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AIMS Biophysics, 9(3): 182–197.
DOI: 10.3934/biophy.2022016
Received: 18 March 2022
Revised: 29 May 2022
Accepted: 13 June 2022
Published: 08 July 2022
http://www.aimspress.com/journal/biophysics
Review
Artificial intelligence and 3D printing technology in orthodontics: future
and scope
Mahamad Irfanulla Khan1,*, Laxmikanth SM1, Tarika Gopal1 and Praveen Kumar Neela2
1 Department of Orthodontics, The Oxford Dental College, Bangalore, India
2 Department of Orthodontics, Kamineni Institute of Dental Sciences, Narketpally, Andhra Pradesh,
India
* Correspondence: Email: drirfankhanmds@gmail.com; Tel: +918147170414.
Abstract: New digital technologies, like in other fields, have revolutionized the health care field and
orthodontic practice in the 21st century. They can assist the health care professionals in working more
efficiently by saving time and improving patient care. Recent advances in artificial intelligence (AI)
and 3D printing technology are useful for improving diagnosis and treatment planning, creating
algorithms and manufacturing customized orthodontic appliances. AI accomplishes the task of human
beings with the help of machines and technology. In orthodontics, AI-based models have been used
for diagnosis, treatment planning, clinical decision-making and prognosis prediction. It minimizes the
required workforce and speeds up the diagnosis and treatment procedure. In addition, the 3D printing
technology is used to fabricate study models, clear aligner models, surgical guides for inserting mini-
implants, clear aligners, lingual appliances, wires components for removable appliances and occlusal
splints. This paper is a review of the future and scope of AI and 3D printing technology in orthodontics.
Keywords: orthodontics; artificial intelligence; artificial neural network; 3D printing
1. Introduction
Artificial intelligence (AI) is a general term coined during a Dartmouth summer research project [1].
AI is the study of an equipment/machine that senses its environment and takes measures to increase its
chances of reaching its objectives [2,3]. AI accomplishes the task of human beings with the help of
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machines and technology [4,5]. AI is currently being applied in health care, the automobile industry,
economics, video games, smartphones, etc. [6].
Orthodontics is a branch of dentistry that focuses on diagnosing malocclusions and other
irregularities of the dentofacial region and preventing and correcting them. So, it deals with the
parameters applied to biological systems. AI applications such as machine learning, artificial neural
networks (ANNs), convolutional neural networks (CNNs) and deep learning (DL) are used for
diagnosis and treatment planning, the prognosis of malocclusion in orthodontics with high accuracy,
and to reduce human error [5,7]. In addition, AI can document and send data to clinicians faster and
more efficiently than humans [8].
Three-dimensional (3D) printing, which is also known as additive manufacturing (AM), is a
fabrication procedure that empowers the layer-by-layer development of 3D objects from the computer-
aided design (CAD) data [9]. The final product is obtained by the union of multiple subunits, instead
of via the subtraction of the material. This concept helps lower the consumption of raw materials and
provide high-quality products [10,11]. The advantages of AM include lower time cost, reduced
financial costs, less human interaction and the creation of a product with any complex shape [12]. In
orthodontics, 3D printing technology is used to fabricate study models, clear aligner models, surgical
guides for inserting mini-implants, clear aligners, lingual appliances, wires components for removable
appliances and occlusal splints [13].
Digital technology, like as in other fields, has revolutionized the orthodontic practice of the 21st
century. With the advances in 3D imaging techniques, 3D printing and AI technology, the orthodontist
can improve diagnosis and treatment planning, and create algorithms for the manufacture of
customized orthodontic appliances. This article is a review of the scope of AI and 3D printing
technology in orthodontics.
