Novel quantitative parameters for pediatric dental arch morphology in children aged 4–12 years

Abstract Objectives This study aimed to develop novel quantitative parameters for pediatric dental arch morphology, providing a reproducible and interpretable approach for characterizing growth-related morphological patterns in children aged 4–12 years. Materials and methods 3 parameters were derived from digital dental models: Arch Curve Irregularity (ACI) quantified fine-scale alignment deviations based on differences between a spline-fitted occlusal curve and a smooth polynomial reference curve. Arch Shape Deviation (ASD) assessed large-scale arch form by comparison with population-based reference templates. Inter-Arch Shape Discrepancy (IASD) evaluated maxillary–mandibular coordination according to typical inter-arch coupling pattern. These parameters were applied to 473 digital models from children aged 4–12 years, including 274 normal occlusion and 199 malocclusion cases. Results All parameters captured typical patterns of dental arch morphology while revealing substantial inter-individual variability. ACI represented the most frequently observed variation and often appeared in isolation. In contrast, isolated IASD findings were uncommon and were usually accompanied by deviations in arch shape or curvature. Combined parameter analysis revealed distinct configurations of large-scale, fine-scale, and inter-arch morphological variation that are not represented by conventional alignment-based indices. Longitudinal observations further distinguished transient alignment-related irregularities from more persistent morphological differences. Conclusions These novel quantitative parameters provide a reproducible and interpretable approach for assessing pediatric dental arch morphology, capturing combined and persistent deviations from typical baselines. These parameters support longitudinal observation and comparative analyses of growth-related morphological patterns, offering a foundation for future research and potential clinical assessment.