RESUMO
AIM: The purpose of the current study was to evaluate Titanium and Bioneck TRI implant-abutment interfaces for microgaps and microbiological leakage. MATERIALS AND METHODS: In this in vitro experiment, 40 dental implants were split into two groups, each of which had 20 samples. Group I: Titanium dental implant, group II: Bioneck TRI. E. coli strain was cultivated in MacConkey media for 24 hours at 37°C. To achieve a bacterial concentration of 1 × 108 colony-forming units per mL at 0.5 scale of MacFarland, the brain-heart infusion (BHI) broth was injected. The CFU count was done to evaluate the microbial leakage. The parts were first submerged, carefully cleaned in an ultrasonic bath, and then installed using a digital torque meter with a 20 N/cm preload. These were attached to a stub of approximately 13 mm using carbon tape, and the microgap evaluation was performed using a scanning electron microscope at a magnification of x1000. Unpaired t-test was used for the calculated data's statistical analysis. The p-value less than 0.05 was considered as statistically significant. RESULTS: The maximum microbial leakage was in Bioneck TRI implants (10000 ± 0.01) followed by Titanium dental implants (8.60 ± 3.16). The mean difference was 9991.40 and there was a statistically significant difference found between the two different groups. The maximum microgap was found in the Bioneck TRI implants (9.72 ± 0.96), followed by Titanium dental implant (6.82 ± 1.10) and there was a statistically significant difference was found between the groups (p < 0.001). CONCLUSION: The present study concluded that the microorganisms can infiltrate the microgap between the implant and abutment interface. When compared with Titanium dental implants, Bioneck TRI implants showed significantly higher levels of microbial leakage. CLINICAL SIGNIFICANCE: A microgap between the implant and abutment connection might operate as a bacterial source, may produce inflammation, even osseointegration in danger, and subsequently alter clinical and histological parameters. Therefore, having an understanding of the compatible components aids in overcoming treatment planning challenges.