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Delayed Dental Development in Children With Non-Syndromic Hypodontia: A Cross-Sectional Study Using a Machine

Marine Crosnier¹, Pierre-Hadrien Decaup^1,2,3, Frédéric Santos²

¹UFR des Sciences Odontologiques, Univ. De Bordeaux, Bordeaux, France.

Orthodontics & Craniofacial Research

|December 29, 2025

Summary

Hypodontia, or missing teeth, is linked to altered dental development timing. Machine learning accurately estimates dental age in children with missing teeth, aiding orthodontic and forensic applications.

Keywords:

dental age dental developmental stage hypodontia machine learning tooth agenesis tooth agenesis pattern

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Area of Science:

Pediatric Dentistry
Dental Development
Forensic Odontology

Background:

Non-syndromic hypodontia affects tooth development.
Accurate dental age estimation is crucial for clinical and forensic assessments.
Machine learning offers novel approaches for complex developmental analyses.

Purpose of the Study:

To investigate the impact of hypodontia on radiographic dental development.
To estimate dental age in children with bilateral mandibular agenesis using machine learning.
To analyze dental developmental delay in relation to agenesis patterns.

Main Methods:

Retrospective cross-sectional study of 626 children (6-15 years).
Dental age assessed using Demirjian method; machine learning (random forests) for age estimation in agenesis cases.
Dental developmental delay calculated (DA-CA); multiple linear regression used to identify predictors.

Main Results:

Machine learning models achieved high accuracy (R² > 0.95) for dental age prediction.
Children with hypodontia showed a significant delay in dental development (0.77 years) compared to controls.
Agenesis status, sex, and chronological age were significant predictors of dental developmental delay.

Conclusions:

Hypodontia is associated with altered dental developmental timing.
Machine learning provides a robust method for estimating dental age in cases of missing teeth.
This approach has potential applications in orthodontics and forensic science for age estimation.