Accelerated Fatigue Model for Predicting Composite Restoration Failure

B. Yang, W. Aregawi, R. Chen, L. Zhang, Y. Wang, A. S.L. Fok

Research output: Contribution to journalArticlepeer-review

Abstract

An empirical method is proposed to predict the clinical performance of resin composite dental restorations by using laboratory data derived from simple specimens subjected to chemical degradation and accelerated cyclic fatigue. Three resin composites were used to fill dentin disks (2-mm inner diameter, 5-mm outer diameter, and 2 mm thick) made from bovine incisor roots. The specimens (n = 30 per group) were aged with different durations of a low-pH challenge (0, 24, and 48 h under pH 4.5) before being subjected to diametral compression with either a monotonically increasing load (fast fracture) or a cyclic load with a continuously increasing amplitude (accelerated fatigue). The data from 1 material were used to establish the relationship between laboratory time (number of cycles) and clinical time to failure (years) via the respective survival probability curves. The temporal relationship was then used to predict the clinical rates of failure for restorations made of the other 2 materials, and the predictions were compared with the clinical data to assess their accuracy. Although there were significant differences in the fast fracture strength among the groups of materials or durations of chemical challenge, fatigue testing was much better at separating the groups. Linear relationships were found between the laboratory and clinical times to failure for the first material (R2 = 0.90, 0.90, and 0.62 for the 0-, 24-, and 48-h low-pH groups, respectively). The clinical life of restorations made of the other 2 materials was best predicted with data from the 48-h low-pH groups. In conclusion, an accelerated fatigue model was successfully calibrated and applied to predict the clinical failure of resin composite restorations, and the predictions based on data obtained from chemically aged specimens provided the best agreement with clinical data.

Original languageEnglish (US)
Pages (from-to)1606-1612
Number of pages7
JournalJournal of dental research
Volume101
Issue number13
DOIs
StatePublished - Dec 2022

Bibliographical note

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this article was supported by the National Institute of Dental and Craniofacial Research of the National Institutes of Health under award R01 DE027034. The authors thank 3M OCSD for providing the materials for testing.

Publisher Copyright:
© International Association for Dental Research and American Association for Dental, Oral, and Craniofacial Research 2022.

Keywords

  • bonding
  • degradation
  • mathematical modeling
  • mechanical properties
  • resin(s)
  • restorative materials

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural

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