2. Artificial intelligence and its applications in orthodontics
AI is a science concerned with the computational understanding of intelligent behavior and
creating artifacts that demonstrate it. AI permits accurate patient examination, organization of the
clinical data and treatment planning [14,15]. AI technology works by imitating human intelligence
through a machine that can think and act rationally. Many subfields of AI that have been commonly
used in different areas, mainly biological and medical diagnostics, including machine learning, ANNs,
CNNs and DL. Some of these subfields of AI have been widely used in various sectors, primarily in
biological and medical diagnostics [16]. Machine learning combines factual and probabilistic tools,
and the machines learn from past models and progress their activities when new information is
presented [17]. ANNs are numerical computing models that can re-enact human brain processes and
accomplish different tasks like classification, estimation, design acknowledgment, picture
coordination, chance forecasting and memory simulation [18,19].
New digital technologies have revolutionized the orthodontic practice. They can assist the health
care professionals with working more efficiently by saving time and in improving patient care. AI-
based models have been used in orthodontic diagnosis, treatment planning, clinical decision-making
and prognosis prediction. It minimizes the required human resources and speeds up the diagnosis and
treatment procedure [20,21].
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Figure 1. Applications of AI in orthodontics.
Table 1. Literature showing the applications of AI in orthodontics.
Year
Article
Applications
AI technology
Reference
2010
Artificial neural network
modeling for deciding if
extractions are necessary prior
to orthodontic treatment
Extraction and
non-extraction
therapy in
orthodontics
Machine learning through a 2-
layer neural network
[22]
2016
New approach for the
diagnosis of extractions with
neural network machine
learning
Extraction and
non-extraction
therapy in
orthodontics
Machine learning through a 2-
layer neural network
[23]
2017
Moving towards precision
orthodontics: an evolving
paradigm shift in the planning
and delivery of customized
orthodontic therapy
Diagnosis and
treatment
planning
Fuzzy logic software was used for
the diagnosis and treatment
planning
[24]
2017
Use of automated learning
techniques for predicting
mandibular morphology in
skeletal classes I, II, and III
Mandibular
morphology
An ANN with unidirectional and
basic elements of support vector
regression and support vector
machines were used
[25]
Continued on next page
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Year
Article
Applications
AI technology
Reference
2019
Artificial intelligent model
with neural network machine
learning for the diagnosis of
orthognathic surgery
Orthognathic
surgery
Neural network machine learning
with various cephalometric
software programs
[26]
2019
A computer-assisted
optimization approach for
orthognathic surgery planning
Orthognathic
surgery
Neural network machine learning
with various cephalometric
software programs
[27]
2019
Facial attractiveness of cleft
patients: a direct comparison
between artificial-intelligence-
based scoring and conventional
rater groups
Cleft patients
and facial
attractiveness
An algorithm consisting of a face
detector and CNNs with visual
cortex/vision processing was used
[28]
2019
Deep learning and artificial
intelligence for the
determination of the cervical
vertebra maturation degree
from lateral radiography
Growth and
development
determination
using cervical
vertebrae
CNN and ANN methods, models
and algorithms were used
[29]
2019
Usage and comparison of
artificial intelligence
algorithms for determination of
growth and development by
cervical vertebrae stages in
orthodontics
Growth and
development
determination
using cervical
vertebrae
CNN and ANN with DL methods
were implemented
[30]
2019
Minimally invasive approach
for diagnosing TMJ
osteoarthritis
Temporomand
ibular
disorders
Deep convoluted neural network
[31]
2019
Compliance monitoring via a
Bluetooth-enabled retainer: a
prospective clinical pilot study
Orthodontic
retention
AI with micro-sensor scanning
was used
[32]
2020
Automated detection of TMJ
osteoarthritis based on artificial
intelligence
Temporomand
ibular
disorders
AI with a region of interest
[33]
2021
A review of the use of artificial
intelligence in orthodontics
Diagnosis and
treatment
planning
Fuzzy logic software was used for
the diagnosis and treatment
planning
[34]
2021
Determination of growth and
development periods in
orthodontics with artificial
neural network
Growth
prediction
ANN models were based on
cervical vertebrae algorithms like
scaled conjugate gradient back
propagation and tan-sigmoid
transfer function
[35]
2021
Orthodontic retention: What's
on the horizon?
Orthodontic
retention
Smartphone-enabled temperature
sensor was incorporated
[36]
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AI plays an important role in orthodontics, and it is thought to have the most promising future in
diagnosis and treatment planning. Hence, the present paper was purposed to review the following
applications of AI technology in orthodontics (Figure 1 and Table 1).
