Pullinger Andrew G, Seligman Donald A, John Mike T, Harkins Stephen
Division of Oral Biology and Medicine, Section of Orofacial Pain, School of Dentistry, University of California at Los Angeles, Los Angeles, 90024-1168, USA.
J Prosthet Dent. 2002 Mar;87(3):298-310. doi: 10.1067/mpr.2002.121742.
There is disagreement about the predictive value of temporomandibular joint tomographic anatomy in the diagnosis of internal derangements.
This study aimed to identify multifactorial temporomandibular hard tissue relationships that differentiate disk displacement with reduction and disk displacement without reduction from normals.
Temporomandibular joint tomograms from females diagnosed with unilateral disk displacement with (n=84) or without (n=78) reduction were compared to 42 asymptomatic normal joints with the use of 14 linear and angular measurements and 8 ratios. A validated classification tree model was tested for accuracy with sensitivity, specificity, goodness of fit, and the amount of log likelihood accounted for. The tree model was compared with a multiple logistic regression model and univariate testing.
The disk displacement with reduction tree model consisted of 3 disease and 2 normal pathways with interactions between fossa width to depth ratio, condyle position, and linear posterior joint space. This class was characterized by either a much wider- and shallower-than-average fossa shape and/or by a moderately posterior condyle position when the fossa shape was average to deeper and/or narrower. The logistic regression and univariate models also suggested wider and/or shallower fossae, as well as longer eminence length. The disk displacement without reduction tree model consisted of 2 disease pathways and 1 normal pathway. Interactions characterized this class by either a posterior to very posterior condyle position or by a much deeper than average fossa depth when the condyle position was concentric to anterior. The logistic regression model emphasized greater fossa depth and width versus normals. The tree models conservatively predicted the disease classes: Rescaled Cox and Snell R(2) 37.0%, sensitivity 70.2%, and specificity 90.5% for disk displacement with reduction; R(2) 28.8%, sensitivity 66.7%, and specificity 85.7% for disk displacement without reduction.
Within the limitations of this study, hard tissue relationships revealed by central tomogram sections were able to model notable differences between disk displacement with reduction and disk displacement without reduction versus asymptomatic normals when temporomandibular joints were examined as a multifactorial system typified by interactions of fossa width to depth proportions and condyle position. While substantial, the hard tissue predicted only part of the biology. The model could be broadened by additional factors and interactions.
颞下颌关节断层解剖在关节内紊乱诊断中的预测价值存在争议。
本研究旨在确定多因素颞下颌硬组织关系，以区分可复性盘移位、不可复性盘移位与正常情况。
将诊断为单侧可复性盘移位（n = 84）或不可复性盘移位（n = 78）的女性患者的颞下颌关节断层图像与42个无症状正常关节进行比较，采用14项线性和角度测量以及8个比率。使用灵敏度、特异性、拟合优度和对数似然值来检验经过验证的分类树模型的准确性。将该树模型与多元逻辑回归模型和单变量检验进行比较。
可复性盘移位树模型由3条疾病路径和2条正常路径组成，涉及关节窝宽度与深度比、髁突位置和关节后间隙线性之间的相互作用。该类别特征为关节窝形状比平均情况更宽且更浅，和/或当关节窝形状为平均深度到更深和/或更窄时，髁突位置为中度后位。逻辑回归和单变量模型也提示关节窝更宽和/或更浅，以及关节结节长度更长。不可复性盘移位树模型由2条疾病路径和1条正常路径组成。相互作用特征为当髁突位置为同心位到前位时，髁突位置为后位到极后位，或关节窝深度比平均情况更深得多。逻辑回归模型强调关节窝深度和宽度相对于正常情况更大。树模型保守地预测疾病类别：可复性盘移位的重新标度的考克斯和斯内尔R²为37.0%，灵敏度为70.2%，特异性为90.5%；不可复性盘移位的R²为28.8%，灵敏度为66.7%，特异性为85.7%。
在本研究的局限性内，当将颞下颌关节作为以关节窝宽度与深度比例和髁突位置的相互作用为典型特征的多因素系统进行检查时，中央断层图像切片所揭示的硬组织关系能够模拟可复性盘移位、不可复性盘移位与无症状正常情况之间的显著差异。虽然硬组织因素很重要，但仅预测了部分生物学情况。该模型可通过其他因素和相互作用进行扩展。
