颞下颌关节骨性结构的精巧吻合与关节局部微环境稳态是口颌系统正常行使功能的基础。基于医学影像大数据挖掘技术和申请人研发的下颌三维运动分析系统，本研究通过收集正常志愿者与骨关节病患者的CBCT数据，采用Otsu及区域生长混合分割算法进行关节骨面提取，并利用三维曲率计算方法完成骨面形态分析并建立关节匹配参数模型；通过下颌运动捕捉还原技术及有限元模拟验证关节匹配参数与力学变化的关系；采用关节液代谢组学筛选不同匹配参数及应力条件下颞下颌关节微环境的差异蛋白标志物，探索不同匹配程度下髁突软骨基质合成和代谢失调的阈值。本研究建立颞下颌关节骨性结构匹配参数模型，结合关节微环境代谢产物阐释骨关节病始发机理，有望揭示颞下颌关节骨关节病的发生发展机制，为疾病诊断和治疗提供新思路。

The precise congruity of temporomandibular joint (TMJ) bony structures and the stability of local synovial fluid micro-environment are the basis for our oral system to function normally. Based on medical imaging big data mining technology and the three-dimensional(3D) mandibular movement analysis system we researched and developed, CBCT images of volunteers and patients with osteoarthrosis are gathered and used for segmentation of joint surface based on Statistical Region Growing and Otsu Thresholding, so as to establish the TMJ matching parameter model using 3D curvature analysis methods; then mandibular movement capture and revivification technique combined with 3D Finite Element Simulation are performed to validate the relation between TMJ matching parameters and dynamic characteristic; we use metabolomics methods to screen differential protein expression markers in synovial fluid micro-environment at different TMJ matching parameter and dynamic status, and explore the match threshold of imbalance of synthesis and degradation of the cartilage matrix. This project intends to establish a TMJ dynamic matching parameter model, combined with the metabolic characteristics of synovial fluid micro-environment, to clarify the pathogenic mechanism of osteoarthrosis, and provide new insights for the diagnosis and treatment of osteoarthrosis.