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Related Experiment Video

Updated: Sep 6, 2025

Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
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Multifactorial Analysis of Endodontic Microsurgery Using Finite Element Models.

Raphael Richert1,2, Jean-Christophe Farges1,3, Jean-Christophe Maurin1,3

  • 1Hospices Civils de Lyon, PAM Odontologie, 69007 Lyon, France.

Journal of Personalized Medicine
|June 24, 2022
PubMed
Summary
This summary is machine-generated.

Root preparation and bone height significantly impact root stresses after apicoectomy. Interactions between factors, especially resection and preparation, are crucial for accurate biomechanical analysis.

Keywords:
decision aidendodonticsfinite element analysis

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Area of Science:

  • Biomechanical analysis in endodontic surgery
  • Finite element analysis in dentistry

Background:

  • Assessing biomechanical factors influencing root stresses in resected premolars.
  • Investigating the impact of root-end filling material, apical preparation, root resection length, and bone height.

Purpose of the Study:

  • To classify the relative contributions of key biomechanical factors on root stresses.
  • To quantify mechanical risk in apicoectomy planning.

Main Methods:

  • Utilized a design of experiments approach with 16 finite element models.
  • Analyzed root stresses using the von Mises stress criterion.
  • Evaluated design robustness with nine supplementary models.

Main Results:

  • Root preparation and bone height were identified as high-influence factors on root stresses.
  • Ignoring factor interactions, particularly resection and preparation, led to missing nearly half the biomechanical impact.
  • Interactions between factors significantly affect stress distribution.

Conclusions:

  • Design of experiments is a valuable strategy for analyzing biomechanical factors in endodontics.
  • A statistical method was proposed to quantify mechanical risk during apicoectomy.
  • Integrating this method into future software could support clinical decision-making.