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      Computer-aided analysis of digital dental impressions obtained from intraoral and extraoral scanners

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          Precision of intraoral digital dental impressions with iTero and extraoral digitization with the iTero and a model scanner.

          Digital impression devices are used alternatively to conventional impression techniques and materials. The aims of this study were to evaluate the precision of digital intraoral scanning under clinical conditions (iTero; Align Technologies, San Jose, Calif) and to compare it with the precision of extraoral digitization.
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            Intraoral Digital Impression Technique: A Review.

            With the techniques of computer-aided design and computer-aided manufacturing (CAD/CAM) being applied in the field of prosthodontics, a concept of intraoral digital impressions was put forward in the early 1980s. It has drawn comprehensive attention from dentists and has been used for dental prosthesis fabrication in a number of cases. This new digital impression technique is expected to bring about absolute digitization to the mode of prosthodontics. A few published articles have indicated that dental prostheses fabricated from intraoral digital impressions have exhibited remarkable advantages over those from conventional impressions in several respects. The present review discusses intraoral digital impression techniques in terms of the following aspects: (1) categories and principles of intraoral digital impression devices currently available; (2) operating characteristics of the devices; and (3) comparison of the manipulation, accuracy, and repeatability between intraoral digital impression and conventional impression.
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              Accuracy of digital models obtained by direct and indirect data capturing.

              With direct and indirect digitalisation, two access points to CAD/CAM-generated restorations are available. The aim of this study was to compare the accuracy of the single steps of both approaches by comparing construction datasets using a new methodology. Twelve test datasets were generated in vitro (1) with the Lava Chairside Oral Scanner (COS) (2) by digitizing polyether impressions (IMP) and (3) by scanning the referring gypsum cast by the Lava Scan ST laboratory scanner (ST) at a time. Using an inspection software, these datasets were superimposed by a best fit algorithm with the reference dataset (REF), gained from industrial computed tomography, and divergences were analysed. On the basis of average positive and negative deviations between test- and REF datasets, it could be shown that direct digitalisation accomplished the most accurate results (COS, 17 μm/-13 μm; SD ± 19 μm), followed by digitized polyether impression (IMP, 23 μm/-22 μm; SD ± 31 μm) and indirect digitalisation (ST, 36 μm/-35 μm; SD ± 52 μm). The mean absolute values of Euclidean distances showed the least values for COS (15 μm; SD ± 6 μm), followed by IMP (23 μm; SD ± 9 μm) and ST (36 μm; SD ± 7 μm). The mean negative and mean absolute values of all groups were significantly different. Comparing the mean positive values of the groups, IMP and COS (p = 0.082) showed no significant difference, whereas ST and COS, and ST and IMP exhibited statistically significant differences. Within the limitations of this in vitro study, the direct digitalisation with Lava C.O.S. showed statistically significantly higher accuracy compared to the conventional procedure of impression taking and indirect digitalisation. Within the limitations of this study, the method of direct digitalisation seems to have the potential to improve the accuracy of impressions for four-unit FDPs.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                The Journal of Prosthetic Dentistry
                The Journal of Prosthetic Dentistry
                Elsevier BV
                00223913
                April 2017
                April 2017
                Article
                10.1016/j.prosdent.2016.11.018
                28385434
                02a15f7b-19f7-4c41-848e-cc432d23573c
                © 2017

                https://www.elsevier.com/tdm/userlicense/1.0/

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