Date of Award


Document Type


Degree Name

Master of Science in Dentistry


College of Dental Medicine

First Advisor

Zachary Evans

Second Advisor

Michael Cuenin

Third Advisor

Robert Gellin


Objective: To compare different techniques for the digital planning of dental implant placement using commercially available computed aided design software and assess the variability in planned implant position. Materials and methods: Eight dentists individually planned fifteen dental implants using SimPlant software. For each implant, the examiner planned the implant under four different conditions relating to the amount of digital reference data used: (1) no waxed up tooth, (2) pre-op intra-oral scan, (3) pre-op intraoral scan with a virtual tooth created by the examiner, and (4) pre-op intra-oral scan with wax up tooth in occlusion provided by the prosthodontist. . Implant sites included single tooth-bound, adjacent to a single tooth, and “stand alone” as in a distal abutment for an implant bridge. The implant placements were then compared against each other using analysis software in SimPlant. The outcome variables were angular deviation, horizontal placement, and vertical placement. Results: For all measured outcomes in angulation and horizontal distance, “stand alone” planned implants were significantly different from each other (p-value = < 0.05). For vertical distance outcomes, single tooth-bound edentulous site planned implants were significantly different from each other (p-value=0.0057). Conclusion: The variability between digitally planned dental implants is indirectly proportional to the number and proximity of reference points to the surgical site. If there are many fixed reference points available in close proximity to the surgical site, the estimation is likely to be more accurate in angulation and axial position, but not depth (e.g., a one-tooth edentulous site with adjacent teeth on the mesial and distal surfaces). In situations where there are fewer references (sites with multiple missing teeth), the estimation is more challenging and is prone to variability, which appears to be on par with error created between guided and implant surgery.


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