Rapid Quantitative Assessment of Knee Joint with Compressed Sensing

利用压缩感知对膝关节进行快速定量评估

• 批准号: 10686034
• 负责人: Ravinder Regatte
• 金额: $ 62.74万
• 依托单位: NEW YORK UNIVERSITY SCHOOL OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-03 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10686034
• 关键词: 3-Dimensional; Acceleration; Affect; Binding; Biochemical; Biological Models; Bovine Cartilage; Cartilage; Clinical; Clinical Protocols; Collagen; Collagen Fiber; Data; Degenerative polyarthritis; Development; Diagnostic; Disease; Early Diagnosis; Evaluation; Extracellular Matrix; Future; Goals; Healthcare Systems; Histology; Human; Hydration status; Image; Imaging Techniques; Joints; Knee Osteoarthritis; Knee joint; Lead; Magnetic Resonance Imaging; Maps; Meniscus structure of joint; Methods; Modeling; Morphology; Musculoskeletal; Non-Invasive Detection; Outcome; Pain; Pathologic Processes; Patients; Performance; Persons; Population; Proteoglycan; Protocols documentation; Relaxation; Research Personnel; Resolution; Sampling; Scanning; Slice; Specificity; Structure; T2 weighted imaging; Techniques; Therapeutic Agents; Thick; Time; Tissue Engineering; Tissues; Translating; Treatment Protocols; United States; Validation; Water; articular cartilage; cartilage degradation; cohort; data space; efficacy evaluation; healing; imaging biomarker; improved; in vivo; macromolecule; morphometry; non-invasive imaging; novel; personalized medicine; premature; prevent; reconstruction; repaired

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. T1ρ and T2 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 high spatial resolution 3D-isotropic- MRI sequence (700µmX700µmX700µm) for simultaneous assessment of morphometry and biexponential 3D- T1ρ (T2) mapping sequences (each protocol under 10 minutes) for improved quantitative assessment of morphological (cartilage thickness and volume) and biochemical characterization of cartilage on a standard clinical 3T scanner employing combinations of compressed sensing (CS) and parallel imaging (PI). The proposed accelerated, isotropic, high spatial resolution, multicomponent 3D-T1ρ (T2) mapping techniques can be easily incorporated into routine clinical protocols for biochemical assessment of cartilage in addition to standard morphological evaluation and could serve as future imaging biomarkers for disease modifying therapies for OA. The outcome of this proposed study will significantly impact our ability for personalized treatment regimens and possibly prevent the development of premature OA.

项目总结 骨关节炎(OA)是一种退行性关节疾病，在美国有2700多万人患病 独自一人。这一庞大的受影响人口以及随之而来的严重的办公自动化能力的丧失导致了大量的费用 医疗保健系统。OA的特征是生物化学、结构和形态上的降解 关节软骨细胞外基质(ECM)成分。ECM主要由两个部分组成 包括蛋白多糖(PG)和胶原纤维在内的一组大分子。软骨的早期诊断 退化需要非侵入性检测PG浓度和胶原蛋白变化的能力 在形态发生变化之前保持完整性。T1ρ和T2松弛时间受这些病理因素的影响 是目前世界上使用最广泛的生物化学软骨磁共振序列。。 该建议的总体目标是开发、优化和转换高空间分辨率的3D-各向同性- MRI序列(700微米×700微米×700微米)，用于同时评估形态测量和双指数3D- T1ρ(T2)映射序列(每个协议不超过10分钟)，以改进定量评估 标准软骨的形态(软骨厚度和体积)和生化特征 采用压缩传感(CS)和并行成像(PI)相结合的临床3T扫描仪。这个 建议的加速、各向同性、高空间分辨率、多分量3D-T1ρ(T2)映射技术可以 可轻松合并到常规临床方案中，用于软骨生化评估 标准的形态评估，可作为未来疾病修饰的成像生物标记物 治疗骨性关节炎。这项拟议研究的结果将显著影响我们的个性化能力 治疗方案，并可能预防早产儿骨性关节炎的发展。

项目成果

Musculoskeletal MR Imaging Applications at Ultra-High (7T) Field Strength.

• DOI: 10.1016/j.mric.2020.09.008
• 发表时间: 2021-03
• 期刊: Magnetic resonance imaging clinics of North America
• 影响因子: 1.6
• 作者: Menon RG;Chang G;Regatte RR
• 通讯作者: Regatte RR

Emerging Trends in Fast MRI Using Deep-Learning Reconstruction on Undersampled k-Space Data: A Systematic Review.

• DOI: 10.3390/bioengineering10091012
• 发表时间: 2023-08-26
• 期刊: Bioengineering (Basel, Switzerland)

3D magnetic resonance fingerprinting for rapid simultaneous T1, T2, and T1ρ volumetric mapping of human articular cartilage at 3 T.

• DOI: 10.1002/nbm.4800
• 发表时间: 2022-12
• 期刊: NMR in biomedicine
• 影响因子: 2.9

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications.

• DOI: 10.1002/jmri.28689
• 发表时间: 2023-07
• 期刊: JOURNAL OF MAGNETIC RESONANCE IMAGING
• 影响因子: 4.4
• 作者: Zibetti, Marcelo V. W.;Menon, Rajiv G. G.;de Moura, Hector L. L.;Zhang, Xiaoxia;Kijowski, Richard;Regatte, Ravinder R. R.
• 通讯作者: Regatte, Ravinder R. R.

Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications.

• DOI: 10.1109/tci.2022.3176129
• 发表时间: 2022
• 期刊: IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
• 影响因子: 5.4
• 作者: Zibetti, Marcelo Victor Wust;Knoll, Florian;Regatte, Ravinder R.
• 通讯作者: Regatte, Ravinder R.