Accuracy in the digital workflow: From data acquisition to the digitally milled cast

The accuracy of digital impressions and the milling of implant crowns greatly influence the clinical outcome of implant restorations.

The purpose of this in vitro study was to calculate the propagation of error in the process of milling an implant crown.

Thirty digitally milled casts made directly from a reference model were prepared. The casts were scanned with a laboratory scanner, and 30 standard tesselation language (STL) datasets from each group were imported to inspection software. In each analysis, STL datasets were aligned by a repeated best fit algorithm, and 18 specified contact locations of interest were measured in mean volumetric deviations. The master reference dataset was aligned 30 times to the master reference dataset to determine the software variation. The reference datasets were aligned to the master reference dataset to determine the scanner variation. The milled cast datasets were aligned to the master reference dataset to determine the milling variation. The 18 specified contact locations of interest were pooled by cusps, occlusal ridge/fossae, interproximal contacts, facial/lingual aspect, and implant position. The pooled areas were statistically analyzed by comparing each group with the reference model to investigate the mean volumetric deviations accounting for accuracy and standard deviations for precision.

Software and scanner variation were negligible. Variations in the milled models resulting from software and scanner error exhibited statistical significance (P<.001). Software, scanner, and milling error were shown to propagate through the digital workflow to the milled model.

The pooled locations may describe the reliability of the milling process as it applies to specific anatomic locations on the tooth.