基于多模医学影像的人体骨骼肌神经生物力学协调机理及其临床应用研究

The skeletal muscle is the one of the most important part of the human musculoskeletal system. All of the human movements are determined by its biomechanical behavior and coordination pattern. The simulation and modeling of skeletal muscle is very important for many human musculoskeletal system diseases. For a long time, the skeletal muscle was modeled by the biomechanical lines which connected the origin point and end point of the muscle fascicle. However, there are some disadvantages which made it hard to explore the biomechanical behavior and coordination pattern of human skeletal muscle in movements. Based on the China digital human project, We reconstructed the three-dimension simulating models of the whole human skeletal system. Inspired by the China mechanical virtual human research, the project put forward the idea of a novel skeletal muscle modeling method based on the medical images, for the research of the biomechanical behavior and coordination pattern of human skeletal muscle in movement, and providing the theory basis for the musculoskeletal system related disease treatment and research. The project is expected to propose a novel image segmentation algorithm and three-dimension reconstruction algorithm. A new skeletal muscle modeling method will be developed. The biomechanical behavior and coordiantion pattern will be illustrated, and the mechanism of the skeletal muscle force will be further revealed. All in all, the project has a very important scientific significance, and also has great practical value and social economic significance for the clinical treatment of applications.

骨骼肌是人体的重要组成部分，肌群协调发力产生了各种运动，骨骼肌神经生物力学协调机理研究对于许多疾病诊疗和临床应用具有重要意义。长期以来，学科界通过连接肌纤维起止点的直线进行建模，用以研究骨骼肌神经生物力学现象。然而，该方法仿真度低，无法获取运动中骨骼肌神经生物力的大小与协调机理。我们前期在中国数字人工程基础上，建立了人体骨骼系统仿真模型。受此启发，本项目提出了基于多模医学影像配准、融合及三维快速重建技术，研究人体骨骼肌在运动中的神经生物力学行为与协调机理的思路，探索建立人体深层骨骼肌非侵入式在体肌力测量方法，为相关疾病诊疗及临床应用提供依据。本项目预期将建立一种针对骨骼肌的多模医学影像重建算法，形成一种非侵入式在体肌力测量方法，阐明人体运动中骨骼肌神经生物力学规律及协调机理，进一步揭示深层骨骼肌力神经调控机制及对运动功能的影响，丰富生物医学建模理论，具有十分重要的科学意义和临床应用价值。

本项目基于多模医学影像数据，完成了人体骨骼肌神经生物力学协调机理方面的探索研究，积累了一批实验数据，通过数据处理及分析，总结获取了人体骨骼肌神经生物力学协调规律，并对其在临床中的应用进行了研究。骨骼肌是人体的重要组成部分，肌群协调发力产生了各种运动，骨骼肌神经生物力学协调机理研究对于许多疾病诊疗和临床应用具有重要意义。长期以来，学科界通过连接肌纤维起止点的直线进行建模，用以研究骨骼肌神经生物力学现象。然而，该方法仿真度低，无法获取运动中骨骼肌神经生物力的大小与协调机理。本项目建立了基于多模医学影像配准、融合及三维快速重建技术，提出了研究人体骨骼肌在运动中的神经生物力学行为与协调机理的新思路，探索建立人体深层骨骼肌非侵入式在体肌力测量方法，为相关疾病诊疗及临床应用提供依据。经过本项目的研究，建立了一种针对骨骼肌的多模医学影像重建算法，形成了一种非侵入式在体肌力测量方法。项目发表论文5篇，出版译著1部，申请发明专利2项，软件著作权1项。本项目按计划完成了相应的研究任务，取得了预期的研究成果。经过本项目的研究，进一步阐明了人体运动中骨骼肌神经生物力学规律及协调机理，进一步揭示了深层骨骼肌力神经调控机制及对运动功能的影响，丰富了生物医学建模理论，具有一定的科学意义和临床应用价值。