Digital Technologies: From Scientific to Clinical Applications in Orthodontic and Dental Communities

Introduction

The significant progress made in our sector since the introduction of digital technologies has now made it possible to easily obtain all the information necessary to diagnose, design and perform interdisciplinary and complex therapies in a simpler and more reproducible way. This epochal change requires careful training of students and young professionals who approach this new type of dentistry. Therefore, the main message that should arise from the scientific literature addressing this topic is to approach new technological processes with an open mind, while maintaining the theoretical foundations and fundamental principles that our universities have always passed on to new generations of professionals.

Computers help us improve patient treatment in various ways during therapy, enabling patient data to be obtained in ways that are completely different from traditional ones. New and sophisticated tools such as intraoral and facial optical scanners allow us to reconstruct the surface of the patient’s teeth and face in 3D and can be integrated with radiographic scans of craniofacial bone structures (CBCT) [1,2,3,4]. These data are then processed through appropriate CAD (Computer-Aided Design) software that provide the clinician with the appropriate way to integrate and interpret the patient’s relevant data and plan the most appropriate therapies. Today it is possible to integrate more patient data (CBCT, intraoral and/or laboratory optical scan, facial scan) to maximize their diagnostic value and to better perform the virtual planning of orthodontic treatment and implants and prosthetic restorations, for example, the virtual planning of orthodontic miniscrew insertion system for maxillary expansion [5] or the virtual functional and aesthetic analysis for anterior rehabilitation with veneers [6].

Moreover, such integrated anatomical files (intra-oral scan/facial scan/CBCT scan) can be edited to obtain morphological analysis and for comparative pre- and post-treatment assessments. This can be accomplished using specific bio-engineering software that can perform the superimposition of the anatomical digital files and the analysis of the surface distances. The discrepancies between the two surfaces can be represented in a color-coded map as the morphological differences or the changes induced by a specific treatment or can be reported in percentage of agreement, according to the deviation analysis and surface-to-surface matching technique. This technique is also most important from the scientific perspective, since it allows the detection of specific variations or side-effects related to specific treatments, especially for orthodontic or facial orthopedic treatments [5].

The second part of the digital system involves the usage of CAM (Computer-Aided Manufacturing) software, which guide manufacturing techniques such as 3D printing. In this regard, the efficiency and the accuracy of the production of dental manufactures can be significantly improved using dedicated equipment, even with in-office applications of this system [7]. Clinicians and collaborators can now fabricate dental aligners [8,9,10,11], removable devices [12], bonding trays [13], occlusals and splints [14,15], guides for the insertion of miniscrews [4], onlays or veneers [8,16,17,18], etcetera. In general, CAD/CAM procedures allow the following: acquisition, management and storage of data; standardization of data and procedures; the use of 3D communication tools with the laboratory and with the patient; the industrialized manufacturing of prosthetic or orthodontic components; as well as the possibility of processing new biocompatible materials with a reduction in time and costs. The applications in prosthetic reconstructive therapy are diverse, consolidated and well-documented in the literature. To these undoubted advantages we must add the great opportunity to be able to eliminate metals in prosthetic restorations (metal free) with great benefits for the health of patients. Several computer-assisted systems are currently available to optimize and facilitate guided implant surgery, which clearly reduces inaccuracies compared to freehand surgery. Guided implant surgery can be recommended for complex anatomical situations that require minimally invasive surgery for the optimization of implant placement (as in critical aesthetic cases) in the flapless surgical approach. The precision obtained when performing guided implant surgery appears to increase the possibility of providing an ideal final reconstruction. In fact, guided implant placement facilitates the use of temporary CAD/CAM prefabricated items or final restorations, which can be delivered immediately after implant placement. To date, the main application of guided implant surgery is the flapless treatment of the completely edentulous patient through resin templates with internal bushings, reducers, stops and long drills. The various systems on the market allow for the management of these complex cases, with some limits in accuracy reported in the scientific literature, up to the immediate functional load [18,19].

Artificial intelligence (AI) is increasingly becoming an integral part of our daily life. There are many possible applications of AI in the healthcare system, and considering the number of new dental technologies, techniques and materials that are introduced each year, dentistry should easily become one of the first branches of medical science to use AI to conduct routine tasks and functions [20]. Artificial intelligence (AI) is the capacity of a computer to accomplish tasks normally performed by humans. AI, with the use of large amounts of data, including diagnostic results, treatments and results, would be able to measure the effectiveness of the different treatment modalities associated with specific symptoms and anatomical conditions, improve the quality of standardization processes and reduce all the innate prejudices in humans and not present in computers. To date, the main applications for AI in the medical field are those involved in radiology and 3D imaging systems [21,22].

In general, it is essential for clinicians to receive adequate digital education to operate at their best and be able to consciously choose between the increasingly different solutions on the market. Clinicians should not wait too long before adopting or integrating these technologies into their workflow, since they would underestimate their enormous potential for development and dissemination.