The development of intra- and extra-oral surface scanners has allowed the implementation of new treatment options for the patient and has provided a paradigm shift in the workflow of surgical and restorative treatments. Advancements in digital impressions combined with computer-aided design/computer-assisted manufacturing (CAD/CAM) have also allowed the development of new dental materials with improved biomechanical properties. Digital impressions have been widely used in applications ranging from fixed/removable prosthodontics to implant dentistry.

Using a digital impression system provides many benefits to clinical practice and patient care. These benefits include (Christensen 2009, Patel 2010): a) improved patient experience during impression taking, b) reduced distortion due to impression and gypsum materials, c) digital recordkeeping, d) three-dimensional pre-visualization of the preparation, e) improved communication between laboratory technicians and practitioners, and f) improved teaching methodology to study tooth anatomy through virtual waxups and evaluate tooth preparations in teaching institutions. Limitations of digital impressions included: a) moisture control, b) capturing the subgingival margin and translucent enamel or a metallic restoration, c) positioning of the wand to capture interproximal contacts or undercuts.

Since the introduction of the first intra-oral digital scanner in the 1980s, numerous companies have developed software technology and introduced intra-oral surface scanners that greatly influenced the fabrication of dental restorations (Birnbaum & Aaronson 2008). Various scanning systems available to consumers implement an integrated digitizing process to achieve adequate three-dimensional (3D) virtual images (Table 1). Depending on the light source and digitizing technology, the intra-oral scanning systems may or may not require a layer of biocompatible titanium dioxide powder to capture the detail of the objects. Resolution also varies between systems, however, no studies have been published to verify its clinical significance. Several studies (Gimenez et al. 2013, Ender & Mehl 2013, Persson et al. 2009) have investigated the accuracy and precision of virtual images obtained from different scanning systems using superimposition and a best-fit algorithm. Their results showed that accuracy and precision varied depending on 1) scanning protocol, 2) scan size (e.g. full or quadrant arch scans), 3) scan location, 4) use of a reflective agent. These factors need to be further evaluated through standardized and randomized clinical studies to investigate their clinical significance.