Assessment of The Reproducibility And Precision For Milling And Prototyped Surgical Guides [post]

2019 unpublished
Technological advancements in dentistry in the past decade have led to many innovations and improvements. These advances have led to faster procedures that are more comfortable for the patient and dental surgeon compared to standard methodologies, such as conventional impressions and implant placement surgeries performed without surgical guides or with conventional handmade guides, which generate less predictable results. Use of CAD/CAM technology, both in manufacturing prostheses and in
more » ... l planning, has led to optimization of the procedures and reductions of patient morbidity. Techniques have been developed for the preparation of surgical guides with the goal of optimizing the surgical procedure. Therefore, the aim of the study was to evaluate the reproducibility and precision of two types of surgical guides, obtained by using prototyping and milling methods. Methods: A virtual model was developed, which allowed the virtual design of surgical guide projections that were milled (n = 10) or prototyped (n = 10). Surgical guides were digitally oriented and overlapped on the virtual model that had generated them. In this way, mismatches from the master model were determined. Coefficients of variation, root mean square deviations, and mismatches during an overlap were evaluated. Results: The evaluations showed that the prototyped surgical guides had a higher coefficient of variation than the milled guides. Conclusions: Milling of the guides resulted in smaller misalignments from the master model. Backgrounds Rehabilitating a patient with an implant requires precise planning and special care during surgery. Placing a badly planned implant can cause real problems, such as perforation of According to the results obtained in this study, it is possible to suggest that prototyped surgical guides presented higher coefficient of variation than milled guides. Moreover, milled guides lead to fewer misalignments relative to the master model. Declarations
doi:10.21203/rs.2.14840/v1 fatcat:py3kietsrfeyvgwhqvqjon7xei