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Muñoz G, Zamora D, Brito L, Ravelo V, de Moraes M, Olate S. Comparison Between an Expert Operator an Inexperienced Operator, and Artificial Intelligence Software: A Brief Clinical Study of Cephalometric Diagnostic. J Craniofac Surg 2024:00001665-990000000-01663. [PMID: 38830014 DOI: 10.1097/scs.0000000000010346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 05/03/2024] [Indexed: 06/05/2024] Open
Abstract
INTRODUCTION Artificial intelligence (AI) is constantly developing in several medical areas and has become useful to assist with treatment planning. Orthodontics and maxillofacial surgery use AI-based technology to identify and select cephalometric points for diagnostics. Although some studies have shown promising results from the use of AI, the evidence is still limited. Hence, additional investigation is justified. MATERIALS AND METHODS In this retrospective study, 2 human operators (1 expert and 1 inexperienced) and 1 software analyzed 30 lateral cephalograms of individuals with orthodontic treatment indications. They measured 10 cephalometric variables and then 2 weeks later, repeated measurements on 30% of the sample. We evaluated the reliability of the measurements between the 2-time points and the differences in the means between the expert operator and the AI software and between the expert and inexperienced operators. RESULTS There was high reliability for the expert operator and AI measurements, and moderate reliability for the inexperienced operator measurements. There were some significant differences in the means produced by the AI software and the inexperienced operator compared with the expert operator. CONCLUSION Although AI is useful for cephalometric analysis, it should be used with caution because there are differences compared with analysis by humans.
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Affiliation(s)
- Gonzalo Muñoz
- Doctoral Program in Morphological Sciences, Universidad de La Frontera
- Undergraduate Dentistry Research Group (GIPO), Faculty of Health Sciences (FACSA), Universidad Autónoma de Chile
| | - Daniel Zamora
- Undergraduate Dentistry Program, Department of pedriatric dentistry and orthodontics, faculty of dentistry, Universidad de La Frontera, Temuco, Chile
| | - Leonardo Brito
- Undergraduate Dentistry Research Group (GIPO), Faculty of Health Sciences (FACSA), Universidad Autónoma de Chile
| | - Victor Ravelo
- Doctoral Program in Morphological Sciences, Universidad de La Frontera
| | - Marcio de Moraes
- Division of Oral and Maxillofacial Surgery, Piracicaba Dental School, State University of Campinas, SP, Brazil
| | - Sergio Olate
- CEMyQ, Center of Excellence in Morphological and Surgical Studies, Universidad de La Frontera
- Division of Oral, Facial and Maxillofacial Surgery, Universidad de La Frontera, Temuco, Chile
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Salazar D, Rossouw PE, Javed F, Michelogiannakis D. Artificial intelligence for treatment planning and soft tissue outcome prediction of orthognathic treatment: A systematic review. J Orthod 2024; 51:107-119. [PMID: 37772513 DOI: 10.1177/14653125231203743] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/30/2023]
Abstract
BACKGROUND The accuracy of artificial intelligence (AI) in treatment planning and outcome prediction in orthognathic treatment (OGT) has not been systematically reviewed. OBJECTIVES To determine the accuracy of AI in treatment planning and soft tissue outcome prediction in OGT. DESIGN Systematic review. DATA SOURCES Unrestricted search of indexed databases and reference lists of included studies. DATA SELECTION Clinical studies that addressed the focused question 'Is AI useful for treatment planning and soft tissue outcome prediction in OGT?' were included. DATA EXTRACTION Study screening, selection and data extraction were performed independently by two authors. The risk of bias (RoB) was assessed using the Cochrane Collaboration's RoB and ROBINS-I tools for randomised and non-randomised clinical studies, respectively. DATA SYNTHESIS Eight clinical studies (seven retrospective cohort studies and one randomised controlled study) were included. Four studies assessed the role of AI for treatment decision making; and four studies assessed the accuracy of AI in soft tissue outcome prediction after OGT. In four studies, the level of agreement between AI and non-AI decision making was found to be clinically acceptable (at least 90%). In four studies, it was shown that AI can be used for soft tissue outcome prediction after OGT; however, predictions were not clinically acceptable for the lip and chin areas. All studies had a low to moderate RoB. LIMITATIONS Due to high methodological inconsistencies among the included studies, it was not possible to conduct a meta-analysis and reporting biases assessment. CONCLUSION AI can be a useful aid to traditional treatment planning by facilitating clinical treatment decision making and providing a visualisation tool for soft tissue outcome prediction in OGT. REGISTRATION PROSPERO CRD42022366864.
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Affiliation(s)
- Daisy Salazar
- Department of Orthodontics and Dentofacial Orthopedics, Eastman Institute for Oral Health, University of Rochester, Rochester, NY, USA
| | - Paul Emile Rossouw
- Department of Orthodontics and Dentofacial Orthopedics, Eastman Institute for Oral Health, University of Rochester, Rochester, NY, USA
| | - Fawad Javed
- Department of Orthodontics and Dentofacial Orthopedics, Eastman Institute for Oral Health, University of Rochester, Rochester, NY, USA
| | - Dimitrios Michelogiannakis
- Department of Orthodontics and Dentofacial Orthopedics, Eastman Institute for Oral Health, University of Rochester, Rochester, NY, USA
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Fudalej PS, Garlicka A, Dołęga-Dołegowski D, Dołęga-Dołegowska M, Proniewska K, Voborna I, Dubovska I. Mixed reality-based technology to visualize and facilitate treatment planning of impacted teeth: Proof of concept. Orthod Craniofac Res 2024. [PMID: 38712682 DOI: 10.1111/ocr.12803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2024] [Indexed: 05/08/2024]
Abstract
OBJECTIVE We propose a method utilizing mixed reality (MR) goggles (HoloLens 2, Microsoft) to facilitate impacted canine alignment, as planning the traction direction and force delivery could benefit from 3D data visualization using mixed reality (MR). METHODS Cone-beam CT scans featuring isometric resolution and low noise-to-signal ratio were semi-automatically segmented in Inobitec software. The exported 3D mesh (OBJ file) was then optimized for the HoloLens 2. Using the Unreal Engine environment, we developed an application for the HoloLens 2, implementing HoloLens SDK and UX Tools. Adjustable pointers were added for planning attachment placement, traction direction, and point of force application. The visualization was presented to participants of a course on impacted teeth treatment, followed by a 10-question survey addressing potential advantages (5-point scale: 1 = totally agree, 5 = totally disagree). RESULTS Out of 38 respondents, 44.7% were orthodontists, 34.2% dentists, 15.8% dental students, and 5.3% dental technicians. Most respondents (44.7%) were between 35 and 44 years old, and only 1 (2.6%) respondent was 55-64 years old. Median answers for six questions were 'totally agree' (25th percentile 1, 75th percentile 2) and for four questions 'agree' (25th percentile 1, 75th percentile 2). No correlation was found between age, profession, and responses. CONCLUSION Our method generated substantial interest among clinicians. The initial responses affirm the potential benefits, supporting the continued exploration of MR-based techniques for the treatment of impacted teeth. However, the recommendation for widespread use awaits validation through clinical trials.
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Affiliation(s)
- Piotr S Fudalej
- Department of Orthodontics, Jagiellonian University Medical College, Jagiellonian University in Cracow, Krakow, Poland
- Department of Orthodontics and Dentofacial Orthopedics, Medical Faculty, School of Dental Medicine, University of Bern, Bern, Switzerland
- Faculty of Medicine and Dentistry, Institute of Dentistry and Oral Sciences, Palacký University Olomouc, Olomouc, Czech Republic
| | - Agnieszka Garlicka
- Department of Orthodontics, Jagiellonian University Medical College, Jagiellonian University in Cracow, Krakow, Poland
| | | | | | - Klaudia Proniewska
- Jagiellonian University Medical College, Jagiellonian University in Cracow, Krakow, Poland
| | - Iva Voborna
- Faculty of Medicine and Dentistry, Institute of Dentistry and Oral Sciences, Palacký University Olomouc, Olomouc, Czech Republic
| | - Ivana Dubovska
- Faculty of Medicine and Dentistry, Institute of Dentistry and Oral Sciences, Palacký University Olomouc, Olomouc, Czech Republic
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Kılınç DD, Mansız D. Examination of the reliability and readability of Chatbot Generative Pretrained Transformer's (ChatGPT) responses to questions about orthodontics and the evolution of these responses in an updated version. Am J Orthod Dentofacial Orthop 2024; 165:546-555. [PMID: 38300168 DOI: 10.1016/j.ajodo.2023.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 11/01/2023] [Accepted: 11/01/2023] [Indexed: 02/02/2024]
Abstract
INTRODUCTION This study aimed to assess the reliability and readability of Chatbot Generative Pretrained Transformer (ChatGPT) responses to questions about orthodontics and the evolution of these responses in an updated version. METHODS Frequently asked questions about orthodontics by laypeople on Web sites were determined using the Google Search Tool. These questions were asked to both ChatGPT's March 23 version and May 24 version on April 20, 2023, and July 12, 2023, respectively. Responses were assessed for readability and reliability using the Flesch-Kincaid and DISCERN tests. RESULTS The mean DISCERN value for general questions was 2.96 ± 0.05, 3.04 ± 0.06, 2.38 ± 0.27, and 2.82 ± 0.31 for treatment-related questions; the mean Flesch-Kincaid Reading Ease score for general questions was 29.28 ± 8.22, 25.12 ± 7.39, 47.67 ± 10.77, and 41.60 ± 9.54 for treatment-related questions; mean Flesch-Kincaid Grade Level for general questions was 14.52 ± 1.48 and 14.04 ± 1.25 and 11.90 ± 2.08 and 11.41 ± 1.88 for treatment-related questions; in first and second evaluations respectively (P = 0.001). CONCLUSIONS In the second evaluation, the reliability of the answers given to general questions and treatment-related questions increased. However, in both evaluations, the reliability of the answers was found to be moderate according to the DISCERN tool. On the second evaluation, Flesch Reading Ease Scores for both general questions and treatment-related questions decreased, meaning that the readability of the new response texts became more difficult. Flesch-Kincaid Grade Level results were found at the college graduate level in the first and second evaluations for general questions and at the high school level in the first and second evaluations for treatment-related questions.
