Clinical implications of age-related change of the mandibular plane angle

Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton

Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to limits of time, prohibitive cost, or health concerns of repeat radiologic imaging. In contrast, cross-sectional samples have few such drawbacks, but it is not known how well estimates of growth milestones can be obtained from cross-sectional samples. The Craniofacial Growth Consortium Study (CGCS) contains longitudinal growth data for approximately 2000 individuals. Single samples from the CGCS for individuals representing cross-sectional data were used to test the ability to predict growth parameters in linear trait measurements separately by sex. Testing across a range of cross-sectional sample sizes from 5 to the full sample, we found that means from repeated samples were able to approximate growth rates determined from the full longitudinal CGCS sample, with mean absolute differences below 1 mm at cross-sectional sample sizes greater than ~ 200 individuals. Our results show that growth parameters and milestones can be accurately estimated from cross-sectional data compared to population-level estimates from complete longitudinal data, underscoring the utility of such datasets in growth modeling. This method can be applied to other forms of growth (e.g., stature) and to cases in which repeated radiographs are not feasible (e.g., cone-beam CT).

Craniofacial growth and morphology among intersecting clinical categories

Differential patterns of craniofacial growth are important sources of variation that can result in skeletal malocclusion. Understanding the timing of growth milestones and morphological change associated with adult skeletal malocclusions is critical for developing individualized orthodontic growth modification strategies. To identify patterns in the timing and geometry of growth, we used Bayesian modeling of cephalometrics and geometric morphometric analyses with a dense, longitudinal sample consisting of 15,407 cephalograms from 1,913 individuals between 2 and 31 years of age. Individuals were classified into vertical facial types (hyper-, normo-, hypo-divergent) and anteroposterior (A-P) skeletal classes (Class I, Class II, Class III) based on adult mandibular plane angle and ANB angle, respectively. These classifications yielded eight facial type-skeletal class categories with sufficient sample sizes to be included in the study. Four linear cephalometrics representing facial heights and maxillary and mandibular lengths were fit to standard double logistic models generating type-class category-specific estimates for age, size, and rate of growth at growth milestones. Mean landmark configurations were compared among type-class categories at four time points between 6 and 20 years of age. Overall, morphology and growth patterns were more similar within vertical facial types than within A-P classes and variation among A-P classes typically nested within variation among vertical types. Further, type-class-associated variation in the rate and magnitude of growth in specific regions identified here may serve as targets for clinical treatment of complex vertical and A-P skeletal malocclusion and provide a clearer picture of the development of variation in craniofacial form.

Orthodontists in forensic facial approximation (FFA): current inter-disciplinary perspective

Forensic odontology has contributed significantly in forensic investigations and involves various branches of dentistry including orthodontics. The current communication presents evidence-based perspective highlighting synergistic union of different specialties for Forensic Facial Approximation (FFA). It brings forth commonality in principles of anthropology, forensic science, anthropometry, anatomy, paleontology, forensic odontology, with orthodontics, used in FFA. Various attributes and skills of orthodontists’ aid in dental and skull profiling and the corresponding sex, age, and ethnicity-based soft tissue assessments for facial soft tissue thickness (FSTT), may aid a life-like appearance. They can assist hard tissue profiling by their expertise in growth of skeletal and soft tissue, along with the evolutionary trends in occlusion, and diet formulations. Their knowledge in identifying teeth patterns, dental/skeletal jaw relationships, cranial/facial indices, vertical/horizontal facial proportions, can help prepare skull for orientation and reconstruction. The dental, photographic, and radiographic records maintained by orthodontists and general dentists are instrumental in data retrieval, used in various software, clinical, or research areas. These can provide normative values for comparative analysis or facial recreation. The orthodontists can also assist anthropologists and forensic specialists in the virtual reconstructions due to their ease in using latest digital technologies including three-dimensional (3D) facial scan, stereo-photogrammetry, 3D printing, automated soft-tissue landmarks, growth, and age predictions. Thus, the current study established the commonality in concepts of various forensic disciplines with orthodontics, which can strengthen both forensic on-field facial approximations and hard/soft tissue research to further enhance the accuracy of contemporary digital software used in FFA.

Geometric morphometric analysis of growth patterns among facial types

Introduction:

Extreme patterns of vertical facial divergence are of great importance to clinicians because of their association with dental malocclusion and functional problems of the orofacial complex. Understanding the growth patterns associated with vertical facial divergence is critical for clinicians to provide optimal treatment. This study evaluates and compares growth patterns from childhood to adulthood among 3 classifications of vertical facial divergence using longitudinal, lateral cephalograms from the Craniofacial Growth Consortium Study.

