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: 10662544
• 负责人: Fang Liu
• 金额: $ 38.87万
• 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/10662544
• 关键词: 3-Dimensional; Acceleration; 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; Maps; Methods; Noise; Patients; Physics; Proteoglycan; Relaxation; Reporting; Resolution; Role; Rotation; Scanning; Signal Transduction; Slice; Staging; Structure; Techniques; Thick; Three-Dimensional Imaging; Time; Tissue Model; Tissues; cartilage degradation; clinical application; clinical translation; cost; deep learning; human tissue; image reconstruction; imaging approach; imaging biomarker; imaging capabilities; learning strategy; macromolecule; magnetic resonance imaging biomarker; mechanical properties; millimeter; 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.

项目总结 骨性关节炎(OA)是影响人类关节的最常见疾病之一，其特点是 软骨细胞外基质中蛋白多糖的含量和胶原纤维网络的破坏。磁性 磁共振成像已被用来量化软骨成分和微结构的变化，由于 骨性关节炎的退行性变。在所有的MR技术中，MR弛豫测量是最流行的，并且可以提供无创的， 高分辨率、三维成像生物标记物，这将在量化人类方面具有很高的价值 纸巾。已发现软骨自旋-自旋(T2)弛豫时间对胶原蛋白的变化很敏感 超微结构与早期软骨退变有关。旋转框架中的软骨自旋-晶格松弛 (T1ρ)对大分子物质的浓度变化敏感，并与蛋白多糖的丢失有关。 骨关节炎。自旋-晶格弛豫(T1)时间的作用也被报道与力学性质有关 软骨的变化，对组织的进行性损害很敏感。虽然每个松弛参数 提供有限的和补充的软骨信息，能够同时成像T1、T2和T1ρ 将提供一套全面的成像生物标记物，用于协同访问大分子 软骨的含量及其超微结构。然而，由于扫描时间长，图像采集效率低， 而复杂的图像重建和组织建模，同时进行多松弛映射是非常重要的 因此，在开放式获取研究中，挑战仍然不发达。这项提议将提供快速的三个- 三维同步多松弛成像经显影定位膝关节T1、T2、T1ρ 一种新的成像序列和重建方法(目标1)。这项新技术将利用高效的三个- 并将通过一种新的深度学习方法加快速度，该方法 利用自我监督学习和MR物理信息组织建模。派生的磁共振成像 生物标记物将与软骨组织学、生化和机械性能相关，这将 建立解释临床研究结果的基础(目标2)。一项试点临床研究，使用优化的和 将对不同程度的膝骨性关节炎患者进行加速成像技术，建立 多松弛标测的实用性、有效性和总体临床价值的临床证据 分期骨关节炎(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。该方案的成功完成将为非侵入性地 监测疾病相关和治疗相关的组织成分和超微结构的变化 放松评估。它在骨性关节炎等疾病中具有广阔的临床应用前景。