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Affiliation(s)
- Delal Dara Kılınç
- Department of Orthodontics, School of Dental Medicine, Bahçeşehir University, Istanbul, Turkey.
| | - Duygu Mansız
- Department of Orthodontics, Faculty of Dentistry, Istanbul Aydin University, Istanbul, Turkey
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Loomans B, Mendes FM, Vinayahalingam S, Xi T, Opdam N, Kreulen CM, Pereira-Cenci T, Cenci MS. Challenges in conducting clinical research in primary care dentistry. J Dent 2024; 144:104958. [PMID: 38522408 DOI: 10.1016/j.jdent.2024.104958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 03/26/2024] Open
Abstract
The integration of dentistry into primary health care is crucial for promoting patient well-being. However, clinical studies in dentistry face challenges, including issues with study design, transparency, and relevance to primary care. Clinical trials in dentistry often focus on specific issues with strict eligibility criteria, limiting the generalizability of findings. Randomized clinical trials (RCTs) face challenges in reflecting real-world conditions and using clinically relevant outcomes. The need for more pragmatic approaches and the inclusion of clinically relevant outcomes (CROs) is discussed, such as tooth loss or implant success. Solutions proposed include well-controlled observational studies, optimized data collection tools, and the integration of artificial intelligence (AI) for predictive modelling, computer-aided diagnostics and automated diagnosis. In this position paper advocates for more efficient trials with a focus on patient-centred outcomes, as well as the adoption of pragmatic study designs reflecting real-world conditions. Collaborative research networks, increased funding, enhanced data retrieval, and open science practices are also recommended. Technology, including intraoral scanners and AI, is highlighted for improving efficiency in dental research. AI is seen as a key tool for participant recruitment, predictive modelling, and outcome evaluation. However, ethical considerations and ongoing validation are emphasized to ensure the reliability and trustworthiness of AI-driven solutions in dental research. In conclusion, the efficient conduct of clinical research in primary care dentistry requires a comprehensive approach, including changes in study design, data collection, and analytical methods. The integration of AI is seen as pivotal in achieving these objectives in a meaningful and efficient way.
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Affiliation(s)
- Bac Loomans
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands.
| | - F M Mendes
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands; Department of Pediatric Dentistry, School of Dentistry, University of São Paulo, São Paulo, Brazil
| | - S Vinayahalingam
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
| | - T Xi
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
| | - Njm Opdam
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
| | - C M Kreulen
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
| | - T Pereira-Cenci
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
| | - M S Cenci
- Department of Oral and Maxillofacial Surgery, Radboud Institute for Medical Innovation, Radboud University Medical Center, Philips van Leydenlaan 25, EX 6525 Nijmegen, The Netherlands
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Spielman AI. Dental education and practice: past, present, and future trends. FRONTIERS IN ORAL HEALTH 2024; 5:1368121. [PMID: 38694791 PMCID: PMC11061397 DOI: 10.3389/froh.2024.1368121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/02/2024] [Indexed: 05/04/2024] Open
Abstract
This position paper explores the historical transitions and current trends in dental education and practice and attempts to predict the future. Dental education and practice landscape, especially after the COVID-19 epidemic, are at a crossroads. Four fundamental forces are shaping the future: the escalating cost of education, the laicization of dental care, the corporatization of dental care, and technological advances. Dental education will likely include individualized, competency-based, asynchronous, hybrid, face-to-face, and virtual education with different start and end points for students. Dental practice, similarly, will be hybrid, with both face-to-face and virtual opportunities for patient care. Artificial intelligence will drive efficiencies in diagnosis, treatment, and office management.
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Affiliation(s)
- Andrew I. Spielman
- Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY, United States
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Buduru S, Cofar F, Mesaroș A, Tăut M, Negucioiu M, Almășan O. Perceptions in Digital Smile Design: Assessing Laypeople and Dental Professionals' Preferences Using an Artificial-Intelligence-Based Application. Dent J (Basel) 2024; 12:104. [PMID: 38668016 PMCID: PMC11049051 DOI: 10.3390/dj12040104] [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: 02/15/2024] [Revised: 04/01/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Digital Smile Design (DSD) is used in many fields of dentistry. This prospective observational study assessed laypeople's and dental professionals' perceptions of a DSD application. SmileCloud, an online DSD platform, was used to create two different designs for three patients; after that, the participants, in a 30-question online illustrated survey, were asked about the most attractive design and other features of the smile. Dentists' and laypeople's perceptions about specific DSD features were assessed. The Kolmogorov-Smirnov normality test was used. Descriptive and crosstab analyses compared the respondents' opinions for each statement. Chi-square tests were used to determine the relationship between the questions and any association with age, gender, and profession. The test results were rated as significant at a p-value < 0.05. A total of 520 participants (dental professionals, students, dental technicians, and laypeople) were enrolled. The statistically significant features were self-esteem related to appearance (p = 0.05), facial and smile symmetry (p = 0.42, p < 0.0001), tooth color (p = 0.012), and symmetry of gums (p < 0.001). For each patient, the design with dominant round upper incisors and perfect symmetry was preferred (p < 0.001). Digital pre-visualization benefits diagnosis and enriches treatment planning. The dentist-dental technician-patient team should be involved in the decision-making process of pre-visualization.
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Affiliation(s)
- Smaranda Buduru
- Prosthetic Dentistry and Dental Materials Department, Iuliu Hațieganu University of Medicine and Pharmacy, 32 Clinicilor Street, 400006 Cluj-Napoca, Romania; (S.B.); (A.M.); (O.A.)
| | - Florin Cofar
- Doctoral School, Dental Medicine, Victor Babeş University of Medicine and Pharmacy, 300041 Timișoara, Romania;
| | - Anca Mesaroș
- Prosthetic Dentistry and Dental Materials Department, Iuliu Hațieganu University of Medicine and Pharmacy, 32 Clinicilor Street, 400006 Cluj-Napoca, Romania; (S.B.); (A.M.); (O.A.)
| | - Manuela Tăut
- Prosthetic Dentistry and Dental Materials Department, Iuliu Hațieganu University of Medicine and Pharmacy, 32 Clinicilor Street, 400006 Cluj-Napoca, Romania; (S.B.); (A.M.); (O.A.)
| | - Marius Negucioiu
- Prosthetic Dentistry and Dental Materials Department, Iuliu Hațieganu University of Medicine and Pharmacy, 32 Clinicilor Street, 400006 Cluj-Napoca, Romania; (S.B.); (A.M.); (O.A.)
| | - Oana Almășan
- Prosthetic Dentistry and Dental Materials Department, Iuliu Hațieganu University of Medicine and Pharmacy, 32 Clinicilor Street, 400006 Cluj-Napoca, Romania; (S.B.); (A.M.); (O.A.)
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Mao F, Wang M, Zhou S, Zhao Y, Huang J, Yin F, Yang H, Ding PH. Clinical relevance of distolingual roots and periodontal status in mandibular first molars: a cross-sectional study employing CBCT analysis. J Zhejiang Univ Sci B 2024; 25:244-253. [PMID: 38453638 PMCID: PMC10918409 DOI: 10.1631/jzus.b2300586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 12/11/2023] [Indexed: 03/09/2024]
Abstract
OBJECTIVES: Distolingual root of the permanent mandibular first molar (PMFM-DLR) has been frequently reported, which may complicate the treatment of periodontitis. This study aimed to assess the morphological features of PMFM-DLR and investigate the correlation between the morphological features of PMFM-DLR and periodontal status in patients with Eastern Chinese ethnic background. MATERIALS AND METHODS: A total of 836 cone beam computed tomography (CBCT) images with 1497 mandibular first molars were analyzed to observe the prevalence of PMFM-DLR at the patients and tooth levels in Eastern China. Among them, complete periodontal charts were available for 69 Chinese patients with 103 teeth. Correlation and regression analyses were used to evaluate the correlation between the morphological features of DLR, bone loss, and periodontal clinical parameters, including clinical attachment loss (CAL), probing pocket depth (PPD), gingival recession (GR), and furcation involvement (FI). RESULTS: The patient-level prevalence and tooth-level prevalence of DLR in mandibular first molars were 29.4% and 26.3%, respectively. Multiple linear regression analysis suggested that bone loss at the lingual site and CAL were negatively affected by the angle of separation between distolingual and mesial roots in the transverse section, while they were significantly influenced by age and the angle of separation between distobuccal and mesial roots in the coronal section. CONCLUSIONS: The prevalence of PMFM-DLR in Eastern China was relatively high in our cohort. The morphological features of DLR were correlated with the periodontal status of mandibular first molars. This study provides critical information on the morphological features of DLR for improved diagnosis and treatment options of mandibular molars with DLR.
