FREE BREATHING 3D CARDIAC MRI
自由呼吸 3D 心脏 MRI
基本信息
- 批准号:7563681
- 负责人:
- 金额:$ 1.22万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2007
- 资助国家:美国
- 起止时间:2007-08-01 至 2008-07-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsArtsBlurBreathingCardiacChildClinicalCodeCollaborationsComplexComputer Retrieval of Information on Scientific Projects DatabaseComputer softwareDataDiagnosticEvaluationFatty acid glycerol estersFinancial compensationFreezingFundingGoalsGrantHeartHourHybridsImageInstitutionInstructionKnowledgeMagnetic Resonance ImagingMeasurementMechanical ventilationMethodsMonitorMorphologic artifactsMotionMyocardiumPatientsPediatric HospitalsPerformancePhaseProtocols documentationPublicationsResearchResearch PersonnelResolutionResourcesRespirationScanningSchemeSedation procedureSeriesSignal TransductionSourceStagingTestingThree-Dimensional ImageThree-Dimensional ImagingTimeUnited States National Institutes of HealthValidationWorkWritingconceptheart motionimpressionimprovednovel strategiespreventprogramsreconstructionresearch studyrespiratorysimulationvolunteer
项目摘要
This subproject is one of many research subprojects utilizing the
resources provided by a Center grant funded by NIH/NCRR. The subproject and
investigator (PI) may have received primary funding from another NIH source,
and thus could be represented in other CRISP entries. The institution listed is
for the Center, which is not necessarily the institution for the investigator.
In cardiac MRI applications, the need to freeze or resolve both cardiac and respiratory motion poses a difficult challenge. We propose a novel approach to detect and correct for the complex respiration-induced motion of the heart, while capturing its beating motion. A respiration compensated, 3D cardiac imaging method will be developed and tested in its ability to evaluate myocardium motion, as compared to our current clinical wall-motion protocol. The specific aims are:
1. To develop and implement a very fast 3D imaging strategy. The algorithms for parallel imaging, for our UNFOLD method and for partial-Fourier imaging will be fused, and the resulting hybrid method will be implemented on a 3D steady-state free-precession (SSFP) imaging sequence.
2. To develop, implement and evaluate further additions to the fast imaging approach developed in Specific Aim 1. Novel strategies will be investigated to suppress fat signal, further suppress potential artifacts and improve spatial/temporal resolution. The resulting fast imaging method will be used to generate time series of 3D cardiac images with temporal resolution sufficient to resolve the respiratory cycle (one frame every 1 to 1.5 s).
3. To develop a method for detecting/correcting respiratory motion in a first step, and generating cardiac-phase images in a second step. The heart respiratory motion will be detected in two complementary ways: A conventional respiration monitoring stretchable belt will provide (non-quantitative) information with very high temporal resolution, while the 3D imaging scheme developed in Specific Aims 1 and 2 will provide a wealth of spatial/geometrical quantitative motionrelated information. Combining the knowledge from these two sources will allow the spatially/temporally complex respiratory-motion of the heart to be detected and correct for. In a second step, the respiration-corrected data will be converted from a time series to a cardiac-phase series of high quality 3D images.
4. To evaluate the method's performance in the task of capturing myocardium motion as compared to the protocol currently in use at our institution, a representative example of the current state-of-the-art. The goal is to verify the hypothesis that our method provides SNR, spatial resolution (which includes spatial blurring) and diagnostic value superior to those of the current protocol. Phantom experiments, simulations and imaging of volunteers and patients will be performed. The evaluation of these results will involve both objective criteria (quantitative measurements) as well as subjective criteria (clinicians' impressions on image quality).
Plans going forward
Although preliminary results showing the beating heart in 3D in free-breathing volunteers have been obtained, artifacts still limit the usefulness of the corresponding results. We will track down, and hopefully address, the sources of these artifacts. Increases in spatial resolution will also be incorporated into the implementation. Collaboration with the Children's hospital has been established to investigate whether the approach can be used to prevent the need for sedation and mechanical ventilation in children old enough to remain mostly still during a scan, but yet unable to reliably follow breathing instructions. The 2D imaging aspect of this work now seems ready for clinical validation.
Benefits of the Collaboration to the NCIGT
This project provides one of the applications where the fast-imaging approaches developed as part of the NCIGT Imaging core can be applied. More specifically, it is the first 3D application to be considered, and provides a practical context in which the 3D compatibility of the software we are writing can be tested and improved.
Benefits to the Project
The NCIGT is providing parallel-imaging software to replace the slow reconstruction programs currently in place (a few hours for a typical 3D time series) by much faster code, which can allow the method to proceed from a proof-of-concept stage to actual tests in a clinical setting.
Publications Acknowledging both the R01 and the U41 Grants
-B. Madore, W.S. Hoge, R. Kwong. An extension to the UNFOLD method to include free-breathing. Magn Reson Med 55:352-362 (2006).
-B. Madore, G. Farneb¿ck, C.-F. Westin, M. A. Dur¿n Mendicuti. A new strategy for respiration compensation, applied toward 3D free-breathing cardiac MR imaging. Magn Reson Imag 24:727-737 (2006).
