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ОглавлениеThe digital revolution is impacting nearly every aspect of our daily life. Today, it is nearly impossible to find a person that is not connected to the internet and performing regular tasks using a mobile device. While many advantages exist with this connectivity, there are disadvantages as well. The abbreviation “FOMO,” which stands for “Fear of Missing Out,” was introduced to the Oxford English Dictionary in 2013. Whether it is a problem or not, nonscientific observations report that more than 70% of people are addicted to social media. In fact, every bedroom has today a “connected” mobile phone beside the bed. True also is that for many of us the mobile phone is the first and last thing we see every day. While this practice is not new, however, it did not exist 10 years ago. Further examples about the necessity of the use of smart phones include, but are not limited to, access to information via search engines, mobile banking, home and office control, access to database reservation systems, entertainment, and so on. Such examples clearly show how digital revolution has been aggressively emerging and impacting every aspect of our daily life.
Similar to these aspects I have just mentioned, the medical field is also being impacted by digital technology. While diagnostic means and treatment concepts are being continuously refined, the emergence of new technologies is driving the implementation of new concepts with the goal of improving patient care and offers the new generation of physicians and scientists better learning and development opportunities. A good example is the use of artificial intelligence (AI) in medicine. This has been pushed after realizing the significance of analyzing extremely large databases, termed “Big Data,” computationally to reveal patterns, trends, and associations, especially relating to human behavior, interaction, and disease progression. While many companies and start-ups are focusing on developing products and software that utilize AI in medicine, Watson Health (Microsoft, Redmond, WA, USA) is considered the first and most advanced AI-based system used for helping healthcare. It enables professionals to share health data and deliver insight to further care through hospitals, providers, insurers, researchers, and patients. The developer states that it is humanly impossible today to keep up with the daily proliferation of healthcare data. As an example, healthcare data is projected to be greater than 2,310 exabytes by 2020. A one-week stay in a hospital can equal hundreds of pages in electronic health records. The global economic impact of chronic disease by 2030 is estimated to be 47 trillion USD. Comparatively, only 10% of the drugs currently in development make it to the market (source: IBM Watson Health). All of these facts have driven the need to create a connected ecosystem across the healthcare industry to harness expertise from this information and determine shared value with the goal to advance health and human services. Of course, IBM Watson is not alone – there are currently thousands of companies and start-ups focusing on AI in healthcare.
According to the Merriam-Webster dictionary, seven definitions of the word digital are listed. The first is “of or relating to the fingers or toes,” while the second is “done with a finger,” both of which apply to dentistry at large. Another definition is “composed of data in the form of especially binary digits/digital images/photos/a digital readout/a digital broadcast.” Wikipedia, the free encyclopedia, refers to digital dentistry as “the use of dental technologies or devices to carry out dental procedures rather than using mechanical or electrical tools.”
Clearly, the dominance of computer-aided design/computer-aided manufacturing (CAD/CAM) and its applications is rather evident in the field of digital dental medicine. This may be attributed to the large contribution of the industry in research and development (R&D) over the past half century and its commercial ramifications. Having said that, the digital dental world is not and should not be considered solely for its restorative dental applications. To start at the very beginning: dental education departments in many academic institutions the world over are implementing digital aspects in their curricula while training young dentists.
This includes the application of digital in basic sciences (e.g., simulations in anatomy, physiology, and pathology) or clinical sciences (e.g., virtual and haptic training of tooth preparation or dental shade matching). Also, most diagnostic sciences in dentistry such as radiology rely almost exclusively nowadays on digital media. The days of chemical processing of X-ray films and the lack of consistency of the development of such images are gone. Along with the introduction of digital technologies (e.g., computers, laptops, tablets, scanners, and a wide spectrum of software applications) this has dramatically changed the practice of dentistry. Today, a vast array of digital technologies is already being used in daily practice. Such tools range from patient data management and organization software for patient data acquisition (medical and dental history, extraoral findings, intraoral and dental findings, periodontal findings, functional findings, and/or radiographic findings) to diagnosis, treatment planning, and treatment execution. Consequently, it is rather evident that digital and dentistry have virtually become synonyms and are inseparable.
This chapter will serve as a brief introduction to the components of digital dentistry and areas of implementation.
The digital workflow in reconstructive dentistry has been described by Att and Gerard (2014)1 as comprised of three main components; starting with data acquisition, followed by data processing and planning, and finally with the execution of treatment or fabrication (Fig 1.1).
