Rapid Three-dimensional Simultaneous Knee Multi-Relaxation Mapping

快速三维同步膝关节多重松弛映射

• 批准号: 10501420
• 负责人: Fang Liu
• 金额: $ 42.77万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501420
• 关键词: 3-Dimensional; Affect; Biochemical; Cartilage; Clinical; Clinical Research; Collagen; Collagen Fiber; Complex; Degenerative polyarthritis; Disease; Disease model; Extracellular Matrix; Face; Histologic; Human; Image; Imaging Techniques; Joints; Knee; Knee Osteoarthritis; Magnetic Resonance; Magnetic Resonance Imaging; Methods; Noise; Patients; Physics; Plant Roots; Proteoglycan; Relaxation; Reporting; Resolution; Role; Scanning; Signal Transduction; Slice; Staging; Structure; Techniques; Thick; Three-Dimensional Imaging; Time; Tissue Model; Tissues; cartilage degradation; clinical application; clinically translatable; cost; deep learning; human tissue; image reconstruction; imaging approach; imaging biomarker; imaging capabilities; learning strategy; macromolecule; magnetic resonance imaging biomarker; mechanical properties; non-invasive imaging; non-invasive monitor; novel; reconstruction; research study; supervised learning

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.

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，其特征是 软骨外基质中胶原蛋白纤维网络的蛋白聚糖含量和破坏。磁的 共振（MR）成像已用于量化由于 OA的变性。在所有MR技术中，Leasation先生是最受欢迎的，并且可以提供无创的， 高分辨率，三维成像生物标志物，这对于量化人来说非常有价值 组织。已经发现软骨自旋旋转（T2）松弛时间对胶原蛋白的变化很敏感 与早期软骨变性有关的超微结构。旋转框架中的软骨自旋晶格松弛 （T1ρ）对大分子的浓度变化敏感，并且与蛋白聚糖损失相关 OA。据报道，自旋晶格松弛时间（T1）时间的作用与机械性能相关 软骨的变化，对组织的进行性损害敏感。而每个放松参数 提供软骨的有限和互补信息，成像T1，T2和T1ρ的能力一起 将提供一组全面的成像生物标志物，以协同访问大分子 内容及其软骨的超微结构。但是，由于扫描时间很长，图像采集效率差， 以及复杂的图像重建和组织建模，同时进行多余的映射非常 因此，在OA研究中，具有挑战性的挑战仍然不发达。该提议将提供三个快速的3- 通过发育的尺寸绘制膝关节映射T1，T2和T1ρ的尺寸同时进行多余的成像 一种新型的成像序列和重建方法（AIM 1）。这种新技术将利用有效的三个 尺寸的黄金角度图像获取，并将通过一种新颖的深度学习方法加速 利用自我监督的学习和MR物理学的组织建模。派生的MR成像 生物标志物将与软骨组织学，生化和机械性能相关，这将 为解释临床研究结果创建基础（AIM 2）。使用优化和 将对具有不同程度的膝盖OA的患者进行加速成像技术，并确定 多释放映射的效用，效率和总体临床价值的临床证据 OA（目标3）。我们提出的新方法将植根于开发新型快速图像采集， 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为非侵入性提供新的快速成像技术 通过多种 放松评估。它将针对OA和其他疾病提供广泛的临床应用。