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Diagnostic efficacy of quantitative ultrasonography for anterior disc displacement of the temporomandibular joint

BACKGROUND: Ultrasonography has been applied as an alternative method in the assessment of temporomandibular joint (TMJ) pathology including anterior disc displacement (ADD). However, a concrete screening or diagnostic method which is feasible in clinical practice has not yet been established. The s...

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Detalles Bibliográficos
Autores principales: Li, Chenyang, Zhou, Jinbo, Shi, Yuchao, Ye, Zelin, Zhang, Chunmiao, Hou, Ruilai, Li, Zhongjie, You, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10585577/
https://www.ncbi.nlm.nih.gov/pubmed/37869327
http://dx.doi.org/10.21037/qims-23-401
Descripción
Sumario:BACKGROUND: Ultrasonography has been applied as an alternative method in the assessment of temporomandibular joint (TMJ) pathology including anterior disc displacement (ADD). However, a concrete screening or diagnostic method which is feasible in clinical practice has not yet been established. The study aimed to establish a quantitative ultrasonographic method and determine its diagnostic efficacy for ADD of the TMJ. METHODS: A total of 75 joints were allocated to either the normal disc position (NDP) group or the ADD group using magnetic resonance imaging (MRI) as the reference standard. Longitudinal scans of the lateral articular compartment were obtained by a 14-MHz L-shaped linear array transducer. The width of the lateral joint space (LJS), the upper lateral joint space (ULJS), and the lower lateral joint space (LLJS), as well as the position of the lateral articular disc edge (ADE), were investigated by stepwise logistic regression analysis to identify significant indicators of ADD and to build a diagnostic model. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were computed at the optimal cut-off value. RESULTS: MRI detected 25 joints in the NDP group and 50 joints in the ADD group. Correlation analysis indicated that all 4 variables were associated with ADD. With the best performance of the area under the receiver operating characteristic (ROC) curve (AUC) of 0.939, LJS and ULJS were identified as predictors of ADD and subsequently adopted to build a diagnostic model by stepwise logistic regression. The optimal cut-off value of the 2-variable regression model for diagnosing ADD was 0.800, with a sensitivity of 82%, specificity of 96%, PPV of 97.6%, NPV of 72.7%, and an accuracy of 86.7%. CONCLUSIONS: The quantitative ultrasonographic diagnostic method showed promising diagnostic efficacy. It has the potential to be used for ADD screening in future clinical practice.