这个子项目是许多研究子项目中利用
资源由NIH/NCRR资助的中心拨款提供。子项目和
调查员(PI)可能从NIH的另一个来源获得了主要资金,
并因此可以在其他清晰的条目中表示。列出的机构是
该中心不一定是调查人员的机构。
在心脏MRI的应用中,冻结或解决心脏和呼吸运动的需要是一个困难的挑战。我们提出了一种新的方法来检测和纠正复杂的呼吸诱导的心脏运动,同时捕获其跳动的运动。将开发一种呼吸补偿的3D心脏成像方法,并与我们目前的临床室壁运动方案进行比较,测试其评估心肌运动的能力。具体目标是:
1.开发和实施非常快速的3D成像策略。并行成像、展开方法和部分傅立叶成像的算法将被融合,由此产生的混合方法将在3D稳态自由进动(SSFP)成像序列上实现。
2.开发、实施和评估针对特定目标开发的快速成像方法的进一步补充1.将研究抑制脂肪信号、进一步抑制潜在伪影和提高空间/时间分辨率的新策略。由此产生的快速成像方法将用于生成时间序列的3D心脏图像,其时间分辨率足以解析呼吸周期(S每1到1.5帧)。
3.开发一种在第一步中检测/校正呼吸运动,并在第二步中产生心相图像的方法。心脏呼吸运动的检测将以两种互补的方式进行:传统的呼吸监测可伸展带将提供非常高时间分辨率的(非定量)信息,而在特定目标1和2中开发的3D成像方案将提供丰富的空间/几何定量运动相关信息。将这两个来源的知识结合起来,可以检测到心脏在空间/时间上复杂的呼吸运动,并对其进行校正。在第二步中,经过呼吸校正的数据将从时间序列转换为高质量3D图像的心脏时相序列。
4.与我们机构目前使用的方案相比,评估该方法在捕获心肌运动任务中的性能,这是当前最先进的代表性实例。目的是验证我们的方法提供的信噪比、空间分辨率(包括空间模糊)和诊断价值优于当前协议的假设。将对志愿者和患者进行体模实验、模拟和成像。对这些结果的评估将包括客观标准(定量测量)和主观标准(临床医生对图像质量的印象)。
未来的计划
尽管已经获得了自由呼吸志愿者的3D心脏跳动的初步结果,但人工制品仍然限制了相应结果的实用性。我们将追踪并有望解决这些文物的来源。提高空间分辨率也将纳入执行工作。已经与儿童医院建立了合作关系,以调查这种方法是否可以用于防止年龄足够大的儿童在扫描过程中大部分保持静止,但无法可靠地遵循呼吸指令的情况下需要镇静和机械通风。这项工作的2D成像方面现在似乎已经准备好进行临床验证。
协作给NCIGT带来的好处
该项目提供了作为NCIGT成像核心的一部分开发的快速成像方法可以应用的应用之一。更具体地说,它是第一个考虑的3D应用程序,并提供了一个实际环境,可以在其中测试和改进我们正在编写的软件的3D兼容性。
给项目带来的好处
NCIGT正在提供并行成像软件,以更快的代码取代目前缓慢的重建程序(典型的3D时间序列需要几个小时),这可以允许该方法从概念验证阶段进入临床环境中的实际测试。
同时认可R01和U41资助金的出版物
-B.题名/责任者:The W.S.Hoge,R.展开方法的扩展,包括自由呼吸。《医学评论》55:352-362(2006)。
-B.题名/责任者:A.一种新的呼吸补偿策略,应用于3D自由呼吸心脏磁共振成像。Magn Reson Imag 24:727-737(2006)。
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 }}
Bruno Madore其他文献
Bruno Madore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('Bruno Madore', 18)}}的其他基金
Ultrasound-based sensors for the fusion and motion correction of MRI and PET/CT data
用于 MRI 和 PET/CT 数据融合和运动校正的超声波传感器
- 批准号:
10092861 - 财政年份:2021
- 资助金额:
$ 1.22万 - 项目类别:
Robust Cardiac-gated MRI using Ultrasound Sensors
使用超声波传感器的稳健心门控 MRI
- 批准号:
9557023 - 财政年份:2017
- 资助金额:
$ 1.22万 - 项目类别:
Temperature monitoring in moving organs during thermal ablation
热消融期间运动器官的温度监测
- 批准号:
8716533 - 财政年份:2011
- 资助金额:
$ 1.22万 - 项目类别:
Temperature monitoring in moving organs during thermal ablation
热消融期间运动器官的温度监测
- 批准号:
8893016 - 财政年份:2011
- 资助金额:
$ 1.22万 - 项目类别:
Temperature monitoring in moving organs during thermal ablation
热消融期间运动器官的温度监测
- 批准号:
8513939 - 财政年份:2011
- 资助金额:
$ 1.22万 - 项目类别:
Temperature monitoring in moving organs during thermal ablation
热消融期间运动器官的温度监测
- 批准号:
8333961 - 财政年份:2011
- 资助金额:
$ 1.22万 - 项目类别:
Temperature monitoring in moving organs during thermal ablation
热消融期间运动器官的温度监测
- 批准号:
8040155 - 财政年份:2011
- 资助金额:
$ 1.22万 - 项目类别:
Advanced Techniques for Rapid and Artifact-Resistant MR Diffusion Imaging
快速、抗伪影的 MR 扩散成像先进技术
- 批准号:
8119465 - 财政年份:2010
- 资助金额:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 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:
$ 1.22万 - 项目类别:
Continuing Grant