Fig 1.1 Overview of the digital workflow in reconstructive dentistry.1
For the first component “data acquisition,” there are many technologies available. The goal is to transform the patient’s information into digital data that can be used for further steps, such as analysis, treatment planning, and processing/planning. Some of the acquisition techniques available encompass digital charting, intraoral or desktop scanners, digital radiography, digital photography, video recordings, and so on. As an example, digital photography is considered an important acquisition tool. It is widely used today for documentation and communication purposes. Together with the appropriate software and online or cloud-based communication platforms, the photos can be used as a part of comprehensive treatment and esthetic analysis and, at the same time, as an important communication tool among the dentist, the dental lab, and the patient.
In cases of smile enhancement, for example, providing photos and videos of different stages of the rehabilitation (try-ins, mock-ups, and so on) helps the dental laboratory technician to optimize the esthetic reconstruction, thus reducing the in-office patient treatment time during try-in. On the other hand, the use of intraoral scanners to perform computer-assisted impressions is considered today as a predictable and a fast tool for the purpose of digitizing and manufacturing small-unit reconstructions.
The next step of the workflow encompasses “processing/planning” of the data acquired in order to set a treatment plan or design a restoration. One of the important aspects here is so-called data matching, where data sets obtained from different acquisition tools (e.g., intraoral scan and cone-beam computed tomography (CBCT) or patient photos superimposed onto model scans) can be merged/superimposed together using specific planning software in order to enhance the information for the dentist or lab technician on the computer screen. Most software companies are intensively working on introducing software that can combine more than two different data sets (e.g., surface scans of the intraoral situation, CBCT, face scan, jaw movement data, and so on). The ultimate goal is to create the completely virtual patient. Such a development would push the digital workflow at an even speedier pace and allow for faster adaptation by practitioners, technicians, and teachers. This topic is described elsewhere in this book.
For clarity in “treatment and fabrication,” it is important to mention that CAD/CAM is considered as a component of the digital workflow. Per definition, CAD is the use of a computer to assist in the creation, modification, analysis, or optimization of a design. CAD software is used to improve the productivity of the designer, the quality of the designs, and the communication through documentation as well as to create a database and a three-dimensional file for manufacturing. Once the CAD process is complete, the generated files are transferred to a local or a remote CAM solution. Here, a software and process are required to enable fully automated manufacturing of dental restorations by preparation of the generated CAD files for subtractive or additive manufacturing machines. While CAM has been successfully performed via subtractive techniques, the increased use of additive manufacturing technologies, such as 3D printing, stereolithography, selective laser sintering, and other methods is remarkable. Concepts related to the different components of the digital workflow that are being used on contemporary dental offices are briefly discussed in this chapter. The next chapters of this book provide an in-depth focus onto the different components of the digital workflow.
As already described, data acquisition is the first step of the digital workflow.
While many acquisition technologies exist, the most-used components are patient management systems, including dental charting software and radiography. While dental offices performing patient registration and “conventional” charting by means of paper form are becoming history, many dental offices and dental schools are using the digital approach using different commercially available software for Electronic Protected Health Information (ePHI). With such software, different patient data and information can be obtained and stored for later use.
Typically, medical and dental history as well as comprehensive charting, including radiographic analysis, can be stored. Large-scale clinics and institutions use network-based software that facilitates access of patient data from different working stations. However, concerns remain about patient privacy and data access. For these it is highly recommended to use software that guarantee patient information (i.e., which implement the ePHI). To facilitate this, the software are required to be compliant with the Health Insurance Portability and Accountability Act (HIPPA) in the United States or with the General Data Protection Regulation (GDPR) across the European union.
The goal is to protect all “individually identifiable health information” held or transmitted by a covered entity or its business associates, in any form or media, whether electronic, paper, or oral. “Individually identifiable health information” is information, including demographic data, that relates to (a) the individual’s past, present, or future physical or mental health or condition; (b) the provision of healthcare to the individual; or (c) the past, present, or future payment for the provision of healthcare to the individual; and that identifies the individual or for which there is a reasonable basis to believe it can be used to identify the individual. Individually identifiable health information includes many common identifiers (e.g., name, address, birth date, ID number, social security number, and so on). Further identifiers include, but are not limited to patient facial photographs, annotated/named radiographs, models, intraoral scan data, face scan data, or any other identifiable data. Therefore, it is important for all staff members of any clinic or institution to understand and implement patient privacy standards and guidelines.