Methods:

Participants (183 females, 188 males) were classified into 1 of 3 facial types on the basis of their adult mandibular plane angle (MPA): hyperdivergent (MPA >39°; n = 40), normodivergent (28° ≤ MPA ≤ 39°; n = 216), and hypodivergent (MPA <28°; n = 115). Each individual had 5 cephalograms between ages 6 and 20 years. A set of 36 cephalometric landmarks were digitized on each cephalogram. Landmark configurations were superimposed to align 5 homologous landmarks of the anterior cranial base and scaled to unit centroid size. Growth trajectories were calculated using multivariate regression for each facial type and sex combination.

Results:

Divergent growth trajectories were identified among facial types, finding more similarities in normodivergent and hypodivergent growth patterns than either share with the hyperdivergent group. Through the use of geometric morphometric methods, new patterns of facial growth related to vertical facial divergence were identified. Hyperdivergent growth exhibits a downward rotation of the maxillomandibular complex relative to the anterior cranial base, in addition to the increased relative growth of the lower anterior face. Conversely, normodivergent and hypodivergent groups exhibit stable positioning of the maxilla relative to the anterior cranial base, with the forward rotation of the mandible. Furthermore, the hyperdivergent maxilla and mandible become relatively shorter and posteriorly positioned with age compared with the other groups.

Conclusions:

This study demonstrates how hyperdivergent growth, particularly restricted growth and positioning of the maxilla, results in a higher potential risk for Class II malocclusion. Future work will investigate growth patterns within each classification of facial divergence.

Bayesian approach to longitudinal craniofacial growth: The Craniofacial Growth Consortium Study

Early in the 20th century, a series of studies were initiated across North America to investigate and characterize childhood growth. The Craniofacial Growth Consortium Study (CGCS) combines craniofacial records from six of those growth studies (15,407 lateral cephalograms from 1,913 individuals; 956 females, 957 males, primarily European descent). Standard cephalometric points collected from the six studies in the CGCS allows direct comparison of craniofacial growth patterns across six North American locations. Three assessors collected all cephalometric points and the coordinates were averaged for each point. Twelve measures were calculated from the averaged coordinates. We implemented a multilevel double logistic equation to estimate growth trajectories fitting each trait separately by sex. Using Bayesian inference, we fit three models for each trait with different random effects structures to compare differences in growth patterns among studies. The models successfully identified important growth milestones (e.g., age at peak growth velocity, age at cessation of growth) for most traits. In a small number of cases, these milestones could not be determined due to truncated age ranges for some studies and slow, steady growth in some measurements. Results demonstrate great similarity among the six growth studies regarding craniofacial growth milestone estimates and the overall shape of the growth curve. These similarities suggest minor variation among studies resulting from differences in protocol, sample, or possible geographic variation. The analyses presented support combining the studies into the CGCS without substantial concerns of bias. The CGCS, therefore, provides an unparalleled opportunity to examine craniofacial growth from childhood into adulthood.

Estimating peak height velocity in individuals: a comparison of statistical methods

BACKGROUND

Estimates pertaining to the timing of the adolescent growth spurt (e.g. peak height velocity; PHV), including age at peak height velocity (aPHV), play a critical role in the diagnosis, treatment, and management of skeletal growth and/or developmental disorders. Yet, distinct statistical methodologies often result in large estimate discrepancies.

AIM

The aim of the present study was to assess the advantages and disadvantages of three modelling methodologies for height as well as to determine how estimates derived from these methodologies may differ, particularly those that may be useful in paediatric clinical practice.

SUBJECTS AND METHODS

Height data from 686 individuals of the Fels Longitudinal Study were modelled using 5th order polynomials, natural cubic splines, and SuperImposition by Translation and Rotation (SITAR) to determine aPHV and PHV for all individuals together (i.e. population average) by sex and separately for each individual. Estimates within and between methodologies were calculated and compared.

RESULTS

In general, mean aPHV was earlier, and PHV was greater for individuals when compared to estimates from population average models. Significant differences between mean aPHV and PHV for individuals were observed in all three methodologies, with SITAR exhibiting the latest aPHV and largest PHV estimates.

CONCLUSION

Each statistical methodology has a number of advantages when used for specific purposes. For modelling growth in individuals, as one would in paediatric clinical practice, we recommend the use of the 5th order polynomial methodology due to its parameter flexibility.