DIY Orthodontics: Design It Yourself

1

Introduction

Rafi Romano

"D o it yourself" (DIY) orthodontics is becoming requisite in modern orthodontic practice. Nevertheless, this book is titled Design It Yourself Orthodontics in order to differentiate it from the doctorless direct-to-patient appliances offered online or at shopping mall kiosks.

Technology and 3D software have irrevocably changed the way modern orthodontics is managed and administered. Printed models are eliminating poured plaster casts, appliances can be designed and printed with computer-assisted hardware and software, and tooth movements can be simulated and staged digitally to increase their accuracy and predictability.

Digitization converts real-world information into digital data that can be presented on a computer screen. Volume scanning and surface scanning of the dental arches and the face are transferred to dedicated orthodontic software to build the virtual patient for orthodontic diagnosis, tooth movement simulations, and treatment planning.

Artificial intelligence (AI), currently in its initial stages, holds promise in becoming a tool for orthodontic diagnosis and treatment outcome predictions. It also has the potential to assist in defining appropriate treatment options for a specific patient, as well as predicting tendencies of relapse. Furthermore, AI can be a valuable research tool. Blockchain assemblies are described herein that could be a digital tool to connect an infinite number of orthodontic clinicians without a centralized server as a network. This could become a window for participants to view treatment examples, digital appliances, radiographs, etc, without violating patient or doctor privacy.

Dentists and orthodontists can at times be intimidated by mathematics, physics, and technology, which are related to forces and appliance design. Technologic understanding is a time-consuming process with a learning curve that can deter the orthodontist from getting involved. A familiar work pattern and acceptance of a particular appliance serve to create a comfort zone for every clinician. The introduction of a disruptive technology may upset this pattern and disturb the established workflow. Nevertheless, avoidance of these technologies will be to the disadvantage of the practitioner. The longer the delay in integrating these technologies, the greater the learning curve in implementing them. As Darwin stated, it is not the strongest of the species that survives nor the most intelligent—it is the one that is most adaptable to change.

The versatility of digital applications has enabled increased control and greater independence within our clinical settings. This trend has justified the inception of many companies that recognize the need for tools to design and plan individualized appliances according to each clinician’s vision for each case, and to enable modifications as needed during the treatment. These tools include multifunctional orthodontic software for virtual patient analysis, treatment simulation, patient education, treatment planning, and smile design. Other software offers the ability to design and create in-house orthodontic aligners, indirect bonding (IDB) trays, customized bands, appliances, and orthognathic surgical splints, etc. 3D printer companies have recognized the application of their technology in dentistry and orthodontics, and new biocompatible printing resins are continuously under development and being introduced in the market for use.

The younger generations of orthodontists and dentists, while certainly less clinically experienced, are naturally better informed as to these technologies because their emergence into the field parallel one another. Older, more experienced clinicians generally are slow to adopt new technologies due to the apprehension created by the disturbance in established principles and the apparent complexity new technology introduces. Young or old, inexperienced or experienced, all clinicians need sources that enable them to accept new technologies and overcome barriers so they can realize their own innovation.

It needs to be understood that technology is not a replacement for the process of coalescing the appropriate diagnostic information into a patient-specific treatment plan. Digital technology can only serve as an assistant, not the master in orthodontic treatments. Ironically, it is the more clinically experienced category of clinicians that can maximize the potential of these tools; however, their aversion to the changes brought by technology has left this potential unrealized. Also, knowledge of new technology should not give the impression in young dentists and orthodontists that it is sufficient for a satisfactory orthodontic treatment result.

This book, as stated in its title, covers the topic of DIY orthodontics from the simple design of expansion and cast/printed appliances using dedicated computer-aided design (CAD) orthodontic software to unique printed appliances designed by general CAD engineering software. As the reader will notice, such tools enable the orthodontist to directly design appliances that cannot be created with any other software. Indirect bonding with digital preparation is thoroughly described with the add-on of a special IDB process that is undertaken upon digital setup. In-house design of customized lingual braces is presented together with an in-house wire-bending robot, for both lingual and labial archwires.