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Affiliation(s)
- Feifei Mao
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Meng Wang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Shuai Zhou
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Yan Zhao
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Jiaping Huang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Fengying Yin
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Haiping Yang
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China
| | - Pei-Hui Ding
- Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou 310016, China.
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Cheung K, Cheung W, Liu Y, Ye H, Lv L, Zhou Y. Establishment of a 3D esthetic analysis workflow on 3D virtual patient and preliminary evaluation. BMC Oral Health 2024; 24:328. [PMID: 38475773 DOI: 10.1186/s12903-024-04085-0] [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: 08/31/2023] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND In esthetic dentistry, a thorough esthetic analysis holds significant role in both diagnosing diseases and designing treatment plans. This study established a 3D esthetic analysis workflow based on 3D facial and dental models, and aimed to provide an imperative foundation for the artificial intelligent 3D analysis in future esthetic dentistry. METHODS The established 3D esthetic analysis workflow includes the following steps: 1) key point detection, 2) coordinate system redetermination and 3) esthetic parameter calculation. The accuracy and reproducibility of this established workflow were evaluated by a self-controlled experiment (n = 15) in which 2D esthetic analysis and direct measurement were taken as control. Measurement differences between 3D and 2D analysis were evaluated with paired t-tests. RESULTS 3D esthetic analysis demonstrated high consistency and reliability (0.973 < ICC < 1.000). Compared with 2D measurements, the results from 3D esthetic measurements were closer to direct measurements regarding tooth-related esthetic parameters (P<0.05). CONCLUSIONS The 3D esthetic analysis workflow established for 3D virtual patients demonstrated a high level of consistency and reliability, better than 2D measurements in the precision of tooth-related parameter analysis. These findings indicate a highly promising outlook for achieving an objective, precise, and efficient esthetic analysis in the future, which is expected to result in a more streamlined and user-friendly digital design process. This study was registered with the Ethics Committee of Peking University School of Stomatology in September 2021 with the registration number PKUSSIRB-202168136.
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Affiliation(s)
- Kwantong Cheung
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China
| | - Waisze Cheung
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China
| | - Yunsong Liu
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China
| | - Hongqiang Ye
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China
| | - Longwei Lv
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China.
| | - Yongsheng Zhou
- Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Disease & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, No. 22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, China.
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Albagieh H, Alzeer ZO, Alasmari ON, Alkadhi AA, Naitah AN, Almasaad KF, Alshahrani TS, Alshahrani KS, Almahmoud MI. Comparing Artificial Intelligence and Senior Residents in Oral Lesion Diagnosis: A Comparative Study. Cureus 2024; 16:e51584. [PMID: 38173951 PMCID: PMC10763647 DOI: 10.7759/cureus.51584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/03/2024] [Indexed: 01/05/2024] Open
Abstract
INTRODUCTION Artificial intelligence (AI) is a field of computer science that seeks to build intelligent machines that can carry out tasks that usually necessitate human intelligence. AI may help dentists with a variety of dental tasks, including clinical diagnosis and treatment planning. This study aims to compare the performance of AI and oral medicine residents in diagnosing different cases, providing treatment, and determining if it is reliable to assist them in their field of work. METHODS The study conducted a comparative analysis of the responses from third- and fourth-year residents trained in Oral Medicine and Pathology at King Saud University, College of Dentistry. The residents were given a closed multiple-choice test consisting of 19 questions with four response options labeled A-D and one question with five response options labeled A-E. The test was administered via Google Forms, and each resident's response was stored electronically in an Excel sheet (Microsoft® Corp., Redmond, WA). The residents' answers were then compared to the responses generated by three major language models: OpenAI, Stablediffusion, and PopAI. The questions were inputted into the language models in the same format as the original test, and prior to each question, an artificial intelligence chat session was created to eliminate memory retention bias. The input was done on November 19, 2023, the same day the official multiple-choice test was administered. The study had a sample size of 20 residents trained in Oral Medicine and Pathology at King Saud University, College of Dentistry, consisting of both third-year and fourth-year residents. RESULT The responses of three large language models (LLM), including OpenAI, Stablediffusion, and PopAI, as well as the responses of 20 senior residents for 20 clinical cases about oral lesion diagnosis. There were no significant variations observed for the remaining questions in the responses to only two questions (10%). For the remaining questions, there were no significant differences. The median (IQR) score of LLMs was 50.0 (45.0 to 60.0), with a minimum of 40 (for stable diffusion) and a maximum of 70 (for OpenAI). The median (IQR) score of senior residents was 65.0 (55.0-75.0). The highest and lowest scores of residents were 40 and 90, respectively. There was no significant difference in the percent scores of residents and LLMs (p = 0.211). The agreement level was measured using the Kappa value. The agreement among senior dental residents was observed to be weak, with a Kappa value of 0.396. In contrast, the agreement among LLMs demonstrated a moderate level, with a Kappa value of 0.622, suggesting a more cohesive alignment in responses among the artificial intelligence models. When comparing residents' responses with those generated by different OpenAI models, including OpenAI, Stablediffusion, and PopAI, the agreement levels were consistently categorized as weak, with Kappa values of 0.402, 0.381, and 0.392, respectively. CONCLUSION What the current study reveals is that when comparing the response score, there is no significant difference, in contrast to the agreement analysis among the residents, which was low compared to the LLMs, in which it was high. Dentists should consider that AI is very beneficial in providing diagnosis and treatment and use it to assist them.
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Affiliation(s)
| | - Zaid O Alzeer
- Dentistry, College of Dentistry, King Saud University, Riyadh, SAU
| | - Osama N Alasmari
- Dentistry, College of Dentistry, King Saud University, Riyadh, SAU
| | - Abdullah A Alkadhi
- College of Dentistry, Dental University Hospital/King Saud University, Riyadh, SAU
| | - Abdulaziz N Naitah
- College of Dentistry, Dental University Hospital/King Saud University, Riyadh, SAU
| | | | - Turki S Alshahrani
- College of Dentistry, Dental University Hospital/King Saud University, Riyadh, SAU
| | - Khalid S Alshahrani
- College of Dentistry, Dental University Hospital/King Saud University, Riyadh, SAU
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11
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Wood RE, Gardner T. Forensic odontology in DVI-A path forward. J Forensic Sci 2023. [PMID: 37929668 DOI: 10.1111/1556-4029.15412] [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: 09/11/2023] [Revised: 10/07/2023] [Accepted: 10/10/2023] [Indexed: 11/07/2023]
Abstract
Dental identification is a pillar of disaster victim identification (DVI). Dental identification is accurate, efficient, inexpensive, and accepted in courts of law. The (known) antemortem (AM) dental charts and radiographic images acquired from the dentist of the missing person are evaluated, processed, and compared to post mortem (PM) findings present in the dentition or fragments of the dentition of the deceased individual. These comparisons evaluate and assess individuating restorative dental work, dental anatomical areas of concordance, spatial relationships of teeth one to another, and occasionally calculate the degree of "uniqueness" of either or both of the AM and PM dentition compared to known population databases. In a multiple fatality incident, odontologists may utilize age stratification to assist other means of identification. Computer comparison algorithms using recorded data can indicate possible matches between AM and PM data sets. Following clinical assessment, collection of post mortem tooth specimens for DNA profiling generation may be undertaken. This paper will highlight modern and efficient use of these tools. The framework for how dental identification in these incidents is currently managed is presented. The authors propose a change to this approach that moves away from interpretive subjective assessment toward comparisons based largely on objective data. The aim of this paper is to highlight the benefits of minimizing subjective decisions and maximizing objective data in the dental DVI process while simultaneously reducing risk to clinical personnel and minimizing costs by reducing the number of clinicians required onsite.
