Journal of Prosthodontics News
Novel Method of Identifying Unknown Dental Implants Via 3D Scan Data Matching
Now online in the Journal of Prosthodontics, a report of a method to identify unknown dental implants co-authored by ACP member Webster Kerry Felix, DDS, MA, FAGD, and ACP Fellow, Cheryl J. Park, DDS, FACP.
The global proliferation of dental implant systems (eclipsing 300 manufacturers worldwide), coupled with increasing rates of dental tourism, has created a clinical challenge as patients frequently present with implants of unknown origin, design, and composition. A 2021 survey by Walter et al. revealed that over 79% of clinicians working with dental implants have experienced difficulty with identification of the systems encountered in their practice.
This proof-of-concept study evaluated whether 3D intaglio-surface comparisons of elastomeric impressions can discriminate matching from non-matching implant connection families using root mean square error (RMSE) values in conjunction with receiver operating characteristic (ROC) and area under the curve (AUC) analyses. These statistical tools provide a robust framework for assessing the diagnostic accuracy of the proposed method.
The method described in this report involves using a scannable polyvinylsiloxane material, digitization with a high-precision dental laboratory scanner, and RMSE calculation comparisons using 3D inspection across five known implant groups (Zimvie Certain Internal, NobelParallel, Straumann Bone Level NC, Straumann Bone Level RC, and Straumann BLX TorcFit).
This objective, RMSE based comparison of impression intaglio surfaces discriminated matching from non matching implant connection families and correctly localized an in situ implant to its reference group. This adjunct to radiographic assessment may assist clinicians when prior records are unavailable or radiographic geometry is suboptimal. The ethical implications of this advancement are important, as accurate implant identification directly impacts our ability to provide appropriate maintenance, manage complications, and ensure optimal long-term outcomes for patients.
Felix WK, Park CJ. Novel method of identifying unknown dental implants via 3D scan data matching: Proof-of-concept study. J Prosthodont. 2025; 1–12. https://doi.org/10.1111/jopr.70034
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