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Background: Dental implant surgery has become a widely accepted method for replacing missing teeth. However, the success of dental implant procedures can be influenced by various factors, including the quality of preoperative planning and assessment. Cone beam computed tomography (CBCT) imaging provides valuable insights into a patient's oral anatomy, but accurately predicting implant success remains a challenge. Materials and Methods: In this randomized controlled trial (RCT), a cohort of 150 patients requiring dental implants was randomly divided into two groups: an artificial intelligence (AI)-assisted group and a traditional assessment group. Preoperative CBCT images of all patients were acquired and processed. The AI-assisted group utilized a machine learning model trained on historical data to assess implant success probability based on CBCT images, while the traditional assessment group relied on conventional methods and clinician expertise. Key parameters such as bone density, bone quality, and anatomical features were considered in the AI model. Results: After the completion of the study, the AI-assisted group demonstrated a significantly higher implant success rate, with 92% of implants successfully integrating into the bone compared to 78% in the traditional assessment group. The AI model showed an accuracy of 87% in predicting implant success, whereas traditional assessment methods achieved an accuracy of 71%. Additionally, the AI-assisted group had a lower rate of complications and required fewer postoperative interventions compared to the traditional assessment group. Conclusion: The AI-assisted approach significantly improved implant success rates and reduced complications, underscoring the importance of incorporating AI into the dental implant planning process.
RESUMEN
BACKGROUND: Disinfection of dentin surface prior to any restorative therapy is important for the longevity of the treatment rendered. However, these dentin disinfection methods should itself not interfere with the adhesion of the restorative material. Therefore the aim of this study was to determine the effect of various dentin disinfection protocols on the shear bond strength (SBS) of resin modified glass ionomer cement (RMGIC). MATERIAL AND METHODS: The occlusal surface of 40 extracted premolars were trimmed to obtain a flat dentinal surface and was randomly divided into four groups. CTRL was the control group; NaOCl was 1% sodium hypochlorite disinfection group; CHX was 2% chlorhexidine disinfection group; and PAD was the photo-activated disinfection group. Then a predetermined dimension of RMGIC was bonded to the pre-treated dentin surfaces. Following this, each sample was tested for SBS using universal testing machine at a crosshead speed of 0.5mm/min. RESULTS: Among the test groups, CHX showed the least reduction in SBS and NaOCl the highest reduction in SBS as compared to the control group. PAD on the other hand showed significantly lower SBS than CTRL and CHX groups, but the values were higher than the NaOCl group. CONCLUSIONS: Thus, it could be concluded from the present study that use of chlorhexidine based dentin disinfection does interfere with the adhesion of RMGIC. However, photo-activated disinfection should be done with caution. Moreover, sodium hypochlorite based disinfectants should be avoided prior to the use of RMGIC. Key words:Chlorhexidine, Dentin disinfection, Photo-activated disinfection, Resin modified glass ionomer cement, Shear bond strength, Sodium hypochlorite.
RESUMEN
BACKGROUND: Dentin surface contaminated with haemostatic agents can interfere with the bonding of self-adhesive resin cement. Therefore the purpose of this study was to evaluate the effect of various haemostatic agents such as Aluminium chloride, Ferric sulphate and Tannic acid on the shear bond strength of self-adhesive resin luting agent. MATERIAL AND METHODS: The buccal surfaces of extracted premolars were flattened to expose the dentine. The teeth were then randomly divided into four groups. In Group I Aluminium Chloride was applied on the flattened dentinal surface, in Group II Ferric Sulphate was applied to exposed dentin surface, in Group III tannic acid was applied on to the dentinal surface, and the control group, i.e. Group IV was rinsed with saline. After the surface treatment, all the teeth were air dried. Then a predetermined dimension of RelyX™ U200 self-adhesive resin cement was bonded to the pretreated dentin surfaces. The samples were then stored under 370C in distilled water for 24 hours under 100 % humidity. Following this each sample was tested for shear bond strength with an Instron testing machine at a crosshead speed of 1mm/min. RESULTS: There was significant difference in the shear bond strength of control and tannic acid contaminated group (p<0.05), whereas there was no significant differences between the shear bond strength between control and aluminium chloride and ferric sulphate groups (p>0.05). CONCLUSIONS: The usage of haemostatic agent can negatively affect the bond strength of self-adhesive resin cement (Rely X) on to the dentin surface. As per the study Tannic acid significantly weakened the bond between the self-adhesive resin and dentin. Key words:Aluminium chloride, Ferric sulphate, haemostatic agent, self-adhesive resin cement, shear bond strength, Tannic acid.