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Affiliation(s)
- Robert E Wood
- Ontario Forensic Pathology Service and Office of the Chief Coroner for Ontario, Toronto, Ontario, Canada
| | - Taylor Gardner
- Ontario Forensic Pathology Service and Office of the Chief Coroner for Ontario, Toronto, Ontario, Canada
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12
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Pascadopoli M, Zampetti P, Nardi MG, Pellegrini M, Scribante A. Smartphone Applications in Dentistry: A Scoping Review. Dent J (Basel) 2023; 11:243. [PMID: 37886928 PMCID: PMC10605491 DOI: 10.3390/dj11100243] [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: 08/30/2023] [Revised: 10/05/2023] [Accepted: 10/19/2023] [Indexed: 10/28/2023] Open
Abstract
This scoping review aims to investigate the latest literature concerning the use of smartphone applications (apps) in the prevention, management, and monitoring of oral diseases. Smartphone applications are software programs that are designed to run on smartphones. Nowadays, smartphones are regularly used by people of all ages, and mobile health apps (MHAs) represent an important means of spreading information related to oral health, which is the state of the mouth and teeth, including the gums and other tissues. Several apps have been designed to promote prevention, diagnosis, and therapeutic adherence monitoring. This scoping review considered randomized clinical trials, cross-sectional studies, before-after (pre-post) studies with no control group, and observational studies. Once the inclusion and exclusion criteria had been defined, a preliminary confined search was performed on PubMed and Scopus; key terms from the collected articles were selected to design a search strategy, and then a search of all the included articles' reference lists was run for further research. Studies were excluded if they did not fulfill the inclusion criteria. The preferred reporting items for scoping reviews (PRISMA-ScR) consensus was followed. The risk of bias was evaluated by providing a qualitative analysis of the clinical studies via the National Heart, Lung, and Blood Institute (NHLBI) Quality Assessment of Controlled Intervention Studies, Observational Cohort Studies, and Cross-Sectional Studies (NHLBI, NIH). A total of 21 studies were included in this review. As it is clear from the studies selected, the literature indicates that MHAs are effective in improving oral hygiene in adolescents and children and reducing the dental plaque index, including in patients undergoing orthodontic treatment. MHAs are also able to reduce the symptoms of patients affected by obstructive sleep apnea-hypopnea syndrome (OSAHS) and improve the swallowing-related quality of life of elderly patients. MHAs are furthermore recommended to decrease dental anxiety among patients, both during dental procedures and the post-operative period. MHAs are useful to spread knowledge about traumatic dental injuries among non-oral health professionals and to monitor dental erosion and awake bruxism. MHAs' clinical outcomes might have been influenced by the demographic features of the subjects involved. Further studies considering a longer follow-up period and larger samples are needed. In conclusion, MHAs can be considered a useful tool to monitor oral disease and increase patients' quality of life related to oral health.
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Affiliation(s)
- Maurizio Pascadopoli
- Unit of Orthodontics and Pediatric Dentistry, Section of Dentistry, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (M.P.); (P.Z.); (A.S.)
| | - Paolo Zampetti
- Unit of Orthodontics and Pediatric Dentistry, Section of Dentistry, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (M.P.); (P.Z.); (A.S.)
| | - Maria Gloria Nardi
- Unit of Orthodontics and Pediatric Dentistry, Section of Dentistry, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (M.P.); (P.Z.); (A.S.)
| | - Matteo Pellegrini
- Maxillofacial Surgery and Dental Unit, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Via della Commenda 10, 20122 Milan, Italy
| | - Andrea Scribante
- Unit of Orthodontics and Pediatric Dentistry, Section of Dentistry, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy; (M.P.); (P.Z.); (A.S.)
- Unit of Dental Hygiene, Section of Dentistry, Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
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Cagna DR, Donovan TE, McKee JR, Eichmiller F, Metz JE, Marzola R, Murphy KG, Troeltzsch M. Annual review of selected scientific literature: A report of the Committee on Scientific Investigation of the American Academy of Restorative Dentistry. J Prosthet Dent 2023; 130:453-532. [PMID: 37453884 DOI: 10.1016/j.prosdent.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 07/18/2023]
Abstract
The Scientific Investigation Committee of the American Academy of Restorative Dentistry offers this review of the 2022 dental literature to briefly touch on several topics of interest to modern restorative dentistry. Each committee member brings discipline-specific expertise in their subject areas that include (in order of the appearance in this report): prosthodontics; periodontics, alveolar bone, and peri-implant tissues; dental materials and therapeutics; occlusion and temporomandibular disorders; sleep-related breathing disorders; oral medicine and oral and maxillofacial surgery; and dental caries and cariology. The authors focused their efforts on reporting information likely to influence the daily dental treatment decisions of the reader with an emphasis on innovations, new materials and processes, and future trends in dentistry. With the tremendous volume of literature published daily in dentistry and related disciplines, this review cannot be comprehensive. Instead, its purpose is to update interested readers and provide valuable resource material for those willing to subsequently pursue greater detail on their own. Our intent remains to assist colleagues in navigating the tremendous volume of newly minted information produced annually. Finally, we hope that readers find this work helpful in managing patients.
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Affiliation(s)
- David R Cagna
- Professor, Associate Dean, Chair, and Residency Director, Department of Prosthodontics, University of Tennessee Health Sciences Center College of Dentistry, Memphis, Tenn.
| | - Terence E Donovan
- Professor, Department of Comprehensive Oral Health, University of North Carolina School of Dentistry, Chapel Hill, NC
| | - James R McKee
- Private practice, Restorative Dentistry, Downers Grove, Ill
| | - Frederick Eichmiller
- Vice President and Science Officer (Emeritus), Delta Dental of Wisconsin, Stevens Point, Wis
| | - James E Metz
- Private practice, Restorative Dentistry, Columbus, Ohio
| | | | - Kevin G Murphy
- Associate Clinical Professor, Department of Periodontics, University of Maryland College of Dentistry, Baltimore, Md
| | - Matthias Troeltzsch
- Private practice, Oral, Maxillofacial, and Facial Plastic Surgery, Ansbach, Germany; Department of Oral and Maxillofacial Surgery and Facial Plastic Surgery, University Hospital, Ludwig Maximilian University of Munich (LMU), Munich, Germany
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14
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Altalhi AM, Alharbi FS, Alhodaithy MA, Almarshedy BS, Al-Saaib MY, Al Jfshar RM, Aljohani AS, Alshareef AH, Muhayya M, Al-Harbi NH. The Impact of Artificial Intelligence on Dental Implantology: A Narrative Review. Cureus 2023; 15:e47941. [PMID: 38034167 PMCID: PMC10685062 DOI: 10.7759/cureus.47941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
Implant dentistry has witnessed a transformative shift with the integration of artificial intelligence (AI) technologies. This article explores the role of AI in implant dentistry, emphasizing its impact on diagnostics, treatment planning, and patient outcomes. AI-driven image analysis and deep learning algorithms enhance the precision of implant placement, reducing risks and optimizing aesthetics. Moreover, AI-driven data analytics provide valuable insights into patient-specific treatment strategies, improving overall success rates. As AI continues to evolve, it promises to reshape the landscape of implant dentistry and lead in an era of personalized and efficient oral healthcare.
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Affiliation(s)
| | | | | | | | | | | | | | - Adeeb H Alshareef
- Dentistry, King Saud Bin Abdulaziz University for Health Sciences, Riyadh, SAU
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15
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Vera M, Gómez-Silva MJ, Vera V, López-González CI, Aliaga I, Gascó E, Vera-González V, Pedrera-Canal M, Besada-Portas E, Pajares G. Artificial Intelligence Techniques for Automatic Detection of Peri-implant Marginal Bone Remodeling in Intraoral Radiographs. J Digit Imaging 2023; 36:2259-2277. [PMID: 37468696 PMCID: PMC10501983 DOI: 10.1007/s10278-023-00880-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 06/30/2023] [Accepted: 07/01/2023] [Indexed: 07/21/2023] Open
Abstract
Peri-implantitis can cause marginal bone remodeling around implants. The aim is to develop an automatic image processing approach based on two artificial intelligence (AI) techniques in intraoral (periapical and bitewing) radiographs to assist dentists in determining bone loss. The first is a deep learning (DL) object-detector (YOLOv3) to roughly identify (no exact localization is required) two objects: prosthesis (crown) and implant (screw). The second is an image understanding-based (IU) process to fine-tune lines on screw edges and to identify significant points (intensity bone changes, intersections between screw and crown). Distances between these points are used to compute bone loss. A total of 2920 radiographs were used for training (50%) and testing (50%) the DL process. The mAP@0.5 metric is used for performance evaluation of DL considering periapical/bitewing and screws/crowns in upper and lower jaws, with scores ranging from 0.537 to 0.898 (sufficient because DL only needs an approximation). The IU performance is assessed with 50% of the testing radiographs through the t test statistical method, obtaining p values of 0.0106 (line fitting) and 0.0213 (significant point detection). The IU performance is satisfactory, as these values are in accordance with the statistical average/standard deviation in pixels for line fitting (2.75/1.01) and for significant point detection (2.63/1.28) according to the expert criteria of dentists, who establish the ground-truth lines and significant points. In conclusion, AI methods have good prospects for automatic bone loss detection in intraoral radiographs to assist dental specialists in diagnosing peri-implantitis.
