Accuracy of AI Assisted Surgical Guide (AISG) (AISG)

Wide research has been conducted to enhance the accuracy of implant placement within the bone while adopting more conservative techniques to improve overall success rates. The digital workflow for computer-aided implant surgery includes a range of steps leading to generation of a prosthetically driven, 3-dimensional virtual plan, and generation of static surgical guide. The use of AI integrated software decreases those steps drastically and seems to be a time saver. This study aims to evaluate and compare the accuracy of conventional static surgical guide and AI-assisted static surgical guide in implant placement in the esthetic zone of partially edentulous maxilla. This clinical study will be conducted on 20 surgical guides, divided equally and randomly via (www.randomizer.org) into 2 groups: Group 1: 10 implants will be placed using 10 conventional surgical guides which are made using traditional manual planning & designing (control group). Group 2: 10 implants will be placed using 10 AI-assisted surgical guides crafted with the help of machine learning-based planning software (study group). AI integrated software performs thorough analysis of the patient's anatomy & a personalized and precise approach of implant placement. By automating the planning process, AI-assisted guides help reduce human error, planning time and provide precise, data-driven recommendations for implant placement position.

Objectives of this study is

Radiographic assessment through:

• pre-operative CBCT & immediate postoperative CBCT to measure and compare angular and linear deviation, and implant depth between planned and actual implant positions in both groups.

• 6 months post operative CBCT for measuring marginal bone level

  • peri implant bone density.

Clinical assessment through:

• Measuring implant stability quotient (ISQ) by Osstell ISQ Scale immediately and 6 months post operative.