@article{nokey,

title = {Craniofacial growth percentile curves: A clinical tool from the Craniofacial Growth Consortium Study},

author = {Heesoo Oh and Kevin M. Middleton and Manish Valiathan and Dana L. Duren and Kieran P. McNulty and James A. McNamara Jr. and Mark Hans and Richard J. Sherwood},

doi = {https://doi.org/10.1016/j.ajodo.2025.11.026},

issn = {0889-5406},

year  = {2026},

date = {2026-03-04},

journal = {American Journal of Orthodontics and Dentofacial Orthopedics},

abstract = {This study aimed to develop new cephalometric standards incorporating samples from across North America, focusing on creating sex-specific percentile growth curves for craniofacial cephalometric measures using the extensive longitudinal data from the Craniofacial Growth Consortium Study. This study comprised 2100 subjects (1056 males and 1044 females) with 17,290 lateral cephalometric radiographs, spanning ages of 2.5-31.3 years. Twenty-four linear cephalometric measurements were calculated, including traits from the basicranium, maxilla, and mandible. For each measurement, multilevel nonlinear growth models were used to estimate growth milestones by sex, percentile growth curves were created, and a web-interface tool was developed to facilitate the practical application of these growth curves. Growth milestones, including age at peak growth velocity and peak growth velocity, were estimated for each sex using double logistic growth models. The timing of peak growth velocity varies across different regions of the craniofacial complex. Craniofacial growth percentile curves were created and cross-validated. A web interface tool was created to allow users to retrieve individual-specific percentile scores. The developed percentile growth curves and web-based tool offer a robust framework for clinicians to assess individual growth patterns, identify deviations from normative growth, and estimate future growth potential, supporting more personalized treatment planning and timing. },

keywords = {cephalometrics, clinical tool, craniofacial growth, growth modeling},

pubstate = {published},

tppubtype = {article}

}

@article{Oh2022d,

title = {Craniofacial growth and morphology among intersecting clinical categories},

author = {R Knigge and A Hardin and K Middleton and K McNulty and H Oh and M Valiathan and D Duren and R Sherwood},

url = {https://pubmed.ncbi.nlm.nih.gov/35076186/},

doi = {10.1002/ar.24870},

year  = {2022},

date = {2022-02-11},

journal = {Anatomical Record (Hoboken)},

abstract = {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.},

keywords = {cephalometrics, craniofacial growth, geometric morphometrics, growth modeling, malocclusion},

pubstate = {published},

tppubtype = {article}

}