Rapid Three-dimensional Simultaneous Knee Multi-Relaxation Mapping

快速三维同步膝关节多重松弛映射

基本信息

  • 批准号:
    10662544
  • 负责人:
  • 金额:
    $ 38.87万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Fang Liu其他文献

Research on the Comprehensive Benefit Evaluation of Electric Vehicle Technology Promotion and Application Under the Strategic Background of “Carbon Peaking and Carbon Neutrality”
  • DOI:
    10.1007/s42835-023-01643-4
  • 发表时间:
    2023-09-14
  • 期刊:
  • 影响因子:
    1.600
  • 作者:
    Dexiang Jia;Xinda Li;Shaodong Guo;Fang Liu;Chengcheng Fu;Xingde Huang;Zhen Dong;Jing Liu
  • 通讯作者:
    Jing Liu

Fang Liu的其他文献

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{{ truncateString('Fang Liu', 18)}}的其他基金

Ultra-Fast High-Resolution Multi-Parametric MRI for Characterizing Cartilage Extracellular Matrix
用于表征软骨细胞外基质的超快速高分辨率多参数 MRI
  • 批准号:
    10929242
  • 财政年份:
    2023
  • 资助金额:
    $ 38.87万
  • 项目类别:
Deep Learning Technology for Rapid Morphological and Quantitative Imaging of Knee Pathology
用于膝关节病理学快速形态学和定量成像的深度学习技术
  • 批准号:
    10444468
  • 财政年份:
    2022
  • 资助金额:
    $ 38.87万
  • 项目类别:
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
  • 财政年份:
    2022
  • 资助金额:
    $ 38.87万
  • 项目类别:
Deep Learning Reconstruction for Rapid Multi-Component Relaxometry
快速多分量松弛测量的深度学习重建
  • 批准号:
    10372860
  • 财政年份:
    2022
  • 资助金额:
    $ 38.87万
  • 项目类别:
Deep Learning Technology for Rapid Morphological and Quantitative Imaging of Knee Pathology
用于膝关节病理学快速形态学和定量成像的深度学习技术
  • 批准号:
    10630920
  • 财政年份:
    2022
  • 资助金额:
    $ 38.87万
  • 项目类别:
Deep Learning Reconstruction for Rapid Multi-Component Relaxometry
快速多分量松弛测量的深度学习重建
  • 批准号:
    10598038
  • 财政年份:
    2022
  • 资助金额:
    $ 38.87万
  • 项目类别:

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