In-house aligner design is presented using uncomplicated software, an aspiration that is currently central in orthodontics. Furthermore, industry efforts to produce a biocompatible material and technique to directly print clear aligners are discussed in these pages and, together with the applications for AI, are the frontiers in the integration of technology into clinical orthodontics.

One of the most revolutionary chapters of this book describes in-house custom bracket design and printing using a new software called UBrackets. This enables the operator-driven design and building of customized orthodontic bracket bases using composite resin on orthodontic brackets. In addition, as a second software option, the orthodontist can use the software’s bracket library to print fully customized brackets. Volume scanning, surface scanning, 3D printing, and AI are covered in separate chapters. A full overview of the digital office workflow is also covered in detail.

To my knowledge, there is currently no similar compilation of these undeniably important aspects of the modern practice of orthodontics. This does not surprise me because the majority of what is described in this book was not in existence even 5 years ago. The importance of a book such as this is highlighted by the frequency at which new companies and products are popping up on the market, offering new ideas and tools to enable simplification of clinical tasks and broaden our professional lives with new and exciting opportunities.

The authors contained in this book are recognized clinicians and researchers whose reputations and contributions are highly regarded. Each presents their respective topic in a well-written, comprehensive, but very readable manner. All the material appearing in this book is not only topical but also extremely up to date with several items receiving initial exposure in these pages. The text and visual presentations complement each other and engender a flowing and enjoyable reading experience of a cutting-edge group of topics.

The biology of tooth movement and the biomechanics applied to do so are constants within orthodontics. Yet with simple DIY tools, the modern clinician can visualize and simulate treatment, and, most importantly, sustain maximum control of the progress of any given treatment. Furthermore, DIY tools facilitate the ability to modify treatment as and when needed without being limited or dependent on outsourced laboratories and/or commercial companies.

The highly innovative nature of this book is sure to make it standard for every orthodontic office. It will go a long way in helping today’s clinicians immerse themselves in this fascinating era, which will certainly become the new normal in every clinic.

2

CBCT in Orthodontics

Apostolos I. Tsolakis

Christos Angelopoulos

Nearchos C. Panayi

Kostas Tsiklakis

CT and CBCT Historical Perspective

Cone beam computed tomography (CBCT) is undoubtedly the most significant diagnostic imaging advancement in maxillofacial imaging in the last 25 years.1,2 Sir Godfrey N. Hounsfield invented computed tomography (CT) in 1972, for which he received the Nobel Prize in Medicine in 1979; however, the principles of tomosynthesis were described in 1934 and provided the theoretical basis of the integration of multiple planar images.3–6

The first patent application for a maxillofacial CBCT was submitted in Italy in 1995 by Attilio Tacconi and Piero Mozzo. This led to the commercial development of the first available CBCT—NewTom DVT 9000. Presently, more than 60 CBCT brands are available, the majority of which offer multiple options to the practitioner, including hybrid panoramic units to a full maxillofacial unit with or without a cephalometric unit.

Basics of CBCT

CBCT imaging is accomplished by rotating an x-ray source and a detector around the region of interest (ie, the patient; Fig 2-1). Radiation is emitted by the x-ray source passing through the patient in a cone-shaped beam to the x-ray detector on the opposite side, with the range of the arc employed being 180 to 360 degrees. During the exposure, hundreds of sequential planar projection images are acquired. In contrast, the CT machine consists of a fan-shaped x-ray beam with a simultaneous translation of the patient table and rotation of the x-ray source and detector, resulting in a helical trajectory (Fig 2-2).

Fig 2-1 A rotating x-ray source, a flat panel detector, and a conical beam are the key components of the CBCT image acquisition process. The x-ray tube completes a full rotation around the patient’s head, producing multiple exposures.

Fig 2-2 Medical CT image acquisition involves a thin fan-shaped rotating beam, a ringlike array of detectors (yellow ring) , and a supine patient. The x-ray source scans the area of interest with multiple rotations, collecting x-ray attenuation data.

