NMR-Based Rapid Fluid Assessment: Device Design and Signal Processing

基于 NMR 的快速流体评估:设备设计和信号处理

基本信息

  • 批准号:
    10441674
  • 负责人:
  • 金额:
    $ 58.18万
  • 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:
    2022-05-05 至 2026-01-31
  • 项目状态:
    未结题

项目摘要

NMR-Based Rapid Fluid Assessment: Device Design and Signal Processing PROJECT SUMMARY Our goal is to develop a portable, non-invasive, measurement of volume status to improve quality of life and reduce morbidity and mortality among hospitalized patients. Maintenance of euvolemic status and proper fluid balance are critical for health and improved outcomes for renal, cardiovascular, and many other disease types as well as in healthy populations prone to dehydration such as athletes and soldiers. Our laboratory has previously constructed a portable single sided magnetic resonance (MR) sensors that is capable of resolving individual fluid compartments (subcutaneous, intramuscular, etc.) within tissue. This sensor was used in a pilot clinical trial with end stage kidney disease patients. Quantitative MRI results on these patients demonstrated that the first sign of fluid overload among hemodialysis patients is an expanded skeletal muscle extracellular fluid (ECF) space. The early stage nature of the technology was evident in that study as the portable sensor could not unambiguously differentiate skeletal muscle tissue from subcutaneous tissue. The proposed research includes the design of a new portable low-field MR sensor and improved signal processing that will allow it to capture the same quantitative assessment of volume status currently achievable with quantitative MRI (qMRI). We measure local fluid distribution in the target in vivo tissue compartment. In the case of fluid volume status, our hypothesis is that a localized skeletal muscle measurement is representative of systemic fluid distribution based on results from a prior study1. The optimized sensor will have the sensitive region of the magnetic field designed to target the skeletal muscle. The existing and newly designed portable MR sensors will be used to measure intramuscular fluid distribution in end stage kidney disease patients undergoing dialysis treatment as well as in healthy athletes experiencing exercise induced fluid loss. The sensor measurement will allow for quantification of volume overload (hypervolemia) or depletion (hypovolemia) and allow for its use in clinical decision making. Dialysis patients and athletes are the target population for the following proposal. The rapid reduction in fluid volume during a dialysis session and exercise respectively provides the ideal clinical context for performing repeated fluid status measurements.
基于核磁共振的流体快速评价装置设计与信号处理 项目总结 我们的目标是开发一种便携式、非侵入性的容量状态测量方法,以提高质量 改善生活,减少住院病人的发病率和死亡率。维持等容血容量 状态和适当的液体平衡对肾脏的健康和改善预后至关重要, 心血管疾病和许多其他类型的疾病,以及容易患上 运动员和士兵等脱水。我们的实验室之前已经构建了一种便携式 能够分辨单个流体的单面磁共振(MR)传感器 间隔(皮下、肌肉内等)在组织内。该传感器在飞行员身上使用。 终末期肾病患者的临床试验。这些患者的定量MRI结果 证明血液透析患者液体超载的第一个症状是扩张 骨骼肌胞外液(ECF)间隙。这项技术的早期性质是 在这项研究中很明显,因为便携式传感器不能明确区分骨骼肌 皮下组织中的组织。 提出的研究包括设计一种新的便携式低场磁共振传感器和 改进的信号处理,使其能够捕获相同的定量评估 容量状态目前可通过定量磁共振成像(QMRI)获得。我们测量局部流体 分布于体内靶区组织间。在流体体积状态的情况下,我们的 假设局部骨骼肌测量是体液的代表。 基于先前研究结果的分布1。优化后的传感器将具有更高的灵敏度 以骨骼肌为目标的磁场区域。现有的和新的 设计的便携式磁共振传感器将用于在终末期测量肌肉内的液体分布 接受透析治疗的肾病患者以及健康运动员经历 运动引起的液体流失。传感器测量将允许对体积进行量化 超负荷(高容量血症)或衰竭(低容量血症),并允许在临床决策中使用 制作。透析患者和运动员是以下提案的目标人群。这个 在透析期和运动期间迅速减少液体量分别提供 适用于重复进行液体状态测量的理想临床环境。

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)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Michael J Cima其他文献

Next-generation wearable electronics
下一代可穿戴电子设备
  • DOI:
    10.1038/nbt.2952
  • 发表时间:
    2014-07-08
  • 期刊:
  • 影响因子:
    41.700
  • 作者:
    Michael J Cima
  • 通讯作者:
    Michael J Cima

Michael J Cima的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Michael J Cima', 18)}}的其他基金

NMR-Based Rapid Fluid Assessment: Device Design and Signal Processing
基于 NMR 的快速流体评估:设备设计和信号处理
  • 批准号:
    10617808
  • 财政年份:
    2022
  • 资助金额:
    $ 58.18万
  • 项目类别:
Micro-invasive biochemical sampling of brain interstitial fluid for investigating neural pathology
脑间质液微创生化取样用于研究神经病理学
  • 批准号:
    10517496
  • 财政年份:
    2020
  • 资助金额:
    $ 58.18万
  • 项目类别:
Micro-invasive biochemical sampling of brain interstitial fluid for investigating neural pathology
脑间质液微创生化取样用于研究神经病理学
  • 批准号:
    10304119
  • 财政年份:
    2020
  • 资助金额:
    $ 58.18万
  • 项目类别:
Micro-invasive biochemical sampling of brain interstitial fluid for investigating neural pathology
脑间质液微创生化取样用于研究神经病理学
  • 批准号:
    9885472
  • 财政年份:
    2020
  • 资助金额:
    $ 58.18万
  • 项目类别:
Micro-invasive biochemical sampling of brain interstitial fluid for investigating neural pathology
脑间质液微创生化取样用于研究神经病理学
  • 批准号:
    10090597
  • 财政年份:
    2020
  • 资助金额:
    $ 58.18万
  • 项目类别:
Implantable device for high-throughput in vivo drug sensitivity testing
用于高通量体内药物敏感性测试的植入装置
  • 批准号:
    8889223
  • 财政年份:
    2014
  • 资助金额:
    $ 58.18万
  • 项目类别:
Implantable device for high-throughput in vivo drug sensitivity testing
用于高通量体内药物敏感性测试的植入装置
  • 批准号:
    8738826
  • 财政年份:
    2014
  • 资助金额:
    $ 58.18万
  • 项目类别:
Implantable device for high-throughput in vivo drug sensitivity testing
用于高通量体内药物敏感性测试的植入装置
  • 批准号:
    9094541
  • 财政年份:
    2014
  • 资助金额:
    $ 58.18万
  • 项目类别:
A New Device for Electrical & Chemical Modulation of Pathological Neural Activity
一种新的电气装置
  • 批准号:
    8640943
  • 财政年份:
    2013
  • 资助金额:
    $ 58.18万
  • 项目类别:
A New Device for Electrical & Chemical Modulation of Pathological Neural Activity
一种新的电气装置
  • 批准号:
    8502954
  • 财政年份:
    2013
  • 资助金额:
    $ 58.18万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 58.18万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了