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Affiliation(s)
- María Vera
- Department of Conservative Dentistry and Prostheses, Faculty of Dentistry, Complutense University of Madrid, Madrid, Spain
| | - María José Gómez-Silva
- Department of Computer Architecture and Automation, Faculty of Informatics, Complutense University of Madrid, Madrid, Spain
| | - Vicente Vera
- Department of Conservative Dentistry and Prostheses, Faculty of Dentistry, Complutense University of Madrid, Madrid, Spain
| | - Clara I. López-González
- Department of Software Engineering and Artificial Intelligence, Faculty of Informatics, Complutense University of Madrid, Madrid, Spain
| | - Ignacio Aliaga
- Department of Conservative Dentistry and Prostheses, Faculty of Dentistry, Complutense University of Madrid, Madrid, Spain
| | - Esther Gascó
- Department of Software Engineering and Artificial Intelligence, Faculty of Informatics, Complutense University of Madrid, Madrid, Spain
| | - Vicente Vera-González
- Department of Conservative Dentistry and Prostheses, Faculty of Dentistry, Complutense University of Madrid, Madrid, Spain
| | - María Pedrera-Canal
- Hospital Clínico San Carlos, Complutense University of Madrid, Madrid, Spain
| | - Eva Besada-Portas
- Department of Computer Architecture and Automation, Faculty of Informatics, Complutense University of Madrid, Madrid, Spain
| | - Gonzalo Pajares
- Instituto de Tecnología del Conocimiento (Institute of Knowledge Technology), Complutense University of Madrid, Madrid, Spain
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16
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Al-Namankany A. Influence of Artificial Intelligence-Driven Diagnostic Tools on Treatment Decision-Making in Early Childhood Caries: A Systematic Review of Accuracy and Clinical Outcomes. Dent J (Basel) 2023; 11:214. [PMID: 37754334 PMCID: PMC10530226 DOI: 10.3390/dj11090214] [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: 07/14/2023] [Revised: 08/23/2023] [Accepted: 09/11/2023] [Indexed: 09/28/2023] Open
Abstract
Early detection and accurate prediction of the risk of early childhood caries (ECC) are essential for effective prevention and management. This systematic review aims to assess the performance and applicability of machine learning algorithms in ECC prediction and detection. A comprehensive search was conducted to identify studies utilizing machine learning algorithms to predict or detect ECC. The included (n = 6) studies demonstrated high accuracy, sensitivity, specificity, and area under the receiver operating characteristic (AUC) values related to predicting and detecting ECC. The application of machine learning algorithms contributed to enhanced clinical decision-making, targeted preventive measures, and improved ECC management. The studies also highlighted the importance of considering multiple factors, including demographic, environmental, and genetic factors, when developing dental caries prediction models. Machine learning algorithms hold significant potential for ECC prediction and detection, having promising performance outcomes. Due to the heterogeneity of the studies, no meta-analysis could be performed. Moreover, further research is needed to explore the feasibility, acceptability, and effectiveness of integrating these algorithms into dental practice. This approach would ultimately contribute to enabling more effective and personalized dental caries management and improved oral health outcomes for diverse populations.
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Affiliation(s)
- Abeer Al-Namankany
- Paediatric Dentistry and Orthodontics Department, College of Dentistry, Taibah University, P.O. Box 41141, Almadinah Almunawwarah 38008, Saudi Arabia
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Stafie CS, Sufaru IG, Ghiciuc CM, Stafie II, Sufaru EC, Solomon SM, Hancianu M. Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review. Diagnostics (Basel) 2023; 13:1995. [PMID: 37370890 DOI: 10.3390/diagnostics13121995] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 06/29/2023] Open
Abstract
Artificial intelligence (AI) plays a more and more important role in our everyday life due to the advantages that it brings when used, such as 24/7 availability, a very low percentage of errors, ability to provide real time insights, or performing a fast analysis. AI is increasingly being used in clinical medical and dental healthcare analyses, with valuable applications, which include disease diagnosis, risk assessment, treatment planning, and drug discovery. This paper presents a narrative literature review of AI use in healthcare from a multi-disciplinary perspective, specifically in the cardiology, allergology, endocrinology, and dental fields. The paper highlights data from recent research and development efforts in AI for healthcare, as well as challenges and limitations associated with AI implementation, such as data privacy and security considerations, along with ethical and legal concerns. The regulation of responsible design, development, and use of AI in healthcare is still in early stages due to the rapid evolution of the field. However, it is our duty to carefully consider the ethical implications of implementing AI and to respond appropriately. With the potential to reshape healthcare delivery and enhance patient outcomes, AI systems continue to reveal their capabilities.
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Affiliation(s)
- Celina Silvia Stafie
- Department of Preventive Medicine and Interdisciplinarity, Grigore T. Popa University of Medicine and Pharmacy Iasi, Universitatii Street 16, 700115 Iasi, Romania
| | - Irina-Georgeta Sufaru
- Department of Periodontology, Grigore T. Popa University of Medicine and Pharmacy Iasi, Universitatii Street 16, 700115 Iasi, Romania
| | - Cristina Mihaela Ghiciuc
- Department of Morpho-Functional Sciences II-Pharmacology and Clinical Pharmacology, Grigore T. Popa University of Medicine and Pharmacy Iasi, Universitatii Street 16, 700115 Iasi, Romania
| | - Ingrid-Ioana Stafie
- Endocrinology Residency Program, Sf. Spiridon Clinical Emergency Hospital, Independentei 1, 700111 Iasi, Romania
| | | | - Sorina Mihaela Solomon
- Department of Periodontology, Grigore T. Popa University of Medicine and Pharmacy Iasi, Universitatii Street 16, 700115 Iasi, Romania
| | - Monica Hancianu
- Pharmacognosy-Phytotherapy, Grigore T. Popa University of Medicine and Pharmacy Iasi, Universitatii Street 16, 700115 Iasi, Romania
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Zhu J, Chen Z, Zhao J, Yu Y, Li X, Shi K, Zhang F, Yu F, Shi K, Sun Z, Lin N, Zheng Y. Artificial intelligence in the diagnosis of dental diseases on panoramic radiographs: a preliminary study. BMC Oral Health 2023; 23:358. [PMID: 37270488 DOI: 10.1186/s12903-023-03027-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 05/09/2023] [Indexed: 06/05/2023] Open
Abstract
BACKGROUND Artificial intelligence (AI) has been introduced to interpret the panoramic radiographs (PRs). The aim of this study was to develop an AI framework to diagnose multiple dental diseases on PRs, and to initially evaluate its performance. METHODS The AI framework was developed based on 2 deep convolutional neural networks (CNNs), BDU-Net and nnU-Net. 1996 PRs were used for training. Diagnostic evaluation was performed on a separate evaluation dataset including 282 PRs. Sensitivity, specificity, Youden's index, the area under the curve (AUC), and diagnostic time were calculated. Dentists with 3 different levels of seniority (H: high, M: medium, L: low) diagnosed the same evaluation dataset independently. Mann-Whitney U test and Delong test were conducted for statistical analysis (ɑ=0.05). RESULTS Sensitivity, specificity, and Youden's index of the framework for diagnosing 5 diseases were 0.964, 0.996, 0.960 (impacted teeth), 0.953, 0.998, 0.951 (full crowns), 0.871, 0.999, 0.870 (residual roots), 0.885, 0.994, 0.879 (missing teeth), and 0.554, 0.990, 0.544 (caries), respectively. AUC of the framework for the diseases were 0.980 (95%CI: 0.976-0.983, impacted teeth), 0.975 (95%CI: 0.972-0.978, full crowns), and 0.935 (95%CI: 0.929-0.940, residual roots), 0.939 (95%CI: 0.934-0.944, missing teeth), and 0.772 (95%CI: 0.764-0.781, caries), respectively. AUC of the AI framework was comparable to that of all dentists in diagnosing residual roots (p > 0.05), and its AUC values were similar to (p > 0.05) or better than (p < 0.05) that of M-level dentists for diagnosing 5 diseases. But AUC of the framework was statistically lower than some of H-level dentists for diagnosing impacted teeth, missing teeth, and caries (p < 0.05). The mean diagnostic time of the framework was significantly shorter than that of all dentists (p < 0.001). CONCLUSIONS The AI framework based on BDU-Net and nnU-Net demonstrated high specificity on diagnosing impacted teeth, full crowns, missing teeth, residual roots, and caries with high efficiency. The clinical feasibility of AI framework was preliminary verified since its performance was similar to or even better than the dentists with 3-10 years of experience. However, the AI framework for caries diagnosis should be improved.
