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.

项目概要 骨关节炎（OA）是影响人类关节的最普遍的疾病之一，其特征是关节减少 软骨细胞外基质中的蛋白多糖含量和胶原纤维网络的破坏。磁的 磁共振 (MR) 成像已用于量化软骨成分和微观结构的变化 OA 退化。在所有 MR 技术中，MR 松弛测量是最受欢迎的，可以提供非侵入性、 高分辨率、三维成像生物标志物，这对于量化人类非常有价值 组织。已发现软骨自旋（T2）弛豫时间对胶原蛋白的变化敏感 超微结构与早期软骨退化相关。旋转框架中的软骨自旋晶格弛豫 (T1ρ) 对大分子的浓度变化敏感，并且与蛋白聚糖损失相关 办公自动化。据报道，自旋晶格弛豫 (T1) 时间的作用与机械性能相关 软骨的变化并对组织的渐进性损伤敏感。而每个松弛参数 提供软骨的有限和补充信息，同时成像 T1、T2 和 T1ρ 的能力 将提供一套全面的成像生物标志物，用于协同访问大分子 软骨的含量及其超微结构。但由于扫描时间长、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重要的 因此，OA 研究仍然不发达。该提案将提供快速的三 通过开发三维同步多松弛成像来绘制膝盖的 T1、T2 和 T1ρ 一种新颖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 三维黄金角度图像采集，并将通过一种新颖的深度学习方法加速， 利用自我监督学习和 MR 物理信息组织建模。衍生的 MR 成像 生物标志物将与软骨组织学、生化和机械特性相关，这将 为临床研究结果的解释奠定基础（目标 2）。使用优化和 加速成像技术将对不同程度的膝关节骨关节炎患者进行，建立 多重松弛映射在检测和诊断方面的实用性、效率和整体临床价值的临床证据 分期 OA（目标 3）。我们提出的新方法将源于开发新颖的快速图像采集， 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为非侵入性提供一种新的快速成像技术 通过多种方式监测组织成分和超微结构中与疾病相关和治疗相关的变化 松弛评估。它将在 OA 和其他疾病方面具有广泛的临床应用。