The basic parts of a CBCT are the following7,8:

•An x-ray generator

•An x-ray detector that must be able to capture multiple basic images

•A powerful computer and software able to process all the acquired image data

•Appropriate image acquisition and integration algorithms

In order to transform a series of 2D multiple planar images (which are captured by the 2D x-ray area detector) to a 3D volume image, a cone beam reconstruction image procedure must be performed. In other words, 3D volume reconstruction software turns a series of 2D acquired images into a 3D volume image. The most popular reconstruction scheme for cone beam projections is the FDK (Feldkamp-Davis-Kress). CBCT provides an alternate method of volume scanning, allowing a fast acquisition of data in an in-office mode. CBCT units use an image intensifier or a flat panel detector as the image detector. The larger the detector, the bigger the field of view (FOV), and as a result the better the imaging; however, this increases the cost of the CBCT unit.

An important factor in the quality of the x-ray detector is the pixel size it detects, because this determines radiographic resolution and subsequently the CBCT image quality. A detector with a small pixel size increases the resolution of the acquired image but captures fewer photons, the consequence of which is increased image noise. In order to increase the resolution and decrease the image noise, detectors are usually grouped together and considered as one element; otherwise, the radiation dose has to be increased to achieve the same goal. While the detector captures 2D images consisting of pixels, the 3D volume data output is composed of cubical elements called voxels (Fig 2-3). This transformation, from the 2D image to a 3D volume image, is performed by a sequence of software algorithms. CBCT images are reconstructed from pixels to voxels and presented as gray values depending on the media through which the radiation is passed (air, bone, soft tissue, teeth, etc).

Fig 2-3 The moment a region of interest is determined, this area is split in numerous small fictional cubes from which the detector of the scanner will collect attenuation data; these cubes, known as voxels , are of a known spatial location and are assigned a shade of gray after the data are processed. This composite of voxels forms the 3D volume.

Originally, the use of CT in the maxillofacial area was a rarely used diagnostic tool limited to suspected tumors, fractures, or craniofacial syndromes—not for dental implant placement. The amount of radiation required, together with the unit costs and size, made the early use of this diagnostic tool prοhibitive for dentistry. Resolution of these parameters and what is now almost routine use of CBCT images has facilitated the transition from 2D to 3D imaging in dentistry and maxillofacial imaging, allowing the use of a fast, inexpensive, and reliable imaging tool.

Field of view (FOV)

The FOV in CBCT is the maximum diameter of the scanned object in the horizontal and vertical dimensions that is represented in the reconstructed image. In other words, FOV refers to the anatomical area that will be included in the data volume and the area of the patient that will be irradiated9,10 (Fig 2-4). Although a wide range of FOVs is available, generally, four categories exist:

1. Large FOV: Covers most of the craniofacial skeleton and is more than 15 cm in both dimensions

2. Medium FOV: Covers both jaws and is 8 cm or more in vertical and horizontal dimensions

3. Small FOV: Covers a single jaw and is wide in diameter (about 10 cm or more) but limited in height (4–6 cm)

4. Very small FOV: Covers between 4 and 6 cm in both dimensions

Fig 2-4 There are a variety of available FOVs in modern CBCT machines; these range from very small (40 × 40 mm) to very large to include almost the entire head of the patient (230 × 230 mm).

In most CBCT units, there are options of increasing or decreasing the FOV depending on the specific diagnostic needs and variability in patient anatomy. Furthermore, the quality of the image is also affected by the FOV size. A large FOV increases the amount of scattering per detector area, which in turn reduces the image quality.11 Image quality is also decreased in large FOVs by the higher beam divergence at the edge of the FOV.

Image quality

The quality of the image is dependent on four parameters:

1. Spatial resolution: The ability to distinguish small details in an image. It is a factor that depends on the voxel size, the pixel size, and the fill factor ( Fig 2-5 ).

2. Contrast resolution: The ability to discriminate objects of different density. Compared to medical CT, CBCT cannot reveal with accuracy differences between soft tissues or structures that have similar anatomical contrast. Nevertheless, structures with different density can be visualized very well ( Fig 2-6 ).

