ABSTRACT

Objectives

To develop a facial growth prediction model incorporating individual skeletal and soft tissue characteristics.

Materials and Methods

Serial longitudinal lateral cephalograms were collected from 303 children (166 girls and 137 boys), who had never undergone orthodontic treatment. A growth prediction model was devised by applying the multivariate partial least squares (PLS) algorithm, with 161 predictor variables. Response variables comprised 78 lateral cephalogram landmarks. Multiple linear regression analysis was performed to investigate factors influencing growth prediction errors.

Results

Using the leave-one-out cross-validation method, a PLS model with 30 components was developed. Younger age at prediction resulted in greater prediction error (0.03 mm/y). Further, prediction error increased in proportion to the growth prediction interval (0.24 mm/y). Girls, subjects with Class II malocclusion, growth in the vertical direction, skeletal landmarks, and landmarks on the maxilla were associated with more accurate prediction results than boys, subjects with Class I or III malocclusion, growth in the anteroposterior direction, soft tissue landmarks, and landmarks on the mandible, respectively.

Conclusions

The prediction error of the prediction model was proportional to the remaining growth potential. PLS growth prediction seems to be a versatile approach that can incorporate large numbers of predictor variables to predict numerous landmarks for an individual subject.

ABSTRACT

Objectives

To analyze the accuracy of planned tooth movements of torque, tip, rotations, and transverse width values with lingual straight-wire technique.

Materials and Methods

40 Caucasian subjects with mean age of 23.9 years, consecutively treated in private practice with a lingual straight-wire appliance (STb, Ormco, Glendora, Calif) were evaluated. Maxillary and mandibular dental casts were taken before treatment (T0), in the setup (T1), and at the end of treatment (T2) and scanned with an intraoral 3D scanner Carestream CS 3600 (Carestream Dental, Atlanta, GA). Virtual models at the three time points were superimposed on T1 using 3D software, and the coordinates were exported as a set of x, y, and z values. Angular and linear measurements were analyzed to measure torque, tip, rotation movements, and transverse intra-arch widths. Changes among the three time points were analyzed with Friedman's nonparametric test.

Results

A general increase in torque was recorded in the setup and in the final result, except for the maxillary molars. Torque, tip, and rotation movement mean accuracy was ≥84% for incisors, canines, and premolars. A general increase in transverse width was measured in the setup and in the final models, except for the upper second molars, which showed reduced transverse width during treatment.

Conclusions

The movements planned in the setup to obtain the ideal torque, tip, and rotations actually occurred, except for second molars, which showed less accuracy. Planned expansion of the arches occurred only partially.

ABSTRACT

Objectives

To determine the accuracy of three-dimensional (3D) printed models fabricated from cone-beam computed tomography (CBCT) scans of human mandibular dry skulls in comparison with models derived from intraoral scanner (IOS) data.

Materials and Methods

Six human mandibular dry skulls were scanned by IOS and CBCT. Digital models (DMs) constructed from the IOS and CBCT data were fabricated physically using a 3D printer. The width and thickness of individual teeth and intercanine and molar widths were measured using a digital caliper. The accuracy of the DMs was compared between IOS and CBCT. Paired t-tests were used for intergroup comparisons.

Results

All intraclass correlation coefficient values for the three measurements (mesial-distal, buccal-lingual, width) exceeded 0.9. For the mandibular teeth, there were significant discrepancies in model accuracy between the IOS (average discrepancies of 0.18 ± 0.08 mm and 0.16 ± 0.12 mm for width and thickness, respectively) and CBCT (0.28 ± 0.07 mm for width, 0.37 ± 0.2 mm for thickness; P < .01). Intercanine (P = .38) and molar widths (P = .41) showed no significant difference between groups.

Conclusions

There was a statistically significant difference in the accuracy of DMs obtained from CBCT and IOS; however, this did not seem to result in any important clinical difference. CBCT could be routinely used as an orthodontic diagnostic tool and for appliance construction.

This listing of academic opportunities is provided as a free service to the profession and the community.

MASSACHUSETTS

Boston University Henry M. Goldman School of Dental Medicine

Department of Orthodontics & Dentofacial Orthopedics

635 Albany Street, Suite 754

Boston, MA 02118

Email applications to: willa@bu.edu

Rank: Clinical Assistant/Clinical Associate Professor

Requirements: DMD/DDS degree or equivalent. Certificate of training in Orthodontics & Dentofacial Orthopedics from an accredited postodoctoral program. 1–3 years teaching experience in academic setting. Eligibility for licensure in the Commonwealth of MA.

Must submit: CV, letter of interest, statement of career goals and academic interest, and leadership goals,

Validation of an AI-aided 3D method for enhanced volumetric quantification of external root resorption in orthodontics

Teresa Baena-de la Iglesia,

Estrella Navarro-Fraile, and

Alejandro Iglesias-Linares