2.1. Diagnosis and treatment planning
Diagnosis and treatment planning in orthodontics involve the data obtained from clinical
examinations, photographs, radiographs and study models. All of these investigations involve operator
skills and patient cooperation. AI facilitates the preparation of patients' diagnostic records and helps to
understand the etiology of malocclusion [34]. AI converts the patient information to suit a natural
language processing-based of AI system, which stores the patient data and problems list in the order
of their treatment priority [24,37]. The AI-based treatment prioritization models can obtain high-
performance feature vectors for a more precise treatment plan.
2.2. Cephalometric landmark identification and automated cephalometric tracing
Cephalometry is the measurement of facial and skull bones and the soft tissue profile, and it is
important for diagnosis and treatment planning in orthodontics. Cephalometric tracing can be done
manually or by using computer software [38,39]. Manual cephalometric tracing is time-consuming,
and there is a risk of human error in the landmark identification and measurement of the cephalometric
parameters. The major errors in manual tracing tend to involve radiograph unpredictability in the
landmark identification and measurements [40,41]. Using computers for cephalometric tracing helps
to save time by reducing manual errors and increasing the diagnostic value of the cephalometric
analysis [42]. Existing literature shows that AI-based automated cephalometric tracing has a high
success rate (over 90%) when applied for the differential diagnosis of cephalometric landmarks using
computerized cephalometric software and web-based software [43,44].
To overcome these human errors and increase time efficiency, AI can identify cephalometric
landmarks via a DL method. The You Only Look Once algorithm is an AI-based systems for
identifying cephalometric landmarks [45].
2.3. Extraction and non-extraction therapy in orthodontics
Orthodontic extraction is a major and important decision that significantly impacts the prognosis
and outcome of the treatment. It is based on the orthodontist's clinical experience and expertise, and the
correctness of the diagnostic test results [46]. AI technology based on an ANN algorithm produced
impressive results, ranging from 80% to 92% accuracy, and it was proved to be a useful tool for extraction
decision-making. This can be additional support for clinicians with relatively less clinical experience [23].
Literature reviews showed that the success rate of the AI models was 93% for the diagnosis of extraction
or non-extraction therapy, and 84% for the selection of extraction patterns [22].
2.4. Growth prediction
The growth and development rate of the face is important for achieving good orthodontic therapy,
as they play a crucial role in the treatment of skeletal discrepancies associated with growth spurts and
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physiological facial growth [35]. The ANN has been created to be comparable to the biological
structure of the human brain, and it mimics the way nerve cells work in the human brain. The hand-
wrist and lateral cephalometric radiographs (for cervical vertebrae) are commonly used to predict
growth and development. Using ANN algorithms, AI technology accurately determines the growth
and development rate based on hand-wrist radiographs and the cervical vertebrae.
2.5. Orthognathic surgery
AI has tremendous potential for application in the diagnosis of dentofacial deformities and
treatment planning of orthognathic surgeries. A CNN algorithm revealed that orthognathic surgery
significantly improved most patients' profiles and facial attractiveness [26]. AI intervenes at various
levels to optimize the data acquisition, processing and pre-analysis of maxillofacial imagery [47]. AI
systems facilitate diagnostic precision for orthognathic surgeries, treatment planning using 3D
models (3D printing of surgical splints) and enhanced therapeutic follow-up and image
superimposition [27,48]. The use of AI in intraoral scanner software allows faster and more efficient
data procurement, which results in higher-quality images with lower radiation and is thus beneficial
for the 3D reconstructions of images [49].
2.6. Cleft patients and facial attractiveness
Although AI has not been broadly connected to assessing facial attractiveness, it enables the
single-face image assessment of attractiveness based on the attractiveness of facial attributes and
combinations [50]. Using a CNN trained on large data and mirroring relevant opinions may be useful
for objectively and reproducibly interpreting facial appearance [51]. One of the most obvious
advantages of a single AI-based score would be eliminating the variability and subjectivity associated
with flexible panel-based ratings. The AI-based results are comparable, but they require further
improvement and refinement to distinguish facial cleft features, which negatively impact the human
perception of attractiveness [28,52].
