Rapid Three-dimensional Simultaneous Knee Multi-Relaxation Mapping

项目摘要 骨关节炎（OA）是影响人类关节的最普遍的疾病之一，其特征在于骨关节炎（OA）引起的骨关节炎（OA）减少。 蛋白多糖含量和软骨细胞外基质中胶原纤维网络的破坏。磁 磁共振（MR）成像已被用于量化软骨组成和微观结构的变化， OA的退化。在所有MR技术中，MR弛豫测量是最受欢迎的，可以提供无创， 高分辨率，三维成像生物标志物，这将是非常有价值的量化人类 组织中已经发现，软骨自旋-自旋（T2）弛豫时间对胶原的变化敏感 超微结构与早期软骨退变有关。旋转坐标系中的Carnival自旋-晶格弛豫 (T1ρ）对大分子的浓度变化敏感，并与蛋白多糖的损失相关， OA。自旋-晶格弛豫（T1）时间的作用也被报道与机械性能相关 软骨的变化，并对组织的进行性损伤敏感。当每个弛豫参数 提供了软骨的有限和互补信息，同时成像T1、T2和T1ρ的能力 将提供一组综合的成像生物标志物，用于协同地访问大分子 软骨组织的含量及其超微结构。然而，由于扫描时间长，图像采集效率差， 和复杂的图像重建和组织建模，同时多松弛映射是非常 因此，在OA研究中仍然缺乏挑战性。这一举措将为快速三... 三维同步多松弛成像，用于通过显影映射膝关节的T1、T2和T1ρ 一种新的成像序列和重建方法（目标1）。这项新技术将利用有效的三- 三维黄金角图像采集，并将通过一种新的深度学习方法来加速， 利用自我监督学习和MR物理信息组织建模。派生的MR成像 生物标志物将与软骨组织学、生物化学和机械特性相关， 为临床研究结果的解释奠定基础（目标2）。使用优化的和 将对不同程度的膝关节OA患者进行加速成像技术， 临床证据表明，多松弛标测在检测和 OA分期（目标3）。我们提出的新方法将源于开发新的快速图像采集， 结合先进的深度学习重建和自动处理，所有这些都是由 我们的团队该提案的成功完成将提供一种新的快速成像技术， 通过多种方法监测组织成分和超微结构的疾病相关和治疗相关变化， 放松评估。它将在OA和其他疾病中具有广泛的临床应用。

PROJECT SUMMARY Osteoarthritis (OA) is one of the most prevalent diseases affecting human joints, characterized by decreased proteoglycan content and disruption of the collagen fiber network in the cartilage extracellular matrix. Magnetic resonance (MR) imaging has been used to quantify cartilage composition and microstructure changes due to degeneration in OA. Among all MR techniques, MR relaxometry is the most popular and can provide non-invasive, high-resolution, three-dimensional imaging biomarkers, which would be highly valuable in quantifying human tissues. Cartilage spin-spin (T2) relaxation time has been found to be sensitive to the changes of collagen ultrastructure associated with early cartilage degeneration. Cartilage spin-lattice relaxation in the rotating frame (T1ρ) is sensitive to the concentration changes of macromolecules and is correlated with proteoglycan loss in OA. The role of spin-lattice relaxation (T1) time has also been reported to correlate with the mechanical property changes of cartilage and is sensitive to progressive damage of the tissue. While each relaxation parameter provides limited and complementary information of cartilage, the capability of imaging T1, T2 and T1ρ together would provide a set of comprehensive imaging biomarkers for synergistically accessing the macromolecular content and their ultrastructure of cartilage. However, due to long scan time, poor image acquisition efficiency, and complex image reconstruction and tissue modeling, simultaneous multi-relaxation mapping is very challenging thus remains underdeveloped in OA research studies. This proposal will provide rapid three- dimensional simultaneous multi-relaxation imaging for mapping T1, T2, and T1ρ of the knee through developing a novel imaging sequence and reconstruction method (Aim 1). This new technique will leverage efficient three- dimensional golden-angle image acquisition and will be accelerated through a novel deep learning method that leverages self-supervised learning and MR physics-informed tissue modeling. The derived MR imaging biomarkers will be correlated with cartilage histological, biochemical, and mechanical properties, which will create a basis for interpretation of the clinical study results (Aim 2). A pilot clinical study using the optimized and accelerated imaging technique will be performed on patients with varying degrees of knee OA, establishing the clinical evidence of the utility, efficiency, and overall clinical value of multi-relaxation mapping on detecting and staging OA (Aim 3). Our proposed new methods will root from developing novel rapid image acquisition, combined with advanced deep learning reconstruction and automatic processing, all of which are pioneered by our team. Successful completion of the proposal will offer a new rapid imaging technique to non-invasively monitor disease-related and treatment-related changes in tissue composition and ultra-structure through multi- relaxation assessment. It will have broad clinical applications for OA and other diseases.