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Di Brigida L, Cortese A, Cataldo E, Naddeo A. A New Method to Design and Manufacture a Low-Cost Custom-Made Template for Mandible Cut and Repositioning Using Standard Plates in BSSO Surgery. Bioengineering (Basel) 2024; 11:668. [PMID: 39061750 PMCID: PMC11273722 DOI: 10.3390/bioengineering11070668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024] Open
Abstract
In this study, a new methodology for designing and creating a custom-made template for maxillofacial surgery has been developed. The custom-made template can be used both for cutting and repositioning of the mandible arches for executing a BSSO (bilateral sagittal split osteotomy) treatment. The idea was developed in order to give the possibility of using a custom-made template with standard plates, thus reducing long times, high costs and low availability of custom-made plates; this represents the proof of novelty of the proposed template, based on a well-established methodology. The methodology was completely developed in the CAD virtual environment and, after the surgeons' assessment, an in-vitro experiment by a maxillofacial surgeon was performed in order to check the usability and the versatility of the system, thanks to the use of additive manufacturing technologies. When computer-aided technologies are used for orthognathic surgery, there are significant time and cost savings that can be realised, as well as improved performance. The cost of the whole operation is lower than the standard one, thanks to the use of standard plates. To carry out the procedures, the proposed methodology allows for inexpensive physical mock-ups that enable the BSSO procedure to be performed.
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Affiliation(s)
- Liliana Di Brigida
- Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy; (L.D.B.); (E.C.)
- Technogym Research and Development Department, Via Calcinaro 2861, 47521 Cesena, FC, Italy
| | - Antonio Cortese
- Department of Medicine, Surgery and Dentistry, University of Salerno, Via Salvador Allende, 84081 Baronissi, SA, Italy;
| | - Emilio Cataldo
- Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy; (L.D.B.); (E.C.)
- Techno Design S.r.l., via Rosa Jemma, 2, 84091 Battipaglia, SA, Italy
| | - Alessandro Naddeo
- Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy; (L.D.B.); (E.C.)
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Chang JS, Ma CY, Ko EWC. Prediction of surgery-first approach orthognathic surgery using deep learning models. Int J Oral Maxillofac Surg 2024:S0901-5027(24)00148-6. [PMID: 38821731 DOI: 10.1016/j.ijom.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 04/24/2024] [Accepted: 05/08/2024] [Indexed: 06/02/2024]
Abstract
The surgery-first approach (SFA) orthognathic surgery can be beneficial due to reduced overall treatment time and earlier profile improvement. The objective of this study was to utilize deep learning to predict the treatment modality of SFA or the orthodontics-first approach (OFA) in orthognathic surgery patients and assess its clinical accuracy. A supervised deep learning model using three convolutional neural networks (CNNs) was trained based on lateral cephalograms and occlusal views of 3D dental model scans from 228 skeletal Class III malocclusion patients (114 treated by SFA and 114 by OFA). An ablation study of five groups (lateral cephalogram only, mandible image only, maxilla image only, maxilla and mandible images, and all data combined) was conducted to assess the influence of each input type. The results showed the average validation accuracy, precision, recall, F1 score, and AUROC for the five folds were 0.978, 0.980, 0.980, 0.980, and 0.998 ; the average testing results for the five folds were 0.906, 0.986, 0.828, 0.892, and 0.952. The lateral cephalogram only group had the least accuracy, while the maxilla image only group had the best accuracy. Deep learning provides a novel method for an accelerated workflow, automated assisted decision-making, and personalized treatment planning.
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Affiliation(s)
- J-S Chang
- Graduate Institute of Dental and Craniofacial Science, Chang Gung University, Taoyuan, Taiwan; Department of Craniofacial Orthodontics, Chang Gung Memorial Hospital, Taipei, Taiwan
| | - C-Y Ma
- Department of Artificial Intelligence, Chang Gung University, Taoyuan, Taiwan; Artificial Intelligence Research Center, Chang Gung University, Taoyuan, Taiwan; Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - E W-C Ko
- Graduate Institute of Dental and Craniofacial Science, Chang Gung University, Taoyuan, Taiwan; Department of Craniofacial Orthodontics, Chang Gung Memorial Hospital, Taipei, Taiwan; Craniofacial Research Center, Chang Gung Memorial Hospital, Linkou, Taiwan.