Machine learning algorithms are also used to build predictive models with single nucleotide
polymorphisms (SNPs). SNPs are the most common type of genetic variation among people. Therefore,
machine learning methods such as the support vector machine, logistic regression, naive Bayesian
classification, random forests, the k-nearest neighbor method, decision trees and ANN-based
methods are used to evaluate the genetic risk assessment in cleft lip and palate etiology [53].
2.7. Mandibular morphology
The mandible plays a key role in decisions for occlusion, treatment planning and growth
prediction applications in orthodontics because its morphology influences facial aesthetics. In addition,
identification of the mandibular morphology becomes important in forensic dentistry when a facial
reconstruction is performed, as in the case of a missing person whose mandibular bone has been lost [54].
In the absence of the mandible, AI has significant potential in mandibular prediction because ANN
can be used in the facial reconstruction [25].
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2.8. Growth and development determination using cervical vertebrae
In orthodontics, the right treatment timing and jawbone growth and development are important for
successful treatment. The stages of growth can be studied by using the cervical vertebra maturation (CVM)
stages [29]. AI technology, such as CNN and DL methods, models and algorithms, can be used to
determine CVM stages. AI algorithms such as k-nearest neighbors, naive Bayes, decision trees, ANNs,
support vector machines, random forests and logistic regression are available for CVM determination [30].
2.9. Temporomandibular disorders
Temporomandibular joint (TMJ) disorders constitute the second-most common musculoskeletal
condition; they cause pain and disability and affect approximately 5% to 12% of the population. Using a
deep neural network model, AI can aid in automatically detecting TMJ osteoarthritis (TMJOA) [33]. It
might as well be used to help clinicians diagnose and decide on the treatment of TMJOA. In the future,
an AI model that incorporates data other than images, such as signs, symptoms and patient demographic
data, would tremendously increase diagnostic accuracy [31]. Furthermore, AI-based TMJ images shed
light on the clinical phenotypes of TMJOA and their possible links to etiologic factors such as
biomarkers, genetic variations and immunologic responses.
2.10. Orthodontic retention
After the active phase of orthodontic treatment, retainers are passive orthodontic appliances that
maintain and stabilize the position of teeth. AI can help with retention monitoring, the fabrication of
different types of retainer materials and the digital workflow to design customized retainers. AI-based
DentalMonitoring (Paris, France) software has been introduced to monitor the retention protocol,
including factors such as stability, retainer adjustment problems and oral hygiene maintenance. This
software makes use of intraoral photographs captured by patients' smartphones. This is useful for the
clinician, as it reduces the chair time and preferences for patients and motivates patients to maintain
and follow the instructions on using the retainer [32,36,55].
Advances in digital technologies made it possible to fabricate retainers by using a digital
workflow. An intraoral scan of the dentition can be used to plan the customized nickel-titanium
retainer digitally. It is then precision-manufactured by using a CAD-Computer aided
manufacturing (CAM) process, ensuring a close fit to the palatal and lingual surfaces of the teeth [56].
The clear plastic retainers were fabricated using 3D-printed models created from intraoral scans, and
they are just as the accurate as retainers made using traditional impressions [57,58].
3. Three-dimensional printing and its applications in orthodontics
Three-dimensional printing technology, also known as AM, is constructed by the addition of a
material layer-by-layer in a specific pattern using a CAD/CAM design [59]. Charles Hull
invented 3D printing, and the standard tessellation language (STL), or stereolithography, is the most
commonly used file format for editing and preparing objects for 3D printing [60]. Additive techniques
enable the creation of complex and difficult structures and geometries with undercuts or hollows
that would be impossible to create using traditional methods [61,62].
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Figure 2. Applications of 3D printing technology in orthodontics.
Table 2. Literature showing the applications of 3D printing in orthodontics.
