Retrospective Evaluation of Early Dental Implant Failure and Mandibular Bone Quality Using Fractal Analysis
Main Article Content
Abstract
Background: The successful osseointegration process is a prerequisite for the survival of dental implants. Fractal analysis (FA) is a radiographic method that assesses trabecular bone structure and quality and offering insights into the prediction of implant survival. In this retrospective study, we aimed to evaluate early implant failure according to the age, sex, and applied jaw. We also quantified mandibular bone density using FA in patients having both successful and failed
implants.
Methods: 126 systemically healthy, non-smoking patients who received a total of 1026 dental implants (492 maxillary, 534 mandibular) were evaluated. Early implant failures due to lack of osseointegration were recorded. Fractal analysis was performed on a subgroup of 23 patients with both successful and failed mandibular implants. Statistical analysis included Mann–Whitney U-test, Kruskal-Wallis H test, t-tests, and Pearson correlation.
Results: There were no statistically significant differences in early implant failure rates between sexes (P = .101) or among different age groups (P = .426). Fractal analysis results showed that preoperative fractal dimension (FD) values were slightly lower in failed implants compared to successful ones, but the difference was not statistically significant (P = .441). Additionally, age and sex did not significantly correlate with FD values in either successful or failed implants (P > .05).
Conclusion: Early implant failure was not significantly affected by patient age, sex, or jaw location. Although FD values were slightly lower in failed implants, the difference was not statistically significant, suggesting that while FA may reflect bone structural properties, it alone may not predict osseointegration outcomes.
Cite this article as: Öner F, Akkaya G, Özgenç G, Can S, Özkan-Karasu Y. Retrospective evaluation of early dental implant failure and mandibular bone quality using fractal analysis. Essent Dent. 2026, 5, 0076, doi:10.5152/EssentDent.2026.25076.