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Affiliation(s)
- Junhua Zhu
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Zhi Chen
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Jing Zhao
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yueyuan Yu
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Xiaojuan Li
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Kangjian Shi
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Fan Zhang
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, Zhejiang, China
| | - Feifei Yu
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Keying Shi
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Zhe Sun
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Nengjie Lin
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Yuanna Zheng
- School/Hospital of Stomatology, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
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Tiwari A, Kumar A, Jain S, Dhull KS, Sajjanar A, Puthenkandathil R, Paiwal K, Singh R. Implications of ChatGPT in Public Health Dentistry: A Systematic Review. Cureus 2023; 15:e40367. [PMID: 37456464 PMCID: PMC10340128 DOI: 10.7759/cureus.40367] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 06/10/2023] [Indexed: 07/18/2023] Open
Abstract
An artificial intelligence (AI) program called ChatGPT that generates text in response to typed commands has proven to be highly popular, as evidenced by the fact that OpenAI makes it available online. The goal of the present investigation was to investigate ChatGPT's potential applications as an outstanding instance of large language models (LLMs) in the fields of public dental health schooling, writing for academic use, research in public dental health, and clinical practice in public dental health based on the available data. Importantly, the goals of the current review included locating any drawbacks and issues that might be connected to using ChatGPT in the previously mentioned contexts in healthcare settings. Using search phrases including chatGPT, implications, artificial intelligence (AI), public health dentistry, public health, practice in public health dentistry, education in public health dentistry, academic writing in public health dentistry, etc., a thorough search was carried out on the Pubmed database, the Embase database, the Ovid database, the Global Health database, PsycINFO, and the Web of Science. The dates of publication were not restricted. Systematic searches were carried out for all publications according to inclusion and exclusion criteria between March 31, 2018, and March 31, 2023. Eighty-four papers were obtained through a literature search using search terms. Sixteen similar and duplicate papers were excluded and 68 distinct articles were initially selected. Thirty-three articles were excluded after reviewing abstracts and titles. Thirty-five papers were selected, for which full text was managed. Four extra papers were found manually from references. Thirty-nine articles with full texts were eligible for the study. Eighteen inadequate articles are excluded from the final 21 studies that were finally selected for systemic review. According to previously published studies, ChatGPT has demonstrated its effectiveness in helping scholars with the authoring of scientific research and dental studies. If the right structures are created, ChatGPT can offer suitable responses and more time to concentrate on the phase of experimentation for scientists. Risks include prejudice in the training data, undervaluing human skills, the possibility of fraud in science, as well as legal and reproducibility concerns. It was concluded that practice considering ChatGPT's potential significance, the research's uniqueness, and the premise-the activity of the human brain-remains. While there is no question about the superiority of incorporating ChatGPT into the practice of public health dentistry, it does not, in any way, take the place of a dentist since clinical practice involves more than just making diagnoses; it also involves relating to clinical findings and providing individualized patient care. Even though AI can be useful in a number of ways, a dentist must ultimately make the decision because dentistry is a field that involves several disciplines.
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Affiliation(s)
- Anushree Tiwari
- Clinical Quality and Value, American Academy of Orthopaedic Surgeons, Rosemont, USA
| | - Amit Kumar
- Department of Dentistry, All India Institute of Medical Sciences, Patna, IND
| | - Shailesh Jain
- Department of Prosthodontics and Crown and Bridge, School of Dental Sciences, Sharda University, Greater Noida, IND
| | - Kanika S Dhull
- Department of Pedodontics and Preventive Dentistry, Kalinga Institute of Dental Sciences (KIIT) Deemed to be University, Bhubaneswar, IND
| | - Arunkumar Sajjanar
- Department of Pediatrics and Preventive Dentistry, Swargiya Dadasaheb Kalmegh Smruti Dental College and Hospital, Nagpur, IND
| | - Rahul Puthenkandathil
- Department of Prosthodontics and Crown and Bridge, AB Shetty Memorial Institute of Dental Sciences (ABSMIDS) Nitte (Deemed to be University), Mangalore, IND
| | - Kapil Paiwal
- Department of Oral and Maxillofacial Pathology, Daswani Dental College and Research Center, Kota, IND
| | - Ramanpal Singh
- Oral Medicine and Radiology, New Horizon Dental College and Research Institute, Bilaspur, IND
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20
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Kim H, Kim CS, Lee JM, Lee JJ, Lee J, Kim JS, Choi SH. Prediction of Fishman's skeletal maturity indicators using artificial intelligence. Sci Rep 2023; 13:5870. [PMID: 37041244 PMCID: PMC10090071 DOI: 10.1038/s41598-023-33058-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 04/06/2023] [Indexed: 04/13/2023] Open
Abstract
The present study aimed to evaluate the performance of automated skeletal maturation assessment system for Fishman's skeletal maturity indicators (SMI) for the use in dental fields. Skeletal maturity is particularly important in orthodontics for the determination of treatment timing and method. SMI is widely used for this purpose, as it is less time-consuming and practical in clinical use compared to other methods. Thus, the existing automated skeletal age assessment system based on Greulich and Pyle and Tanner-Whitehouse3 methods was further developed to include SMI using artificial intelligence. This hybrid SMI-modified system consists of three major steps: (1) automated detection of region of interest; (2) automated evaluation of skeletal maturity of each region; and (3) SMI stage mapping. The primary validation was carried out using a dataset of 2593 hand-wrist radiographs, and the SMI mapping algorithm was adjusted accordingly. The performance of the final system was evaluated on a test dataset of 711 hand-wrist radiographs from a different institution. The system achieved a prediction accuracy of 0.772 and mean absolute error and root mean square error of 0.27 and 0.604, respectively, indicating a clinically reliable performance. Thus, it can be used to improve clinical efficiency and reproducibility of SMI prediction.
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Affiliation(s)
- Harim Kim
- Department of Orthodontics, Institute of Craniofacial Deformity, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | | | - Ji-Min Lee
- Department of Orthodontics, Institute of Craniofacial Deformity, Yonsei University College of Dentistry, Seoul, Republic of Korea
| | | | | | | | - Sung-Hwan Choi
- Department of Orthodontics, Institute of Craniofacial Deformity, Yonsei University College of Dentistry, Seoul, Republic of Korea.
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21
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Strunga M, Urban R, Surovková J, Thurzo A. Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment. Healthcare (Basel) 2023; 11:healthcare11050683. [PMID: 36900687 PMCID: PMC10000479 DOI: 10.3390/healthcare11050683] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 02/17/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023] Open
Abstract
This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients' treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently.
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22
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Developments and Performance of Artificial Intelligence Models Designed for Application in Endodontics: A Systematic Review. Diagnostics (Basel) 2023; 13:diagnostics13030414. [PMID: 36766519 PMCID: PMC9913920 DOI: 10.3390/diagnostics13030414] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 01/26/2023] Open
Abstract
Technological advancements in health sciences have led to enormous developments in artificial intelligence (AI) models designed for application in health sectors. This article aimed at reporting on the application and performances of AI models that have been designed for application in endodontics. Renowned online databases, primarily PubMed, Scopus, Web of Science, Embase, and Cochrane and secondarily Google Scholar and the Saudi Digital Library, were accessed for articles relevant to the research question that were published from 1 January 2000 to 30 November 2022. In the last 5 years, there has been a significant increase in the number of articles reporting on AI models applied for endodontics. AI models have been developed for determining working length, vertical root fractures, root canal failures, root morphology, and thrust force and torque in canal preparation; detecting pulpal diseases; detecting and diagnosing periapical lesions; predicting postoperative pain, curative effect after treatment, and case difficulty; and segmenting pulp cavities. Most of the included studies (n = 21) were developed using convolutional neural networks. Among the included studies. datasets that were used were mostly cone-beam computed tomography images, followed by periapical radiographs and panoramic radiographs. Thirty-seven original research articles that fulfilled the eligibility criteria were critically assessed in accordance with QUADAS-2 guidelines, which revealed a low risk of bias in the patient selection domain in most of the studies (risk of bias: 90%; applicability: 70%). The certainty of the evidence was assessed using the GRADE approach. These models can be used as supplementary tools in clinical practice in order to expedite the clinical decision-making process and enhance the treatment modality and clinical operation.
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Miloglu O, Guller MT, Tosun ZT. The Use of Artificial Intelligence in Dentistry Practices. Eurasian J Med 2022; 54:34-42. [PMID: 36655443 PMCID: PMC11163356 DOI: 10.5152/eurasianjmed.2022.22301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 11/30/2022] [Indexed: 01/19/2023] Open
Abstract
Artificial intelligence can be defined as "understanding human thinking and trying to develop computer processes that will produce a similar structure." Thus, it is an attempt by a programmed computer to think. According to a broader definition, artificial intelligence is a computer equipped with human intelligencespecific capacities such as acquiring information, perceiving, seeing, thinking, and making decisions. Quality demands in dental treatments have constantly been increasing in recent years. In parallel with this, using image-based methods and multimedia-supported explanation systems on the computer is becoming widespread to evaluate the available information. The use of artificial intelligence in dentistry will greatly contribute to the reduction of treatment times and the effort spent by the dentist, reduce the need for a specialist dentist, and give a new perspective to how dentistry is practiced. In this review, we aim to review the studies conducted with artificial intelligence in dentistry and to inform our dentists about the existence of this new technology.