Year
Article
Applications
3D printing technology
Reference
2003
Customized brackets and arch
wires for lingual orthodontic
treatment
Custom-made lingual
orthodontic brackets,
wires
An optical 3D scanner
was used
[63]
2006
Rapid prototyping as a tool
for diagnosis and treatment
planning for maxillary canine
impaction
Maxillary canine
impaction diagnosis and
treatment planning
Computed tomography
(CT) scanning with rapid
prototyping software to
construct 3D models was
used
[64]
2008
Herbst appliance in lingual
orthodontics
Custom-made lingual
orthodontic brackets,
wires
An optical 3D scanner
with STL was used
[65]
2012
Bone anchor systems for
orthodontic application: a
systematic review
Surgical guides for the
placement of
orthodontic mini-screws
and miniplates
Stereolithography with
CAD/CAM drill guide
was used
[66]
2013
A digital process for additive
manufacturing of occlusal
splints: a clinical pilot study
Occlusal splints
A laser-based AM
technique was used
[67]
2014
Virtual techniques for
designing and fabricating a
retainer
Customized orthodontic
retainers
DICOM images with
selective laser sintering
[68]
2017
Developing customized
dental miniscrew surgical
template from thermoplastic
polymer material using image
superimposition, CAD
system, and 3D Printing
Surgical guides for the
placement of
orthodontic mini-screws
and miniplates
Stereolithography with
CAD/CAM drill guide
was used
[69]
Continued on next page
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Year
Article
Applications
3D printing technology
Reference
2020
Accuracy of digital light
processing printing of 3-
dimensional dental models
Orthodontic study
models
3D printing and liquid
polyjet photopolymer
were used
[70]
2020
Evaluation of the
effectiveness of a tailored
mobile application in
increasing the duration of
wear of thermoplastic
retainers: a randomized
controlled trial
Approaches to enhance
removable retainer wear
A micro-electronic
sensor was used to
evaluate the wear of the
clear plastic retainer
[55]
2021
Removable retention:
enhancing adherence and the
remit of shared decision-
making
Removable orthodontic
retainers
Shared decision-making
and motivational
interviewing were used
for removable orthodontic
retainers
[71]
Advantages of 3D printing include accuracy, high-quality production, full integration with a
digital workflow (utilization of intraoral scanners and digital models), reduced manufacturing costs,
ability to detect and repair scanned faults before model printing, smaller required manual workforce
and cost savings on materials. The disadvantages include a large required initial capital investment for the
purchase of the 3D printer and post-processing hardware, the need for staff training to master new skills,
the need to process the scan file and manipulate the digital models before printing, the post-print
washing and curing phases and the need for an update of health practices and the safety guidelines for
the handling and storage of new materials [72].
Advances in 3D printing technology have been explored for automobiles, aviation, aerospace,
science and medicine. Various materials, such as gypsum, metal alloys, glass, carbon fiber, resins,
organic materials, living cells and tissues, can be used to print objects with 3D printers. Some of the
materials mentioned above have widespread applications in dentistry and orthodontics.
Three-dimensional printing applications in orthodontics (Figure 2 and Table 2) include the
fabrication of diagnostic and working orthodontic study models, surgical templates and guides for the
placement of mini-implants, clear aligners and lingual appliances, as well as wire components for
removable appliances and occlusal splints [73].
3.1. Orthodontic study models
Three-dimensional printing can fabricate orthodontic study models owing to its accuracy,
visualization and accessibility [70,74]. It can convert a digital, virtual dental model of a patient's
dentition into a physical model, skipping the conventional steps of impression-taking and model
casting [75]. The 3D-printed models are useful for fabricating removable orthodontic appliances,
expansion appliances, indirect bonding trays and thermoplastic aligners [76].
3.2. Removable orthodontic appliances
Several removable orthodontic appliances and other appliances such as the activator and sleep
apnea devices are manufactured using 3D printing technology. With the advancement of 3D printing,
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the Hawley retainer can be fabricated using an intraoral scanner, eliminating the need for conventional
impression-taking and pouring study models [71,77]. At present, 3D printing technology allows the
manufacture of wire components, such as labial bows and clasps, as well as the incorporation of these
parts into the base plate of the appliance. Another important use of 3D printing is the fabrication of
custom-made soft silicone removable appliances [78]. Although the literature mentioned earlier and
appliances are only case reports, they demonstrate the potential of 3D printing applications in
orthodontics. The procedures described by the article authors must be evaluated, particularly regarding
costs, workflow, accuracy and clinical efficiency.
