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Al Turkestani N, Li T, Bianchi J, Gurgel M, Prieto J, Shah H, Benavides E, Soki F, Mishina Y, Fontana M, Rao A, Zhu H, Cevidanes L. A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression. Proc Natl Acad Sci U S A 2024; 121:e2306132121. [PMID: 38346188 PMCID: PMC10895339 DOI: 10.1073/pnas.2306132121] [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: 04/17/2023] [Accepted: 01/03/2024] [Indexed: 02/15/2024] Open
Abstract
Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative disease characterized by chronic pain and impaired jaw function. The complexity of TMJ OA has hindered the development of prognostic tools, posing a significant challenge in timely, patient-specific management. Addressing this gap, our research employs a comprehensive, multidimensional approach to advance TMJ OA prognostication. We conducted a prospective study with 106 subjects, 74 of whom were followed up after 2 to 3 y of conservative treatment. Central to our methodology is the development of an innovative, open-source predictive modeling framework, the Ensemble via Hierarchical Predictions through Nested cross-validation tool (EHPN). This framework synergistically integrates 18 feature selection, statistical, and machine learning methods to yield an accuracy of 0.87, with an area under the ROC curve of 0.72 and an F1 score of 0.82. Our study, beyond technical advancements, emphasizes the global impact of TMJ OA, recognizing its unique demographic occurrence. We highlight key factors influencing TMJ OA progression. Using SHAP analysis, we identified personalized prognostic predictors: lower values of headache, lower back pain, restless sleep, condyle high gray level-GL-run emphasis, articular fossa GL nonuniformity, and long-run low GL emphasis; and higher values of superior joint space, mouth opening, saliva Vascular-endothelium-growth-factor, Matrix-metalloproteinase-7, serum Epithelial-neutrophil-activating-peptide, and age indicate recovery likelihood. Our multidimensional and multimodal EHPN tool enhances clinicians' decision-making, offering a transformative translational infrastructure. The EHPN model stands as a significant contribution to precision medicine, offering a paradigm shift in the management of temporomandibular disorders and potentially influencing broader applications in personalized healthcare.
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Affiliation(s)
- Najla Al Turkestani
- Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah21589, Saudi Arabia
- Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Tengfei Li
- Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC27599
| | - Jonas Bianchi
- Department of Orthodontics, University of the Pacific, Arthur A. Dugoni School of Dentistry, San Francisco, CA94103
| | - Marcela Gurgel
- Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Juan Prieto
- Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC27599
| | - Hina Shah
- Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC27599
| | - Erika Benavides
- Department of Periodontics & Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Fabiana Soki
- Department of Periodontics & Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Yuji Mishina
- Department of Biologic and Materials Sciences & Prosthodontics, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Margherita Fontana
- Department of Cariology, Restorative Sciences and Endodontics, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Arvind Rao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI48109
- Department of Computational Medicine & Bioinformatics, School of Dentistry, University of Michigan, Ann Arbor, MI48109
| | - Hongtu Zhu
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC27599
| | - Lucia Cevidanes
- Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI48109
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Xu L, Chen J, Qiu K, Yang F, Wu W. Artificial intelligence for detecting temporomandibular joint osteoarthritis using radiographic image data: A systematic review and meta-analysis of diagnostic test accuracy. PLoS One 2023; 18:e0288631. [PMID: 37450501 PMCID: PMC10348514 DOI: 10.1371/journal.pone.0288631] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 07/02/2023] [Indexed: 07/18/2023] Open
Abstract
In this review, we assessed the diagnostic efficiency of artificial intelligence (AI) models in detecting temporomandibular joint osteoarthritis (TMJOA) using radiographic imaging data. Based upon the PRISMA guidelines, a systematic review of studies published between January 2010 and January 2023 was conducted using PubMed, Web of Science, Scopus, and Embase. Articles on the accuracy of AI to detect TMJOA or degenerative changes by radiographic imaging were selected. The characteristics and diagnostic information of each article were extracted. The quality of studies was assessed by the QUADAS-2 tool. Pooled data for sensitivity, specificity, and summary receiver operating characteristic curve (SROC) were calculated. Of 513 records identified through a database search, six met the inclusion criteria and were collected. The pooled sensitivity, specificity, and area under the curve (AUC) were 80%, 90%, and 92%, respectively. Substantial heterogeneity between AI models mainly arose from imaging modality, ethnicity, sex, techniques of AI, and sample size. This article confirmed AI models have enormous potential for diagnosing TMJOA automatically through radiographic imaging. Therefore, AI models appear to have enormous potential to diagnose TMJOA automatically using radiographic images. However, further studies are needed to evaluate AI more thoroughly.
