超声弹性成像检测关节软骨退变的基础研究

The medical imaging technology for non-invasive detection of early osteoarthritis is the focus of the current domestic and international research. As a non-invasive method of quantifying mechanical properties of soft tissues, ultrasound elastography has been successfully used in detecting lesions and pathological changes of various tissues or organs. Because the mechanical properties of early osteoarthritis cartilage dramatically change and structural change is limited, so the current ultrasound elastography can be more accurately realize the early degeneration non-invasive detection than other method based on the change of structural. However, it cannot be directly applied to the stiff and plate cartilage due to the lack of the theory. To solve the problem, firstly, the proposed project will build and anapysis the mathematical physical modeling for the normal and early degenerative knee joint cartilage and its surrounding environment. By the introduced multi-objective optimization and evolutionary multi-objective optimization algorithm, a optimization problem from the process of the cartilage detection based on elastography will be modeled and solved with conflicting goals which were the measurable, non-invasive, energy-saving and so on. Then, the detection program will be obtained and used to determine the scope, best energy value, precision, etc. Secondly, the quasi-linear black-box model will be introduced to model the detection system which include production of shear wave, its spread in cartilage, the receiving of ultrasound, measurement and calculation. The corresponding identification method will be given to identify the system, and then the principle of the shear wave in a thin layer of cartilage tissue ultrasonic propagation will be presented. Finally, an adaptive control system for detecting the early osteoarthritis on elastography will be designed and its stability will be proved with the results of detection program and principle of the shear wave. This project aims to propose a theoretical analysis and available control procedures for the detection of early osteoarthritis, and provide an essential theory security and technical support for the animal experiments and clinical application.

利用医学影像技术进行无创检测骨关节炎是当前国内外研究焦点，超声弹性成像技术基于生物力学性质与病理相关性，利用超声技术实现无创检测软组织早期病变已获得成功。因骨关节炎早期软骨力学性质发生巨大改变而结构改变有限，所以利用该技术可以更精确地实现早期退变的无创检测，但是因为缺少必要的软骨内成像理论基础而无法用于检测较硬的薄层结构的关节软骨。为了解决这一问题，本项目将主要对正常的和发生早期退变的膝关节处软骨层及周围环境进行数学物理建模和分析，建立超声弹性成像检测软骨组织过程中需要满足可测、无创等多个相互冲突的目标的优化问题并求解，得到振源和接收器设定方案；拟采用准线性黑箱模型对整个检测过程进行系统建模和辨识，得到适用于薄层软骨组织的超声波传播规律；基于设定方案和传播规律的研究结果，设计可以在线自主调节的自适应检测控制程序。该工作的完成为超声弹性成像诊断早期骨关节炎的临床应用提供必要的理论基础和保障。

项目背景：早期诊断对于防治骨关节炎意义重大。当前骨关节炎早期诊断为临床上空白，直接利用影像法检测结构或生物标记无法达到早期无创伤诊断要求。超声弹性影像技术基于组织硬度或弹性与病理相关性，实现无创诊断软组织早期病变获得成功。该方法用于测量软骨组织的优势在于软骨退变早期结构并没有明显变化而刚度却发生数十倍改变，可以实现无创精确地诊断早期退变。但是该方法用于更硬的薄层结构的软骨(肝脏等软组织弹性模量为2–70 KPa，软骨组织大约为5MPa)时面临一些基本问题。该问题的解决为超声弹性影像诊断早期骨关节炎的临床测试提供必要的理论基础和保障。..主要研究内容与重要结果：本项目首先对骨关节炎早期阶段进行数学物理建模，量化能量扩散情况，系统的分析了剪切波在软骨模型中传播的过程，提出了新的测量剪切波传播和合适的估算弹性模量的方法，给出该技术测量精度的关键指标。计算脉冲力大小的选择对测量结果的影响，得到最佳的振源脉冲力的取值范围。采用明胶-琼脂造模模拟类似人体软骨结构，通过加载频率载荷产生剪切波产生，当发生早期软骨弹性模量改变的时候，得到剪切波传播过程以及改变。并与前部分理论模型对比，验证和完善了理论模型，确认了将超声弹性成像技术应用于骨关节炎早期检测的可行性。在此理论基础和原有检测系统的基础上，设计具有切换机制的控制检测程序。最后进一步探究组织退变的机制以及生物植入材料的匹配问题。结合信号通路和数学建模知识建立理论模型，为早期检测提供病理基础和后期保障。..关键数据及其科学意义：作为超声弹性影像临床诊断早期骨关节炎的关键性第一步，初步建立了超声弹性成像法诊断早期关节软骨退变的理论框架，确定了合理的载荷和测量方法的精度，并利用实验验证和完善了理论模型。在此基础上，设计了能够根据反馈的不同波速情来切换声源的检测器。为最终的临床应用提供理论基础和保障。..至今已发表标注本项目批准号的论文6篇，授权专利1项，参加相关学术会议4次。