn clinical skills and risk management. The usefulness of a patient robot for orthodontic bonding practice was investigated in this study from June 2013 to August 2013. Methods:Nine subjects participated in training using a mannequin and the patient robot, a lecture, and mutual training. The following items were analyzed: A. examiner's score, B. bonding time, C. bracket mounting position, and D. questionnaire results.Results: When training using the patient robot was performed twice on the same day, the examiner's score rose and bonding time decreased. The examiner's score did not decrease after a 14-day interval. In contrast, when training using the patient robot was performed only once followed by a 14-day interval, the examiner's score markedly decreased Bracket heights of 32 and 35 were significantly lower, increasing deviation from the target value, in the training using the patient robot than those when using a mannequin. When performance of the training using the patient robot was compared between before and after the lecture and mutual training, the mean examiner's score in all subjects decreased and the bonding time increased after the lecture and mutual training. No significant difference was noted in the bracket mounting position. Conclusions:The educational effect is markedly influenced by feedback immediately after training and iterative learning. It was clarified that training using the patient robot is more difficult than training using a mannequin. It was suggested that a patient robot is useful in orthodontic bonding practice.