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Affiliation(s)
- Ozkan Miloglu
- Department of Oral, Dental and Maxillofacial Radiology, Atatürk University Faculty of Dentistry, Erzurum, Turkey
| | - Mustafa Taha Guller
- Department of Dentistry Services, Oral and Dental Health Program, Binali Yıldırım University Vocational School of Health Services, , Erzincan, Turkey
| | - Zeynep Turanli Tosun
- Department of Oral, Dental and Maxillofacial Radiology, Atatürk University Faculty of Dentistry, Erzurum, Turkey
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24
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Thurzo A, Gálfiová P, Nováková ZV, Polák Š, Varga I, Strunga M, Urban R, Surovková J, Leško Ľ, Hajdúchová Z, Feranc J, Janek M, Danišovič Ľ. Fabrication and In Vitro Characterization of Novel Hydroxyapatite Scaffolds 3D Printed Using Polyvinyl Alcohol as a Thermoplastic Binder. Int J Mol Sci 2022; 23:ijms232314870. [PMID: 36499194 PMCID: PMC9736063 DOI: 10.3390/ijms232314870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
This paper presents a proof-of-concept study on the biocolonization of 3D-printed hydroxyapatite scaffolds with mesenchymal stem cells (MSCs). Three-dimensional (3D) printed biomimetic bone structure made of calcium deficient hydroxyapatite (CDHA) intended as a future bone graft was made from newly developed composite material for FDM printing. The biopolymer polyvinyl alcohol serves in this material as a thermoplastic binder for 3D molding of the printed object with a passive function and is completely removed during sintering. The study presents the material, the process of fused deposition modeling (FDM) of CDHA scaffolds, and its post-processing at three temperatures (1200, 1300, and 1400 °C), as well it evaluates the cytotoxicity and biocompatibility of scaffolds with MTT and LDH release assays after 14 days. The study also includes a morphological evaluation of cellular colonization with scanning electron microscopy (SEM) in two different filament orientations (rectilinear and gyroid). The results of the MTT assay showed that the tested material was not toxic, and cells were preserved in both orientations, with most cells present on the material fired at 1300 °C. Results of the LDH release assay showed a slight increase in LDH leakage from all samples. Visual evaluation of SEM confirmed the ideal post-processing temperature of the 3D-printed FDM framework for samples fired at 1300 °C and 1400 °C, with a porosity of 0.3 mm between filaments. In conclusion, the presented fabrication and colonization of CDHA scaffolds have great potential to be used in the tissue engineering of bones.
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Affiliation(s)
- Andrej Thurzo
- Department of Orthodontics, Regenerative and Aesthetic Dentistry, Faculty of Medicine, Comenius University, 81250 Bratislava, Slovakia
- Correspondence: (A.T.); (Ľ.D.)
| | - Paulína Gálfiová
- Institute of Histology and Embryology, Faculty of Medicine, Comenius University, 81104 Bratislava, Slovakia
| | - Zuzana Varchulová Nováková
- Institute of Medical Biology, Genetics and Clinical Genetic, Faculty of Medicine, Comenius University, 81108 Bratislava, Slovakia
- National Institute of Rheumatic Diseases, 92112 Piešťany, Slovakia
| | - Štefan Polák
- Institute of Histology and Embryology, Faculty of Medicine, Comenius University, 81104 Bratislava, Slovakia
| | - Ivan Varga
- Institute of Histology and Embryology, Faculty of Medicine, Comenius University, 81104 Bratislava, Slovakia
| | - Martin Strunga
- Department of Orthodontics, Regenerative and Aesthetic Dentistry, Faculty of Medicine, Comenius University, 81250 Bratislava, Slovakia
| | - Renáta Urban
- Department of Orthodontics, Regenerative and Aesthetic Dentistry, Faculty of Medicine, Comenius University, 81250 Bratislava, Slovakia
| | - Jana Surovková
- Department of Orthodontics, Regenerative and Aesthetic Dentistry, Faculty of Medicine, Comenius University, 81250 Bratislava, Slovakia
| | - Ľuboš Leško
- Institute of Medical Biology, Genetics and Clinical Genetic, Faculty of Medicine, Comenius University, 81108 Bratislava, Slovakia
| | - Zora Hajdúchová
- Department of Inorganic Materials, Faculty of Chemical and Food Technology, Slovak University of Technology, 81237 Bratislava, Slovakia
| | - Jozef Feranc
- Department of Plastics, Rubber and Fibres, Faculty of Chemical and Food Technology, Slovak University of Technology, 81237 Bratislava, Slovakia
| | - Marian Janek
- Department of Inorganic Materials, Faculty of Chemical and Food Technology, Slovak University of Technology, 81237 Bratislava, Slovakia
- Department of Physical and Theoretical Chemistry, Faculty of Natural Sciences, Comenius University, 84215 Bratislava, Slovakia
| | - Ľuboš Danišovič
- Institute of Medical Biology, Genetics and Clinical Genetic, Faculty of Medicine, Comenius University, 81108 Bratislava, Slovakia
- National Institute of Rheumatic Diseases, 92112 Piešťany, Slovakia
- Correspondence: (A.T.); (Ľ.D.)
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25
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Tsolakis IA, Tsolakis AI, Elshebiny T, Matthaios S, Palomo JM. Comparing a Fully Automated Cephalometric Tracing Method to a Manual Tracing Method for Orthodontic Diagnosis. J Clin Med 2022; 11:jcm11226854. [PMID: 36431331 PMCID: PMC9693212 DOI: 10.3390/jcm11226854] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/11/2022] [Accepted: 11/16/2022] [Indexed: 11/22/2022] Open
Abstract
Background: This study aims to compare an automated cephalometric analysis based on the latest deep learning method of automatically identifying cephalometric landmarks with a manual tracing method using broadly accepted cephalometric software. Methods: A total of 100 cephalometric X-rays taken using a CS8100SC cephalostat were collected from a private practice. The X-rays were taken in maximum image size (18 × 24 cm lateral image). All cephalometric X-rays were first manually traced using the Dolphin 3D Imaging program version 11.0 and then automatically, using the Artificial Intelligence CS imaging V8 software. The American Board of Orthodontics analysis and the European Board of Orthodontics analysis were used for the cephalometric measurements. This resulted in the identification of 16 cephalometric landmarks, used for 16 angular and 2 linear measurements. Results: All measurements showed great reproducibility with high intra-class reliability (>0.97). The two methods showed great agreement, with an ICC range of 0.70−0.92. Mean values of SNA, SNB, ANB, SN-MP, U1-SN, L1-NB, SNPg, ANPg, SN/ANS-PNS, SN/GoGn, U1/ANS-PNS, L1-APg, U1-NA, and L1-GoGn landmarks had no significant differences between the two methods (p > 0.0027), while the mean values of FMA, L1-MP, ANS-PNS/GoGn, and U1-L1 were statistically significantly different (p < 0.0027). Conclusions: The automatic cephalometric tracing method using CS imaging V8 software is reliable and accurate for all cephalometric measurements.
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Affiliation(s)
- Ioannis A. Tsolakis
- Department of Orthodontics, School of Dentistry, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
- Correspondence:
| | - Apostolos I. Tsolakis
- Department of Orthodontics, School of Dentistry, National and Kapodistrian, University of Athens, 157 72 Athens, Greece
- Department of Orthodontics, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Tarek Elshebiny
- Department of Orthodontics, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Stefanos Matthaios
- Department of Orthodontics, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - J. Martin Palomo
- Department of Orthodontics, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
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Artificial Intelligence as an Aid in CBCT Airway Analysis: A Systematic Review. LIFE (BASEL, SWITZERLAND) 2022; 12:life12111894. [PMID: 36431029 PMCID: PMC9696726 DOI: 10.3390/life12111894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/10/2022] [Accepted: 11/11/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND The use of artificial intelligence (AI) in health sciences is becoming increasingly popular among doctors nowadays. This study evaluated the literature regarding the use of AI for CBCT airway analysis. To our knowledge, this is the first systematic review that examines the performance of artificial intelligence in CBCT airway analysis. METHODS Electronic databases and the reference lists of the relevant research papers were searched for published and unpublished literature. Study selection, data extraction, and risk of bias evaluation were all carried out independently and twice. Finally, five articles were chosen. RESULTS The results suggested a high correlation between the automatic and manual airway measurements indicating that the airway measurements may be automatically and accurately calculated from CBCT images. CONCLUSIONS According to the present literature, automatic airway segmentation can be used for clinical purposes. The main key findings of this systematic review are that the automatic airway segmentation is accurate in the measurement of the airway and, at the same time, appears to be fast and easy to use. However, the present literature is really limited, and more studies in the future providing high-quality evidence are needed.
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27
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Ajami M, Tripathi P, Ling H, Mahdian M. Automated Detection of Cervical Carotid Artery Calcifications in Cone Beam Computed Tomographic Images Using Deep Convolutional Neural Networks. Diagnostics (Basel) 2022; 12:diagnostics12102537. [PMID: 36292226 PMCID: PMC9600983 DOI: 10.3390/diagnostics12102537] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/09/2022] [Accepted: 10/13/2022] [Indexed: 11/16/2022] Open
Abstract
The aim of this study was to determine if a convolutional neural network (CNN) can be trained to automatically detect and localize cervical carotid artery calcifications (CACs) in CBCT. A total of 56 CBCT studies (15,257 axial slices) were utilized to train, validate, and test the deep learning model. The study comprised of two steps: Step 1: Localizing axial slices that are below the C2–C3 disc space. For this step the openly available Inception V3 architecture was trained on the ImageNet dataset of real-world images, and retrained on 40 CBCT studies. Step 2: Detecting CACs in slices from step 1. For this step, two methods were implemented; Method A: Segmentation neural network trained using small patches at random coordinates of the original axial slices; Method B: Segmentation neural network trained using two larger patches at fixed coordinates of the original axial slices with an improved loss function to account for class imbalance. Our approach resulted in 94.2% sensitivity and 96.5% specificity. The mean intersection over union metric for Method A was 76.26% and Method B improved this metric to 82.51%. The proposed CNN model shows the feasibility of deep learning in the detection and localization of CAC in CBCT images.