3. Image noise: The variability of the projected gray values in a homogenous tissue. There are various causes of this noise in a CBCT. These include the basic nature of random x-ray interactions resulting in a nonuniform signal at the detector, as well as x-ray scatter. Filtering during image reconstruction can improve the resolution of signal detection (ie, separate useful diagnostic information from noise; Fig 2-7).

4. Artifacts: An image artifact is a visualized structure in the 3D volume image that is not present in the object under investigation. In the maxillofacial region, this most frequently occurs due to the presence of a metallic structure (ie, restorations) and can be seen as dark/bright streaks most often in the axial plane. Patient movement during the CBCT scanning will also result in artifacts proportional to the extent of the motion. 11 Ring artifacts can also occur when the detector has not been properly calibrated. Unfortunately, when such a 3D volume image is taken, such unwanted structures are frequently detected; however, they are usually discernible from normal structures and are only problematic if they obscure an area of interest.

Fig 2-5 (a) Coronal section of the maxillary bone (0.3-mm voxel size scan acquisition) vs (b) a coronal section of another scan of the maxilla (0.15-mm voxel size). There is an obvious difference in the image resolution attributed to the smaller voxel size.

Fig 2-6 (a) A CBCT axial section at the level of the maxilla compared to (b) a medical CT axial section at the same level. Note the difference in the soft tissue contrast (much higher in the medical CT scan) because of the higher contrast resolution (many more shades of gray).

Fig 2-7 (a) Coronal CBCT section and (b) a series of sagittal CBCT sections of the left temporomandibular joint (TMJ) in a young patient. Note the diffuse graininess seen in all images; this is attributed to the noise in the scan (ie, the heterogeneous distribution of the x-rays onto the detector).

Scanning time is another variable that can alter image quality. In general, longer scanning times lead to a larger number of base images, higher radiation dose, more data, greater contrast resolution, smoother images, and fewer metallic artifacts. On the other hand, longer scanning times could lead to motion artifacts due to an increased chance of patient movement.12

Exposure parameters

There is the need to adjust the exposure parameters before we proceed to CBCT image acquisition:

•Milliamperage (mA): This determines the number of x-rays emitted by the generator per unit time; it is coupled with the kilovoltage (kV) and exposure time to create an acceptable image. This parameter should be set according to the patient’s size and age. A high mA reduces image noise by increasing the radiation dose, which leads to an increased detector signal.

•Kilovoltage (kV): This proportionately determines the quantity of x-rays produced per unit time. Moreover, it also increases the mean and maximum energy of each x-ray. In general, an increase in kV increases the quantity of x-rays produced while reducing the image noise and beam hardening and improving contrast.

In most CBCT machines, the kV and mA settings are predetermined or fixed; however, there are also units where some level of adjustment is possible. As low as reasonably achievable (ALARA) is a technical concept that should be taken into account in order to decrease the dose of radiation without lowering the image quality. In cases where image quality is not crucial, mA could be reduced without compromising diagnostic quality.13 An appropriate example of decreased radiation is the CBCT imaging for presurgical implant planning or for orthodontic diagnosis.14,15

Image display

From the time that the data from the detectors enters the computer, there are four distinct operations involved16:

1. Reconstruction: The 2D sequential planar imaging data derived by the detector undergo reconstruction to generate a 3D volume dataset.

2. Visualization: The reconstructed images from the CBCT are optimized and finalized to be visualized by rendition techniques.

3. Postprocessing: The operator uses software tools to change the presentation of the image. The tools are usually based on specific image enhancement techniques.

4. Analysis: The image characteristics are assessed to provide the necessary quantitative information from the data.

Almost all CBCT computer visualization software displays images in the standard three planes of section (axial, sagittal, coronal) as well as different reformatted images (panoramic and cross-sectional; Figs 2-8 and 2-9). A multitude of image reconstructions can be performed by reshuffling the volumetric data. Image enhancements can also be performed in order to improve diagnostic image quality.

Fig 2-8 Standard multiplanar view of a CBCT volume of the maxilla with (clockwise from left) axial, coronal, and sagittal sections.