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Affiliation(s)
- Liang Xu
- The School of Stomatology, Fujian Medical University, Fuzhou, Fujian, China
- Department of Stomatology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Jiang Chen
- The School of Stomatology, Fujian Medical University, Fuzhou, Fujian, China
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, Fujian, China
| | - Kaixi Qiu
- Fuzhou No. 1 Hospital Affiliated with Fujian Medical University, Fuzhou, Fujian, China
| | - Feng Yang
- School and Hospital of Stomatology, Fujian Medical University, Fuzhou, Fujian, China
| | - Weiliang Wu
- The School of Stomatology, Fujian Medical University, Fuzhou, Fujian, China
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Mizuhashi F, Ogura I, Mizuhashi R, Watarai Y, Oohashi M, Suzuki T, Saegusa H. Examination for the Factors Involving to Joint Effusion in Patients with Temporomandibular Disorders Using Magnetic Resonance Imaging. J Imaging 2023; 9:jimaging9050101. [PMID: 37233320 DOI: 10.3390/jimaging9050101] [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: 01/14/2023] [Revised: 03/20/2023] [Accepted: 03/23/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND This study investigated the factors involving joint effusion in patients with temporomandibular disorders. METHODS The magnetic resonance images of 131 temporomandibular joints (TMJs) of patients with temporomandibular disorders were evaluated. Gender, age, disease classification, duration of manifestation, muscle pain, TMJ pain, jaw opening disturbance, disc displacement with and without reduction, deformation of the articular disc, deformation of bone, and joint effusion were investigated. Differences in the appearance of symptoms and observations were evaluated using cross-tabulation. The differences in the amounts of synovial fluid in joint effusion vs. duration of manifestation were analyzed using the Kruskal-Wallis test. Multiple logistic regression analysis was performed to analyze the factors contributing to joint effusion. RESULTS Manifestation duration was significantly longer when joint effusion was not recognized (p < 0.05). Arthralgia and deformation of the articular disc were related to a high risk of joint effusion (p < 0.05). CONCLUSIONS The results of this study suggest that joint effusion recognized in magnetic resonance imaging was easily observed when the manifestation duration was short, and arthralgia and deformation of the articular disc were related to a higher risk of joint effusion.
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Affiliation(s)
- Fumi Mizuhashi
- Department of Removable Prosthodontics, The Nippon Dental University School of Life Dentistry at Niigata, Niigata 951-8580, Japan
| | - Ichiro Ogura
- Department of Oral and Maxillofacial Radiology, The Nippon Dental University School of Life Dentistry at Niigata, Niigata 951-8580, Japan
| | - Ryo Mizuhashi
- Comprehensive Dental Care, The Nippon Dental University Niigata Hospital, Niigata 951-1500, Japan
| | - Yuko Watarai
- Department of Removable Prosthodontics, The Nippon Dental University School of Life Dentistry at Niigata, Niigata 951-8580, Japan
| | - Makoto Oohashi
- Department of Dental Anesthesia and General Health Management, The Nippon Dental University School of Life Dentistry at Niigata, Niigata 951-8580, Japan
| | - Tatsuhiro Suzuki
- Functional Occlusal Treatment, The Nippon Dental University Graduate School of Life Dentistry at Niigata, Niigata 951-8580, Japan
| | - Hisato Saegusa
- Comprehensive Dental Care, The Nippon Dental University Niigata Hospital, Niigata 951-1500, Japan
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Mizuhashi F, Ogura I, Watarai Y, Suzuki T, Mizuhashi R, Oohashi M, Saegusa H. Examination for the factors contribute to joint effusion in patients with internal derangement on temporomandibular joint disorder. JOURNAL OF ORAL AND MAXILLOFACIAL RADIOLOGY 2022. [DOI: 10.4103/jomr.jomr_17_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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Cong N, Wang N, Huang S, Cheng T, Yan X. Diagnostic significance of magnetic resonance imaging in distinguishing temporomandibular disorders: a retrospective chart review. BMC Oral Health 2021; 21:481. [PMID: 34583663 PMCID: PMC8479910 DOI: 10.1186/s12903-021-01826-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 09/13/2021] [Indexed: 11/29/2022] Open
Abstract
Background This study was to evaluate the diagnostic significance of Magnetic Resonance Imaging (MRI) in distinguishing temporomandibular disorders (TMD). Methods A total of 684 patients with TMD were included in the study. Diagnosis for TMD was conducted according to the international criteria. Two professional radiologists were selected for professional training, and the Kappa values were compared for the diagnosis results to determine the consistency of the diagnosis. Then MRI images of these 684 patients were analyzed and the diagnosis results were obtained. Results MRI can be used for the diagnosis of TMD. There were significantly more females (518 cases) than males (166 cases) with TMD; Disc displacement with/without reduction is more common in the youth group, with the majority aged 20–30 years. The highest incidence of temporomandibular joint osteoarthrosis is in the 60-year-old age group, followed by the 70-year-old age group. Conclusions Bilateral temporomandibular joint MRI can clearly show their changes; there are significantly more female with TMD than male; osteoarthritis has a significant correlation with age.
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Affiliation(s)
- Nuonuo Cong
- Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, No. 95, Yongan Road, Xicheng District, Beijing, 100050, China
| | - Ning Wang
- Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, No. 95, Yongan Road, Xicheng District, Beijing, 100050, China
| | - Shengyuan Huang
- Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, No. 95, Yongan Road, Xicheng District, Beijing, 100050, China
| | - Taiqi Cheng
- Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, No. 95, Yongan Road, Xicheng District, Beijing, 100050, China
| | - Xing Yan
- Department of Stomatology, Beijing Friendship Hospital, Capital Medical University, No. 95, Yongan Road, Xicheng District, Beijing, 100050, China.
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Mizuhashi F, Ogura I, Sugawara Y, Oohashi M, Mizuhashi R, Saegusa H. Analysis of related factors to internal derangement in temporomandibular joint dysfunction patients using magnetic resonance imaging. JOURNAL OF ORAL AND MAXILLOFACIAL RADIOLOGY 2021. [DOI: 10.4103/jomr.jomr_11_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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