Non invasive measurements of muscle microstructure assessed by diffusion tensor imaging

骨骼肌在生物学中阐明了结构-功能关系。肌节的组织结构 分层排序，形成长收缩细胞，捆绑在细胞外基质中，形成更大的纤维束， 最后是整个肌肉。结构和功能之间的紧密关系使肌肉性能 (and疾病）从其微观结构推断。例如，纤维面积与等长力直接相关 生产肌肉。随着损伤，肌纤维面积（大小）、纤维化（积聚） 观察到细胞外基质（细胞外基质）、膜损伤（渗透性）和炎症（水肿）， 肌肉功能肌肉活检，其次是显微镜检查的组织（组织学），是黄金 诊断和监测肌肉健康和疾病的标准。这种工具是侵入性的，需要大口径 在无菌条件下移除针头和组织，这使得它痛苦且昂贵。因此，活检不是 有助于连续监测肌肉健康。它也是半定量的，通常很难外推到 这限制了它的科学和临床价值。由于这些原因，需要非侵入性的 评估肌肉微观结构，这将有助于定量检查肌肉损伤超过 时间磁共振成像（MRI）已被用于非侵入性量化的变化，体积，脂肪 分布和肌肉含水量。扩散张量成像（DTI）是MRI的一种， 水的各向异性扩散，与组织微结构有关，但往往产生非特异性变化 无论受伤或疾病状态如何。这种缺乏特异性的关键原因是， 微观结构和扩散之间的关系还没有被严格地研究，也没有被仔细地校准。 为了解决这一知识差距，本提案的目的是比较肌肉微观结构和MRI 肌肉的扩散特性在新的和严格控制的计算机模拟，精密工程 幻影和肌肉损伤和疾病的动物模型。我们的中心假设是DT-MRI可以 当使用适当的脉冲序列解偶联时， 复杂的病理学目标1将使用基于计算机的肌肉结构和生物化学模拟， 仔细了解扩散与多种肌肉显微结构变化的关系。目标#2将使用3D 精确设计的模型，将扩散与真实世界DT-MRI实验中的肌肉结构联系起来。这些 这些实验将被整合到最终的体内实验组（目标#3）中，其被设计为测试 DT-MRI在肌肉萎缩时分离复杂微结构变化的准确性， 炎症和变性。这些实验将阐明研究不足的关系， 微结构和肌肉扩散。长期目标是连续量化肌肉微观结构， 侵入性地这种方法是创新的，因为它结合了最先进的成像，模拟，纳米纤维， 和形态学方法来产生临床上有意义的测量工具。

Skeletal muscle exemplifies structure-function relationships in biology. The organization of sarcomeres follow hierarchical ordering to form long contractile cells, bundled in extra-cellular matrix, to form larger fascicles and ultimately whole muscles. The tight relationship between structure and function allows muscle performance (and disease) to be inferred from its microstructure. For example, fiber area is directly related to isometric force production in muscle. With injury, microstructural changes in muscle fiber area (size), fibrosis (accumulation of extracellular matrix), membrane damage (permeability), and inflammation (edema) are observed, and impair muscle function. Muscle biopsy, followed by microscopic examination of the tissue (histology), is the gold standard to diagnose and monitor muscle health and disease. This tool is invasive, requiring a large bore needle and tissue removal under sterile conditions, which makes it painful and costly. Therefore, biopsy is not conducive to serial monitoring of muscle health. It is also semi-quantitative, and often difficult to extrapolate to the entire muscle, limiting its scientific and clinical value. For these reasons, there is a need for noninvasive assessment of muscle microstructure, which would facilitate the quantitative examination of muscle injury over time. Magnetic resonance imaging (MRI) has been used to noninvasively quantify changes in volume, fat distribution, and water content in muscle. Diffusion tensor imaging (DTI) is a version of MRI that measures anisotropic diffusion of water, which is related to tissue microstructure, but tends to yield non-specific changes regardless of the injury or disease state. The key reason for this lack of specificity is that the explicit relationships between microstructure and diffusion have not been rigorously studied, nor carefully calibrated. To address this gap in knowledge, the purpose of this proposal is to compare muscle microstructure and MRI diffusion properties of muscle in novel and tightly controlled computer simulations, precision engineered phantoms, and animal models of muscle injury and disease. Our central hypothesis is that DT-MRI can be directly related to muscle microstructural changes, when appropriate pulse sequences are used to uncouple complex pathology. Aim #1 will use computer-based simulations of muscle structure and biochemistry to carefully understand how diffusion is related to multiple muscle microstructural changes. Aim #2 will utilize 3D precision-engineered models to relate diffusion to muscle structure in real-world DT-MRI experiments. These experiments will be integrated into a final in vivo set of experiments (Aim #3), which are designed to test the accuracy of DT-MRI to uncouple complex microstructural changes in the presence of muscle atrophy, inflammation, and degeneration. These experiments will elucidate the understudied relationships between microstructure and diffusion in muscle. The long-term goal is to serially quantify muscle microstructure non- invasively. This approach is innovative in that it combines state-of-the art imaging, simulation, nanofabrication, and morphology methods to generate a clinically meaningful measurement tool.