Data Processing/Planning and Treatment Planning
While some software incorporate both acquisition and processing/planning capabilities, the majority of developers currently separate them in different software to avoid complexity and introduce clarity into the workflow. Data processing/planning software can be introduced by the same manufacturer of the acquisition device/tool or by another. A good example is the use of acquisition software for an intraoral scanner and CAD from the same device manufacturer (e.g., Sirona or 3Shape). Another possibility is to use processing/planning software that is developed by a different manufacturer than the acquisition software. An example here is the use of CBCT data obtained from a specific manufacturer and imported into implant planning software from a different developer. While this procedure is common, it is important to have the files/data prepared in universal way that the majority of the software can read. Here, the most commonly used universal file formats, among others, are Joint Photographic Experts Group (JPEG), Digital Imaging and Communications In Medicine (DICOM), Standard Tessellation Language (STL), Geometry Definition File Format (OBJ), Tagged Image File Format (TIFF), and Moving Picture Experts Group 4 (MP4). Whenever these files are the output by an acquisition software and can be easily imported and read by the processing/planning software, the workflow is considered as an open system. In the case where the output file is not universal, it must be read by a specific processing/planning software that is typically from the same acquisition device/software developer, so the system is considered to be closed. With some closed systems it is still possible to export the data in a universal format or, in other words, to convert from a closed to an open system. Here, the software developer typically charges fees for this conversion, termed as a click fee.
Typically, the processing/planning software can be used for analysis and diagnostics (e.g., caries and lesion detection), treatment planning (virtual mock-up, virtual implant treatment planning, virtual orthodontics treatment planning, and so on), or CAD. In terms of caries and lesion detection, several companies are working now on introducing AI for automatic detection of caries as well as further pathological lesions from radiographs, namely periapical radiographs, panoramic radiographs, or CBCT. Also, AI is being implemented for automatic annotation of different anatomical structures, such as mandibular nerve, impacted teeth, maxillary sinus, floor of the nose, and others. Likewise, there are undergoing developments to enable automatic detection and segmentation of the teeth from CBCT and creation of separate files (STLs) of the teeth, as well as the bony structures. The implementation of such technologies in the near future will accelerate the workflow and enhance the diagnostic experience for the clinician, thus providing a better healthcare service for the patient.
Data processing/planning software for treatment planning is one of the most important components of the digital workflow. It is not only intended for communication between the patient and the treatment team, but also an important tool for treatment planning and expectations. A good example is implant planning software, where CBCT data (typically DICOM files) is imported into the software and used to plan the implant position virtually with consideration of the anatomical structures as well as the restorative needs. Another application is the use of patient facial photographs in combination with calibrated intraoral scan or model scan data to analyze and plan the future esthetic rehabilitation (e.g., smile design software) in terms of tooth length, width, and proportions, as well as shade, and share the information with the patient as well as the treatment team. While such features facilitate design capabilities, CAD is considered the last component of data processing/planning. Here, the software is used to design the form of the intended object (e.g., crown, prosthesis, surgical guide, night guard, virtual wax-up, and so on) before moving to the last component of the digital workflow.
Execution of Treatment or Fabrication
The last component of the digital workflow is to perform the planned treatment or production of the intended object by means of computer-aided manufacturing (CAM). CAD data is imported into CAM software, where details of the production process can be simulated and executed (e.g., placement of supportive structures or simulation of the milling/grinding process). Both the subtractive and the additive manufacturing technologies are available for CAM.
The subtractive technologies can be subcategorized into milling and grinding. It is considered as the most widely spread manufacturing technology. The manufacturing machines can be divided into chairside or lab units. In the former option, the unit is typically intended for the manufacture of single-unit restorations during the same office visit. For a larger-scale production and more demanding units/restorations, the latter option is selected. The milling machine can be either in an office, a laboratory, or a central manufacturing facility. On the other hand, additive manufacturing is becoming increasingly popular. Here, several methods are available for manufacturing of an object, including but not limited to selective laser sintering (SLS), digital light processing (DLP), stereolithography (SL), and three-dimensional printing (3D printing). The latter technology is considered to be the most up to date and improving day by day. However, the scientific evidence about its accuracy and efficiency is still limited. Comparatively, the other additive manufacturing technologies are well established. For example, SL is considered for a long time as the method of choice for central manufacture of surgical guides or models with a predictable accuracy. Also, SLS is being used to produce nonprecious alloy frameworks of crowns and fixed partial dentures with a predictable accuracy. While many techniques already exist, significantly further technologies and materials for additive manufacturing are expected to be introduced within the next few years. Further details about the different CAM technologies are provided in Chapter 10.
1.Att W, Gerad M. Digital workflow in reconstructive dentistry: new technologies for high-strength ceramics. In: Ferenz J, Navarro J, Silva N (eds). High-Strength Ceramics. Chicago, IL: Quintessence Publishing, 2014.