Fig 2-9 Very popular reconstruction layout for CBCT data visualization: Axial section (left) with a curved line indicating the panoramic reconstruction (top right) and a series of cross-sectional images (bottom right) perpendicular to the panoramic curved line.

Orthodontics and CBCT

Traditionally, radiographic imaging in orthodontics was performed using 2D extraoral radiography, namely panoramic and cephalometric radiographs, combined with analyses using manual tracing of the latter and 2D photographs. The main purpose of such imaging in orthodontics is to provide diagnostic information to corroborate the clinical orthodontic diagnosis of skeletal, dental, and soft tissue conditions. Moreover, cephalometric radiography is used as an adjunct to treatment planning, evaluation of growth, treatment progress follow-up, and research purposes.

It needs to be emphasized that this entails the assessment of a 3D object on a 2D basis. Traditionally, the only 3D tool that has been used for diagnosis, treatment planning, and progress evaluation is the plaster dental casts. The task of merging 3D information from plaster casts into 2D radiographic or photographic images is a difficult one. Thus, the result could be an inaccurate diagnosis due to the inability of the diagnostic tools to be combined and reflect the true nature of the malocclusion in 3D.17 According to DiFranco et al, the process of recording a 3D object into 2D data can cause significant data loss and could result in an incomplete diagnosis or even misdiagnosis.18 Although there are problems related to the 2D imaging of 3D subjects, attempts have been made to obtain the necessary information by stereometrics. Nevertheless, this approach was never universally adopted as part of standard acceptable clinical procedure.19,20

It has been demonstrated that deficiencies are revealed where a thorough 3D evaluation of the patient was needed but not performed or cases where 2D radiographic imaging was found to be lacking in differentiating important information. Moreover, complications can arise when information derived from 2D images was misleading, which is common given the projection of intervening anatomical structures. According to Tsolakis et al, conventional radiographic methods demonstrate a more subjective diagnostic procedure compared with CBCT images. Furthermore, CBCT is a more accurate and precise examination method compared with conventional radiography for the localization of impacted teeth and for the identification of root resorption of the adjacent teeth.21

The comparative information presented above begs the question as to whether it is obligatory to perform a CBCT scan without exception on all patients based on the concern of not discovering vital imaging/orthodontic information. In resolving this query, it is recommended to apply the same criteria as in treatment planning, meaning that each patient’s treatment plan should be individualized and based on careful examination leading to the appropriate selection of an imaging modality based on anatomical and functional requirements. Factored into this decision is the added value of 3D imaging and analysis (ie, skeleton, airway, temporomandibular joint [TMJ], impacted teeth, etc), with the principle of ALARA being the golden rule that should always be followed in every orthodontic case.

CBCT in orthodontic treatment stages

Similar to traditional 2D radiographic imaging indications, a CBCT could be performed in the following three stages of orthodontic treatment: (1) diagnosis, (2) treatment, and (3) posttreatment.

Diagnosis stage

CBCT scanning usually is used as a supplemental diagnostic tool for pretreatment assessment of the orthodontic patient. A CBCT can be easily reconstructed into a panoramic, lateral, or posteroanterior cephalometric image. Volume scanning can reveal the contribution of the dental and skeletal elements to the malocclusion or the craniofacial anomaly. Soft tissue can also be assessed and combined with the dental and skeletal elements in order to formulate a treatment plan. In a fully digital orthodontic office where an intraoral scanner and orthodontic diagnostic software (ie, Dolphin Imaging) are present, a CBCT scan can serve as the core of data integration to form the virtual patient. In this way, the orthodontist can combine all the data fragments (puzzlelike format) into a single central image (3D dental cast, CBCT image, 3D face photography), evaluating the totality of a given orthodontic problem from a single unified perspective rather than from disjointed fragments.

Treatment stage

A CBCT should not be performed without profound justification. During treatment it is done mostly to monitor changes that have occurred and to investigate possible problems that were not assessed before treatment, or to evaluate issues that appeared during treatment. An example that justifies this procedure is in preparation for orthognathic surgery, where it has implications for surgical preparation analysis and surgical splint fabrication. Another possible justification is to aid in TAD (temporary anchorage device) placement.

