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Evaluating the Predictive Potential of Patient-Specific Biomechanical Models in Class III Protraction Therapy.

Joeri Meyns1,2,3, Wout Vertenten4, Sohaib Shujaat2,5

  • 1Department of Oral and Maxillofacial Surgery, General Hospital St-Jan, 3600 Genk, Belgium.

Bioengineering (Basel, Switzerland)
|November 27, 2025
PubMed
Summary

Finite element analysis (FEA) models struggle to predict treatment outcomes in Class III malocclusion. Patient anatomy significantly influences results more than treatment type, indicating a need for models incorporating biological factors.

Keywords:
Class III malocclusionbiomechanical modelingfinite element analysismaxillary protractiontreatment prediction

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Area of Science:

  • Orthodontics
  • Biomedical Engineering
  • Craniofacial Development

Background:

  • Predicting treatment outcomes in Class III protraction therapy is complex.
  • Finite element analysis (FEA) is used for biomechanical studies but lacks validation for patient-specific Class III protraction outcomes.
  • Current FEA applications focus on appliance design over individual patient anatomy.

Purpose of the Study:

  • To validate the predictive accuracy of finite element analysis (FEA) in Class III protraction therapy.
  • To compare FEA predictions with actual clinical outcomes in growing patients.
  • To investigate the influence of patient-specific anatomy versus treatment type on maxillary changes.

Main Methods:

  • Constructed simplified finite element models from CT scans of four Class III malocclusion patients.
  • Compared FEA predictions with one-year treatment outcomes from six additional patients.
  • Analyzed stress patterns and maxillary deformation in relation to facemask or mentoplate treatment.

Main Results:

  • Patient-specific geometrical factors had a greater impact on deformation than treatment type.
  • FEA-predicted maxillary changes were significantly smaller (approx. one-tenth) than actual clinical changes.
  • No significant correlation was found between FEA predictions and actual treatment outcomes.

Conclusions:

  • Current finite element analysis (FEA) models cannot reliably predict clinical outcomes in growing Class III patients.
  • Successful prediction models must integrate biological and growth factors beyond biomechanics.
  • Comprehensive models incorporating multiple biological and developmental factors are necessary for accurate outcome prediction.