Highlights
- •Combining multisource images such as cone beam computed tomography systems and three-dimensional digital dental models is essential for implant planning.
- •Data science approaches, advances in the image analysis field, and new artificial intelligence approaches are now available.
- •Better and more personalized treatment can now help the clinical decision making and the prognosis.
ABSTRACT
In the digital dentistry era, new tools, algorithms, data science approaches, and
computer applications are available to researchers and clinicians. However, there
is also a strong need for better knowledge and understanding of multisource data applications,
including three-dimensional imaging information such as cone-beam computed tomography
images and digital dental models for multidisciplinary cases. In addition, artificial
intelligence models and automated clinical decision systems are rising. The clinician
needs to plan the treatment based on state-of-the-art diagnosis for better and more
personalized treatment. This article aimed to review basic concepts and the current
panorama of digital implant planning in orthodontics, with open-source and closed-source
tools for assessing cone-beam computed images and digital dental models. The visualization
and processing of the three-dimensional data allow better implant planning based on
bone conditions, adjacent teeth and root positions, and the prognosis of the case.
We showed that many tools for assessment, segmentation, and visualization of cone-beam
computed tomographic images and digital dental models could facilitate the treatment
planning of patients needing implants or space closure. The tools and approaches presented
are toward personalized treatment and better prognosis, following the path to a more
automated clinical decision system based on multisource three-dimensional data, artificial
intelligence models, and digital planning. In summary, the orthodontist needs to analyze
each patient individually and use different software or tools that better fit their
practice, allowing efficient treatment planning and satisfactory results with an adequate
prognosis.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Journal of the World Federation of OrthodontistsAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Combined orthodontic and prosthetic therapy. Special considerations.Dent Clin North Am. 1996; 40: 911-943
- Consensus Conference Panel Report: crown-height space guidelines for implant dentistry - part 1.Implant Dent. 2005; 14: 312-318
- Clinical complications with implants and implant prostheses.J Prosthet Dent. 2003; 90: 121-132
- Advancements in digital imaging: what is new and on the horizon?.J Am Dent Assoc. 2008; 139 (Suppl.):20S–4S
- Big data analytics in healthcare: promise and potential.Health Inf Sci Syst. 2014; 2: 3
- From big data analysis to personalized medicine for all: challenges and opportunities.BMC Med Genomics. 2015; 8: 33
- Clinical decision support systems in orthodontics: a narrative review of data science approaches.Orthod Craniofac Res. 2021; 24: 26-36
- A review on patient-specific facial and cranial implant design using Artificial Intelligence (AI) techniques.Expert Rev Med Devices. 2021; 18: 985-994
- The use and performance of artificial intelligence in prosthodontics: a systematic review.Sensors (Basel). 2021; 21: 6628
- Artificial intelligence in fixed implant prosthodontics: a retrospective study of 106 implant-supported monolithic zirconia crowns inserted in the posterior jaws of 90 patients.BMC Oral Health. 2020; 20: 80
- CBCT: basics and applications in dentistry.J Istanb Univ Fac Dent. 2017; 51: 102-121
- Intra-arch dimensional measurement validity of laser-scanned digital dental models compared with the original plaster models: a systematic review.Orthod Craniofac Res. 2015; 18: 65-76
- Comparison of space analysis evaluations with digital models and plaster dental casts.Am J Orthod Dentofacial Orthop. 2009; 136 (16.e1–4)
- Dental long axes using digital dental models compared to cone-beam computed tomography.Orthod Craniofac Res. 2022; 25: 64-72
- Automatic segmentation of dental root canal and merging with crown shape.Annu Int Conf IEEE Eng Med Biol Soc. 2021; 2021: 2948-2951
Github. SlicerAutomatedDentalTools. Available from: https://github.com/DCBIA-OrthoLab/SlicerAutomatedDentalTools [Accessed 10/02/2022].
- Multiclass CBCT image segmentation for orthodontics with deep learning.J Dent Res. 2021; 100: 943-949
- Accuracy and reliability of a novel method for fusion of digital dental casts and cone beam computed tomography scans.PLoS One. 2013; 8: e59130
- A new method for the integration of digital dental models and cone-beam computed tomography images.Annu Int Conf IEEE Eng Med Biol Soc. 2013; 2013: 2328-2331
- Application of artificial intelligence in dentistry.J Dent Res. 2021; 100: 232-244
- Artificial intelligence in prosthodontics: a scoping review on current applications and future possibilities.Int J Adv Med. 2022; 9: 367
- Artificial intelligence in fractured dental implant detection and classification: evaluation using dataset from two dental hospitals.Diagnostics (Basel). 2021; 11: 233
- The digital POIP concept: Preorthodontic implant placement.J Esthet Restor Dent. 2020; 32: 545-553
- Present and the future of digital orthodontics✰.Semin Orthod. 2018; 24: 376-385
- Comparison of conventional and digital workflow for dental rehabilitation with a novel patient-specific framework implant system: an experimental dataset evaluation.Int J Implant Dent. 2022; 8: 4
Article info
Publication history
Published online: November 15, 2022
Accepted:
October 20,
2022
Received in revised form:
October 20,
2022
Received:
September 7,
2022
Footnotes
Funding: American Association of Orthodontists Foundation; National Institute of Dental and Craniofacial Research, Grant/Award Number: R01DE024450 and the Research Enhancement Award Activity 141 from the University of the Pacific, Arthur A. Dugoni School of Dentistry.
Competing interests: Authors have completed and submitted the ICMJE Form for Disclosure of potential conflicts of interest. None declared.
Provenance and peer review: Commissioned and internally peer reviewed.
Identification
Copyright
© 2022 World Federation of Orthodontists. Published by Elsevier Inc. All rights reserved.