Midtreatment CBCT scans are also appropriate to facilitate clear aligner fabrication as well as to direct orthodontic fixed appliance orientation. In both these instances, a CBCT scan could be fused with the 3D virtual dental cast to evaluate crown and root position in relation to peridental structures. Surface and volume scanning integration are desirable when there is a risk of root recession, fenestration, or dehiscence.

Posttreatment stage

A CBCT is rarely needed after orthodontic treatment. However, it is routinely performed for postsurgical assessment in orthognathic cases, craniofacial deformities, assessment of root resorption, or for TMJ periodic evaluation (Fig 2-10).

Fig 2-10 A CBCT panoramic reconstruction (bottom) and a series of cross-sectional images (top) of the maxilla for the assessment of postsurgical changes in the midface after orthognathic surgery (LeFort 1 osteotomy).a

CBCT indications in orthodontics

Although some authors mention several general indications for CBCT imaging in orthodontics,22–24 there is no true consensus in the field regarding its appropriate indications.25,26 CBCT scans may be used for the following reasons:

•3D patient analysis at diagnosis

•Evaluation of buccolingual root position ( Fig 2-11 )

•Analysis of craniofacial deformities ( Fig 2-12 ) 27, 28

•Imaging of clefts

•Airway volume analysis for patients with sleep apnea (with the disadvantage that the image is acquired in a vertical position instead of in a horizontal position; Fig 2-13 )

•Assessment of dentoalveolar bone loss

•TMJ evaluation ( Fig 2-14 )

•Localization of dental impaction(s), root dilacerations, transposed teeth, supernumerary teeth, external resorption, root fusion, germination, fenestrations, or dehiscence ( Figs 2-15 and 2-16 )

•Computer-aided surgical simulation (CASS)

•Computer-aided orthognathic surgery (CAOS)

•Orthognathic surgical splint design

•3D cephalometry ( Fig 2-17 )

•TAD and miniplate placement planning

•Corroboration of panoramic radiographic findings

•Integration of volume and surface scanning in a virtual setup for aligner design

•In cases of impacted teeth, where the planning of the dental movements has to be performed (once these are defined in 3D) through the design of a force system 29

Fig 2-11 A CBCT panoramic reconstruction (top) and a series of cross-sectional images (bottom) of the anterior maxilla for the assessment of the integrity of the cortical plates and incisor root position inside the alveolar ridge.

Fig 2-12 A CBCT 3D reconstruction illustrating a marked asymmetry between the right and left mandible due to hemimandibular hyperplasia (right side); note the deviated mandibular midline to the left.

Fig 2-13 A CBCT midsagittal section with the airway highlighted (red) ; this is a special software application that provides volumetric measurements of the airway (bottom) , a crucial tool in airway analysis.

Fig 2-14 Coronal section (top) and a series of sagittal cross sections (bottom) of the right and left TMJs acquired for the periodic evaluation of the TMJ after extensive orthognathic surgery; note the marked degenerative changes in both TMJs.

Fig 2-15 A CBCT panoramic reconstruction (bottom) and a series of cross-sectional images (top) of the maxilla and mandible showing extensive root resorption on the maxillary and mandibular incisors after orthodontic treatment.

Fig 2-16 Root fenestrations in the apical third (a) and middle third (b) in two different patients; these were anatomical variants revealed prior to orthodontic treatment.

Fig 2-17 3D volume rendering of the skull, airway, and soft tissue outline with major anatomical landmarks identified; this is an application of contemporary software (courtesy of Anatomage Inc).

According to Tsolakis et al, CBCT seems to be the only reliable and accurate diagnostic method for the exact 3D localization of impacted maxillary canines and root resorption of the adjacent teeth.21,30,31

Advantages of CBCT imaging in orthodontics

Traditional panoramic and cephalometric radiographs have some advantages over CBCT. For example, they carry lower radiation exposure, they are relatively easy to obtain, and they are comparatively inexpensive. On the other hand, 3D imaging affords the clinician several diagnostic refinements