Multimodal Surface Characterization of Implant Failure in Peri-Implant Disease: SEM, EDX, and AFM-Based Study
Surface Analysis of Failed Implants in Peri-Implantitis
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Background
Peri-implantitis is a progressive inflammatory disease affecting the tissues surrounding dental implants, often leading to implant failure and compromising oral health and patient wellbeing. Surface characteristics of implants play a critical role in osseointegration, disease prevention, and long-term clinical success. Understanding surface alterations in failed implants can provide valuable insight into disease mechanisms and support the development of improved implant designs and treatment strategies, contributing to better health outcomes and quality of life.
Aim
This study aimed to analyze and compare the surface morphology, elemental composition, and topographical features of failed dental implants retrieved from peri-implantitis patients with those of unused implants using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and atomic force microscopy (AFM).
Methods
Five failed implants were retrieved from patients diagnosed with peri-implantitis and compared with five unused implants. Surface morphology was evaluated using SEM, elemental composition through EDX, and nanoscale surface topography via AFM. Quantitative data were statistically analyzed using an unpaired t-test, with significance set at p < 0.05.
Results
SEM analysis revealed substantial surface degradation and debris accumulation on failed implants, while controls showed intact, well-defined surfaces. EDX spectra indicated increased levels of oxygen, carbon, calcium, and phosphorus on failed implants, suggesting corrosion and contamination. AFM analysis showed significantly higher surface roughness in failed implants across all parameters (p = 0.000).
Conclusion
Failed implants exhibited pronounced morphological damage, elemental contamination, and increased nanoscale roughness, highlighting the role of surface deterioration in peri-implantitis- related failures. These findings underscore the importance of surface optimization for implant longevity.
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