Research methods to detect hard tissue, soft tissue, and dental changes due to treatment or growth in orthodontics and dentofacial orthopedics have been evolving rapidly with the advancement of digital technologies. The diagnostic tools have also shifted from 2D photos, X-rays, and physical impressions to 3D facial scanning, CBCT, and intra-oral scans. Digital planning and prediction of the treatment outcomes may enhance the accuracy of diagnosis and customize the treatment individually. This warrants the integration of 3D data from different anatomical structures to obtain a 3D virtual simulation of a patient and simulate the treatment outcome into the patient’s face, presenting as a better communication tool with colleagues, technicians, and patients.

Lateral cephalograms have been routinely used in orthodontic practice. However, they present certain limitations, e.g., they are time-consuming for manual cephalometric analysis, not representative of transverse dimension, and missing incidental findings. 3D CBCT, automatic cephalometric analysis, and artificial intelligence are the new trends. Different methods to predict the tooth movement or response to specific clinical situations include but are not limited to digital models or CBCTs superimposition, or finite elements method (FEM).

 In this Methods Collection, our primary goal is to:

1.    Introduce different methods to obtain an orthodontic virtual patient through the superimposition of 3D data.

2.    Provide diagnostic methods using 3D CBCT segmentation and the recent development of 2D images.

3.    Introduce different methods to superimpose digital models and CBCT to measure the tooth movements.

4.    Share details of FEM analysis to predict tooth movements.