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Kazimierczak N, Kazimierczak W, Serafin Z, Nowicki P, Nożewski J, Janiszewska-Olszowska J. AI in Orthodontics: Revolutionizing Diagnostics and Treatment Planning-A Comprehensive Review. J Clin Med 2024; 13:344. [PMID: 38256478 PMCID: PMC10816993 DOI: 10.3390/jcm13020344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 12/29/2023] [Accepted: 01/05/2024] [Indexed: 01/24/2024] Open
Abstract
The advent of artificial intelligence (AI) in medicine has transformed various medical specialties, including orthodontics. AI has shown promising results in enhancing the accuracy of diagnoses, treatment planning, and predicting treatment outcomes. Its usage in orthodontic practices worldwide has increased with the availability of various AI applications and tools. This review explores the principles of AI, its applications in orthodontics, and its implementation in clinical practice. A comprehensive literature review was conducted, focusing on AI applications in dental diagnostics, cephalometric evaluation, skeletal age determination, temporomandibular joint (TMJ) evaluation, decision making, and patient telemonitoring. Due to study heterogeneity, no meta-analysis was possible. AI has demonstrated high efficacy in all these areas, but variations in performance and the need for manual supervision suggest caution in clinical settings. The complexity and unpredictability of AI algorithms call for cautious implementation and regular manual validation. Continuous AI learning, proper governance, and addressing privacy and ethical concerns are crucial for successful integration into orthodontic practice.
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Affiliation(s)
- Natalia Kazimierczak
- Kazimierczak Private Medical Practice, Dworcowa 13/u6a, 85-009 Bydgoszcz, Poland
| | - Wojciech Kazimierczak
- Kazimierczak Private Medical Practice, Dworcowa 13/u6a, 85-009 Bydgoszcz, Poland
- Department of Radiology and Diagnostic Imaging, Collegium Medicum, Nicolaus Copernicus University in Torun, Jagiellońska 13-15, 85-067 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Collegium Medicum, Nicolaus Copernicus University in Torun, Jagiellońska 13-15, 85-067 Bydgoszcz, Poland
| | - Paweł Nowicki
- Kazimierczak Private Medical Practice, Dworcowa 13/u6a, 85-009 Bydgoszcz, Poland
| | - Jakub Nożewski
- Department of Emeregncy Medicine, University Hospital No 2 in Bydgoszcz, Ujejskiego 75, 85-168 Bydgoszcz, Poland
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Bonny T, Al Nassan W, Obaideen K, Al Mallahi MN, Mohammad Y, El-damanhoury HM. Contemporary Role and Applications of Artificial Intelligence in Dentistry. F1000Res 2023; 12:1179. [PMID: 37942018 PMCID: PMC10630586 DOI: 10.12688/f1000research.140204.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/24/2023] [Indexed: 11/10/2023] Open
Abstract
Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.
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Affiliation(s)
- Talal Bonny
- Department of Computer Engineering, University of Sharjah, Sharjah, 27272, United Arab Emirates
| | - Wafaa Al Nassan
- Department of Computer Engineering, University of Sharjah, Sharjah, 27272, United Arab Emirates
| | - Khaled Obaideen
- Sustainable Energy and Power Systems Research Centre, RISE, University of Sharjah, Sharjah, 27272, United Arab Emirates
| | - Maryam Nooman Al Mallahi
- Department of Mechanical and Aerospace Engineering, United Arab Emirates University, Al Ain City, Abu Dhabi, 27272, United Arab Emirates
| | - Yara Mohammad
- College of Engineering and Information Technology, Ajman University, Ajman University, Ajman, Ajman, United Arab Emirates
| | - Hatem M. El-damanhoury
- Department of Preventive and Restorative Dentistry, College of Dental Medicine, University of Sharjah, Sharjah, 27272, United Arab Emirates
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M S, Gandedkar NH, kumar S, Kim YJ, Adel SM. AN INTEGRATED 3D-DRIVEN PROTOCOL FOR SURGERY FIRST ORTHOGNATHIC APPROACH (SFOA) USING VIRTUAL SURGICAL PLANNING (VSP). Semin Orthod 2022. [DOI: 10.1053/j.sodo.2022.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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