Multiparametric Mapping of Knee Joint with Magnetic Resonance Fingerprinting

膝关节磁共振指纹多参数绘图

基本信息

批准号：
10115230
负责人：
Ravinder Regatte
金额：
$ 62.07万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10115230
关键词：
3-Dimensional Abdomen Affect Agar Base Sequence Biochemical Brain Cardiac Cartilage Cattle Clinical Clinical Research Protocols Collagen Collagen Fiber Contrast Media Data Degenerative polyarthritis Development Diagnosis Dictionary Disease Disease Progression Early Diagnosis Evolution Extracellular Matrix Fingerprint Future Gel Goals Healthcare Systems Hip region structure Image Individual KITLG gene Knee Osteoarthritis Knee joint Lead Magnetic Resonance Magnetic Resonance Imaging Maps Measures Modeling Morphology Noise Pathologic Processes Pathology Patient Outcomes Assessments Patients Pattern Pattern Recognition Physiologic pulse Population Preparation Property Prostate Proteoglycan Protons Quantitative Evaluations Radial Relaxation Reproducibility Sampling Scanning Signal Transduction Structure System Techniques Time Tissues Training Translating United States Validation Variant articular cartilage base cartilage degradation clinical application data acquisition density follow-up imaging biomarker improved in vivo interest joint destruction macromolecule non-invasive imaging novel simulation therapeutic evaluation

项目摘要

PROJECT SUMMARY Osteoarthritis (OA) is a degenerative joint disease, affecting more than 27 million people in the United States alone. This large affected population and the severe consequent debility of OA lead to significant expenses to the health care system. OA is characterized by biochemical, structural and morphologic degradation of components of the extracellular matrix (ECM) of articular cartilage. The ECM is composed of primarily two groups of macromolecules including proteoglycan (PG) and collagen fibers. Early diagnosis of cartilage degeneration would require the ability to non-invasively detect changes in PG concentration and collagen integrity before morphological changes occur. T1, T2 and T1ρ relaxation times are affected by these pathological processes and are the most widely used biochemical cartilage MRI sequences worldwide. The overarching goal of this proposal is to develop, optimize, and translate the magnetic resonance fingerprinting (MRF) framework, which allows for simultaneous, morphological, volumetric, and quantitative multiparametric mapping [T1, T2, T1ρ, B1+ and proton density (PD)] to the knee joint in a much shorter time (≤10 minutes) than conventional individual parametric mapping on a standard 3T clinical scanner. The proposed MRF-based multiparametric mapping approach can be easily incorporated into routine research/clinical protocols for multi- tissue assessment of the knee joint without exogenous contrast agents and could serve as future imaging biomarkers for disease modifying therapies for OA.

项目概要骨关节炎 (OA) 是一种退行性关节疾病，影响美国超过 2700 万人光是如此庞大的受影响人口以及随之而来的严重的 OA 就导致了巨大的开支。 OA 的特点是生物化学、结构和形态退化。关节软骨细胞外基质 (ECM) 的成分 ECM 主要由两组组成。包括蛋白多糖（PG）和胶原纤维在内的大分子的软骨退化的早期诊断。需要能够在之前以非侵入性方式检测 PG 浓度和胶原蛋白完整性的变化 T1、T2 和 T1ρ 弛豫时间会发生形态变化，并受到这些病理过程的影响。是全球使用最广泛的生化软骨 MRI 序列。该提案的总体目标是开发、优化和翻译磁共振指纹识别 (MRF) 框架，允许同时、形态、体积和定量多参数将 [T1、T2、T1ρ、B1+ 和质子密度 (PD)] 映射到膝关节的时间（≤10 分钟）比标准 3T 临床扫描仪上的传统个体参数映射建议的基于 MRF 的。多参数映射方法可以轻松地纳入多参数的常规研究/临床方案中无需外源性造影剂即可对膝关节进行组织评估，并可作为未来的成像 OA 疾病修饰疗法的生物标志物。