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Affiliation(s)
- Maryam Ajami
- School of Dental Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Pavani Tripathi
- Department of Computer Sciences, Stony Brook University, Stony Brook, NY 11794, USA
| | - Haibin Ling
- Department of Computer Sciences, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mina Mahdian
- Department of Prosthodontics and Digital Technology, School of Dental Medicine, Stony Brook University, Stony Brook, NY 11794, USA
- Correspondence:
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28
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Thurzo A, Strunga M, Havlínová R, Reháková K, Urban R, Surovková J, Kurilová V. Smartphone-Based Facial Scanning as a Viable Tool for Facially Driven Orthodontics? SENSORS (BASEL, SWITZERLAND) 2022; 22:s22207752. [PMID: 36298103 PMCID: PMC9607180 DOI: 10.3390/s22207752] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/05/2022] [Accepted: 10/11/2022] [Indexed: 05/28/2023]
Abstract
The current paradigm shift in orthodontic treatment planning is based on facially driven diagnostics. This requires an affordable, convenient, and non-invasive solution for face scanning. Therefore, utilization of smartphones' TrueDepth sensors is very tempting. TrueDepth refers to front-facing cameras with a dot projector in Apple devices that provide real-time depth data in addition to visual information. There are several applications that tout themselves as accurate solutions for 3D scanning of the face in dentistry. Their clinical accuracy has been uncertain. This study focuses on evaluating the accuracy of the Bellus3D Dental Pro app, which uses Apple's TrueDepth sensor. The app reconstructs a virtual, high-resolution version of the face, which is available for download as a 3D object. In this paper, sixty TrueDepth scans of the face were compared to sixty corresponding facial surfaces segmented from CBCT. Difference maps were created for each pair and evaluated in specific facial regions. The results confirmed statistically significant differences in some facial regions with amplitudes greater than 3 mm, suggesting that current technology has limited applicability for clinical use. The clinical utilization of facial scanning for orthodontic evaluation, which does not require accuracy in the lip region below 3 mm, can be considered.
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Affiliation(s)
- Andrej Thurzo
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Martin Strunga
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Romana Havlínová
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Katarína Reháková
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Renata Urban
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Jana Surovková
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Veronika Kurilová
- Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovičova 3, 81219 Bratislava, Slovakia
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29
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Ahn S, Kim J, Jeong SC, Kim M, Kim C, Park D. Stress Distribution Analysis of Threaded Implants for Digital Dentistry. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:12674. [PMID: 36231974 PMCID: PMC9565012 DOI: 10.3390/ijerph191912674] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/25/2022] [Accepted: 09/02/2022] [Indexed: 06/16/2023]
Abstract
In this study, stability evaluation is performed through structural analysis based on digital dental implant design variables. The design variables include the implant length and thickness, cortical bone thickness, and elastic modulus of the cancellous bone. Subsequently, the stress in the external cortical bone, in which numerous nerves exist, is analyzed. Results show that stress increases as the implant length decreases. However, when the implant length is 10 mm, the stress decreases, owing to stress dispersion at the lower section of the implant. Moreover, as the implant thickness increases, the stress decreases. As the elastic modulus of the cancellous bone decreases, the stress exerted on the cancellous bone decreases; consequently, the stress exerted on the cortical bone increases. Finally, as the thickness of the cortical bone increases, the stress decreases when a vertical load is applied. However, when a load is applied in the oblique direction, the stress increases. Based on data obtained via digital radiography, which is a digital dental technology, a more precise implantation plan will be established by substituting the data via structural analysis.
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Affiliation(s)
- Seokho Ahn
- Department of Digital Manufacturing, Hanbat National University, 125 Dongseo-daero, Yuseong-gu, Daejeon 34158, Korea
| | - Jaesung Kim
- Department of Industry-Academic Convergence, Hanbat National University, 125 Dongseo-daero, Yuseong-gu, Daejeon 34158, Korea
| | - Seok Chan Jeong
- Department of e-Business, Dong-Eui University, Busanjin-gu, Busan 47340, Korea
| | - Myungil Kim
- Div. of National Supercomputing Intelligent Simulation Center, Korea Institute of Science and Technology Information 245, Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Cheolyoung Kim
- Implant Research Laboratory, Cybermed 6-26, Yuseong-daro 1205 beon-gil, Yuseong-gu, Daejeon 34104, Korea
| | - Dongki Park
- Implant Research Laboratory, Cybermed 6-26, Yuseong-daro 1205 beon-gil, Yuseong-gu, Daejeon 34104, Korea
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30
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Thurzo A, Šufliarsky B, Urbanová W, Čverha M, Strunga M, Varga I. Pierre Robin Sequence and 3D Printed Personalized Composite Appliances in Interdisciplinary Approach. Polymers (Basel) 2022; 14:polym14183858. [PMID: 36146014 PMCID: PMC9500754 DOI: 10.3390/polym14183858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/09/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
This paper introduces a complex novel concept and methodology for the creation of personalized biomedical appliances 3D-printed from certified biocompatible photopolymer resin Dental LT Clear (V2). The explained workflow includes intraoral and CT scanning, patient virtualization, digital appliance design, additive manufacturing, and clinical application with evaluation of the appliance intended for patients with cranio-facial syndromes. The presented concept defines virtual 3D fusion of intraoral optical scan and segmented CT as sufficient and accurate data defining the 3D surface of the face, intraoral and airway morphology necessary for the 3D design of complex personalized intraoral and extraoral parts of the orthopedic appliance. A central aspect of the concept is a feasible utilization of composite resin for biomedical prototyping of the sequence of marginally different appliances necessary to keep the pace with the patient rapid growth. Affordability, noninvasiveness, and practicality of the appliance update process shall be highlighted. The methodology is demonstrated on a particular case of two-year-old infant with Pierre Robin sequence. Materialization by additive manufacturing of this photopolymer provides a highly durable and resistant-to-fracture two-part appliance similar to a Tübingen palatal plate, for example. The paper concludes with the viability of the described method and material upon interdisciplinary clinical evaluation of experts from departments of orthodontics and cleft anomalies, pediatric pneumology and phthisiology, and pediatric otorhinolaryngology.
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Affiliation(s)
- Andrej Thurzo
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
- Correspondence: ; Tel.: +421-903-110-107
| | - Barbora Šufliarsky
- Department of Oral and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava and University Hospital, 81372 Bratislava, Slovakia
| | - Wanda Urbanová
- Department of Orthodontics and Cleft Anomalies, Faculty Hospital Kralovske Vinohrady, Dental Clinic 3rd Medical Faculty Charles University, 10034 Prague, Czech Republic
| | - Martin Čverha
- Clinic of Pediatric Otorhinolaryngology of the Medical Faculty Comenius University in Bratislava, 83340 Bratislava, Slovakia
| | - Martin Strunga
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
| | - Ivan Varga
- Department of Histology and Embryology, Faculty of Medicine, Comenius University in Bratislava, 81372 Bratislava, Slovakia
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31
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Fountoulaki G, Thurzo A. Change in the Constricted Airway in Patients after Clear Aligner Treatment: A Retrospective Study. Diagnostics (Basel) 2022; 12:diagnostics12092201. [PMID: 36140602 PMCID: PMC9498122 DOI: 10.3390/diagnostics12092201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
This retrospective study evaluated changes in the pharyngeal portion of the upper airway in patients with constricted and normal airways treated with clear aligners (Invisalign, Align). Additionally, we assessed the change of tongue position in the oral cavity from a lateral view. Evaluation was performed with specialized software (Invivo 6.0, Anatomage) on pretreatment and post-treatment pairs of cone beam computed tomography imaging (CBCT) data. The level of airway constriction, volume, cross-section minimal area and tongue profile were evaluated. Patients with malocclusion, with pair or initial and finishing CBCT and without significant weight change between the scans, treated with Invisalign clear aligners were distributed into two groups. Group A consisted of fifty-five patients with orthodontic malocclusion and constricted upper airway. Control group B consisted of thirty-one patients with orthodontic malocclusions without any airway constriction. In the group with airway constriction there was a statistically significant increase in volume during therapy (p < 0.001). The surface of the most constricted cross-section of the airway did not change significantly after treatment in any of the groups. The final tongue position was different from the initial position in 62.2% of all clear aligner treatments. The position of the smallest clearance of the airway in the pharynx was similar for both groups localized at the level of 2nd cervical vertebra.
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Affiliation(s)
- Georgia Fountoulaki
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
- Correspondence: (G.F.); (A.T.)
| | - Andrej Thurzo
- Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
- Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University in Bratislava, Sasinkova 4, 81272 Bratislava, Slovakia
- Correspondence: (G.F.); (A.T.)
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