Background: Symptoms of osteoarthritis (OA) in the temporomandibular joint (TMJ) may vary and possible causes should be further explored, such as prevalence and characteristics of imaging features.
Objectives: Investigate prevalence, gender differences and characteristics of imaging signs of TMJ-OA by cone beam computed tomography (CBCT) in a population-based sample of 65-year-old Oslo citizens.
Materials And Methods: 159 (86 women, 73 men) individuals randomly recruited from a cohort of 460 Oslo citizens were examined with CBCT. The TMJs were categorised as with imaging signs of OA, no OA or indeterminate for OA.
Results: CBCT signs of TMJ-OA were found in 35% of the 159 participants: 47% of the women and 22% of the men. CBCT signs of TMJ-OA were unilateral in two-thirds of the TMJs and characterised by articular surface flattening and condylar osteophytes. In almost all joints with bone erosive findings, bone productive findings were also found. Participants with and without CBCT signs of TMJ-OA showed no significant difference in TMD pain screener. Fourteen of the 159 participants (9%) had pain-related TMD and 12 (8%) had been in contact with health care services due to TMD.
Conclusions: CBCT signs of TMJ-OA was common in this study group of 65-year-old Oslo citizens, found in every second woman and every fifth man. Articular surface flattening and bone productive changes, in particular condylar osteophytes, were the most frequent imaging features. Despite the high frequency of CBCT signs of TMJ-OA, few of the participants had pain-related TMD.
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http://dx.doi.org/10.1111/joor.13547 | DOI Listing |
Equine Vet J
January 2025
Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Warsaw, Poland.
Background: The temporomandibular joint (TMJ) is a unique joint that enables mandibular movement. Temporomandibular diseases (TMDs) impair joint function, leading to more or less specific clinical signs.
Objectives: To compile and disseminate clinical data and research findings from existing publications on equine TMD.
Int J Oral Sci
January 2025
Department of Stomatology, Tangdu Hospital & State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, School of Stomatology, The Fourth Military Medical University, Xi'an, China.
Temporomandibular joint osteoarthritis (TMJ-OA) is a common disease often accompanied by pain, seriously affecting physical and mental health of patients. Abnormal innervation at the osteochondral junction has been considered as a predominant origin of arthralgia, while the specific mechanism mediating pain remains unclear. To investigate the underlying mechanism of TMJ-OA pain, an abnormal joint loading model was used to induce TMJ-OA pain.
View Article and Find Full Text PDFComb Chem High Throughput Screen
January 2025
Department of Orthodontics II, Affiliated Stomatological Hospital of Zunyi Medical University, Zunyi 56300, China.
Osteoarthritis, particularly temporomandibular joint (TMJ) osteoarthritis (OA), poses significant challenges in diagnosis and treatment. Recent studies suggest that nanomaterials hold considerable promise in treating TMJ-OA, showing validated efficacy in animal models. However, further research is required to ensure their long-term safety within the TMJ-OA environment.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Oral and Maxillofacial Surgery, Yonsei University College of Dentistry, Gangnam Severance Hospital, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
This study aimed to investigate the cutoff values of standardized uptake values (SUVs) and their accuracy using single-photon emission computed tomography-computed tomography (SPECT-CT) for temporomandibular joint (TMJ) osteoarthritis (OA) based on magnetic resonance imaging (MRI) and clinical examination. We included 106 joints of 53 patients with TMJ OA. SUVmax and SUVpeak of each TMJ was measured.
View Article and Find Full Text PDFJ Stomatol Oral Maxillofac Surg
October 2024
Oral and Maxillofacial Surgery Department, Faculty of Dentistry, Alexandria University, Alexandria, Egypt. Electronic address:
Objective: The purpose of this study was to investigate the diagnostic performance of a neural network Artificial Intelligence model for the radiographic confirmation of Temporomandibular Joint Osteoarthritis in reference to an experienced radiologist.
Materials And Methods: The diagnostic performance of an AI model in identifying radiographic features in patients with TMJ-OA was evaluated in a diagnostic accuracy cohort study. Adult patients elected for radiographic examination by the Diagnostic Criteria for Temporomandibular Disorders decision tree were included.
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