3.3. Maxillary canine impaction diagnosis and treatment planning
Maxillary canine impaction is one of the most common dental anomalies in orthodontic patients.
Identifying the correct location and angulation is crucial for the success of treatment. The 3D printing
of an anatomical model created from computed tomography images of an impacted maxillary canine
allows clinicians to thoroughly assess and visualize the anatomy, localization of the impacted tooth
and surgical exposure procedure of the impacted tooth [64]
3.4. Custom-made lingual orthodontic brackets and wires
Lingual orthodontic brackets can be manufactured using 3D printing. The digital design enables
customization of the in-out, angulation and bracket torque for an individual bracket prescription
created for each patient. Wiechmann et al. [63] presented 3D printing to make wax designs of lingual
brackets, permitting customization of the bracket design. Making thicker and amplified bracket bases
on maxillary teeth, as well as starting with the molars and mandibular canines to make those brackets
as groups, was part of the digital design of lingual orthodontic brackets. Exact prototyping of the
planned machine is required and can be accomplished with 3D printing technology, allowing
customized fixed functional treatment in conjunction with lingual orthodontic treatment [65].
3.5. Occlusal splints
Occlusal splints are used to treat temporomandibular disorders. The occlusal splints prepared
from the 3D printing were more accurate as the best fit for the patients. In addition, the printing
preparation is very reproducible and faster, and it significantly reduces fabrication time relative to that
for the conventional fabrication method of splints [67]. One advantage of AM is that it allows one to
print a large number of individual splints in a short period using modern digital technology, thereby
eliminating manual working phases in a dental laboratory. This could reduce costs, technician working
time and chair-side time in the coming years.
3.6. Surgical guides for the placement of orthodontic mini-screws and miniplates
Miniplates and orthodontic mini-screws are used in a variety of orthodontic treatment procedures,
including those for the intrusion of molars, the correction of open bite, molar distalization and
maxillary impaction or protraction [66]. Hence, accurate placement of these mini-screws and
miniplates in patients is critical for the success of treatment. The material utilized to construct surgical
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guides should be firm and sufficient to stay stable during the mini-implant insertion procedure. Three-
dimensional-printed surgical guides have become progressively popular because they offer
orthodontists a safe and simple method of placing mini-implants [69,79]. They provide custom-made
adaptation, accuracy and precision for the placement of the final position of the miniplate, as well as
the utmost surface contact between the bone and the miniplate, stability and a lower risk of miniplate
failure [80–82].
3.7. Customized orthodontic retainers
Three-dimensional printing opens a new avenue in orthodontics to fabricate custom-made
removable retainers. The procedure incorporates cutting-edge technologies such as cone-beam computed
tomography (CBCT), CAD and 3D printing. The first step is to use CBCT to scan the patient's dentition
and create a 3D model of the patient's dentition. The retainer is virtually designed after importing
the 3D model into dedicated software, and it is possible to print a clear plastic retainer directly by using
an additive 3D printing process [68,83].
4. Conclusions
AI and 3D printing technology have revolutionized oral health care and the orthodontic practice
by addressing the weaknesses of conventional diagnosis and treatment planning procedures. With AI-
based algorithms, orthodontists can better diagnose and plan treatment, whereas 3D printing helps
manufacture customized orthodontic appliances with precision.
AI and 3D printing can solve various clinical problems, improve diagnosis, clinical decision-
making and prediction of failures, as well as reduce the chair side time, bypass various extra steps of
conventional methods and provide quality treatment with accuracy and precision. There is fascinating
literature evidence that AI and 3D printing broaden the scope of state-of-the-art technology in
orthodontics and can play a crucial role in sufficiently aiding practicing clinicians in delivering health
care in the 21st century.
Conflict of interest
All authors declare no conflicts of interest in this paper.
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