Li Chenyang, Zhou Jinbo, Shi Yuchao, Ye Zelin, Zhang Chunmiao, Hou Ruilai, Li Zhongjie, You Meng
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral Medical Imaging, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Temporomandibular Joint, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Quant Imaging Med Surg. 2023 Oct 1;13(10):6446-6455. doi: 10.21037/qims-23-401. Epub 2023 Aug 3.
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.
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.
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%.
The quantitative ultrasonographic diagnostic method showed promising diagnostic efficacy. It has the potential to be used for ADD screening in future clinical practice.
超声检查已被用作评估颞下颌关节（TMJ）病变（包括关节盘前移位（ADD））的一种替代方法。然而，尚未建立一种在临床实践中可行的具体筛查或诊断方法。本研究旨在建立一种定量超声检查方法，并确定其对颞下颌关节ADD的诊断效能。
以磁共振成像（MRI）作为参考标准，将总共75个关节分为关节盘正常位置（NDP）组或ADD组。使用14MHz的L形线性阵列换能器对关节外侧腔进行纵向扫描。通过逐步逻辑回归分析研究外侧关节间隙（LJS）、上外侧关节间隙（ULJS）和下外侧关节间隙（LLJS）的宽度，以及外侧关节盘边缘（ADE）的位置，以确定ADD的显著指标并建立诊断模型。在最佳截断值处计算敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和诊断准确性。
MRI在NDP组中检测到25个关节，在ADD组中检测到50个关节。相关性分析表明，所有4个变量均与ADD相关。LJS和ULJS的受试者工作特征（ROC）曲线下面积（AUC）表现最佳，为0.939，被确定为ADD的预测指标，并随后通过逐步逻辑回归用于建立诊断模型。用于诊断ADD的双变量回归模型的最佳截断值为0.800，敏感性为82%，特异性为96%，PPV为97.6%，NPV为72.7%，准确性为86.7%。
定量超声诊断方法显示出有前景的诊断效能。它有可能在未来临床实践中用于ADD筛查。
