Leveraging artificial intelligence enhanced immediate implantation utilizing socket shield

Abstract

Immediate implant placement (IIP) with the socket shield technique (SST) offers advantages in preserving bone and soft tissue. However, achieving optimal outcomes relies heavily on precise surgical techniques. This study explores the potential of artificial intelligence (AI) to refine the SST approach for IIP by evaluating the effectiveness of AI-assisted SST compared to the conventional technique. The present study included 46 participants, aged 20 to 45, with non-restorable maxillary anterior tooth and intact socket walls. After Kafrelsheikh University research ethics committee approval, participants were randomized into 2 groups. The control group patients underwent conventional socket shield with conventional IIP, while the study group patients underwent computer guidedIIP combined with artificial intelligence-assisted SST. Then the peri-implant bone defects were filled with bone graft in both groups. Quotient of implant stability (QIS), pink esthetic score (PES), midfacial mucosal level (MFML), labial marginal bone level (LMBL), peri-implant vertical bone defect depth (PVBDD) and peri-implant bone density (PBD) were recorded and assessed at baseline, 6 and 12 months post-operatively. All implants were successful and had no complications during the evaluation period. By the end of the study period after 1-year, the study group demonstrated a significant improvement in regard to QIS, PES, MFML, LMBL, PVBDD and PBD over the control group (P<0.001). By incorporating AI into SST, we envision improved accuracy, predictability, and efficiency in immediate implant placement, ultimately leading to better patient outcomes.