Improved Motion Robust MRI of Children

改进儿童运动鲁棒性 MRI

基本信息

  • 批准号:
    10605154
  • 负责人:
  • 金额:
    $ 57.65万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-07-01 至 2025-03-31
  • 项目状态:
    未结题

项目摘要

Project Summary Magnetic resonance imaging (MRI) is critically important for pediatric care. However, patient motion significantly limits our ability to produce high-quality images in young children who may be unable to respond well to verbal instructions and who have difficulty remaining still inside the scanner. Head motion during MRI disrupts spatial encoding and leads to data loss, generating a range of artifacts in the images, which hinders diagnostic utility. Thus, sedation and anesthesia are routinely used in pediatric populations; however, these practices are associated with severe adverse events and are extremely time-consuming and costly to administer. Unfortunately, current state-of-the-art motion compensation technologies are not fast or accurate enough to adequately compensate for large and frequent head movements in uncooperative children, or require external hardware, which is far from ideal for clinical workflow. Under the previous grant period, we made significant progress towards our overarching goal of improved motion-robust pediatric MRI by successfully developing a new markerless motion tracking approach utilizing free induction decay (FID) navigators and novel algorithms to generate diagnostic images from small periods of motion-free time. The goal of the research proposed under this renewed application to the NIH is two-fold: 1) to continue to develop and refine novel markerless technologies for motion measurement and correction to enable high-quality MRI in the presence of large, frequent motion and 2) to evaluate these technologies for improving the quality and success rate of pediatric MRI without the use of sedation and anesthesia. We hypothesize that improving the accuracy of FID navigator motion measurements, and the extent and speed of our correction algorithms, will successfully compensate for sources of persistent artifacts in the images. To achieve these ambitious goals, we propose to undertake the following Specific Aims over the 5-year period of requested support: 1) develop and evaluate an extended model that can, for the first time, simultaneously measure head motion and induced magnetic field changes using FID navigators; 2) develop and evaluate a novel self-navigated 3D radial acquisition with augmented reconstruction for retrospective correction of motion, and induced magnetic field and coil sensitivity variations; 3) develop and evaluate prospective motion correction and dynamic shimming utilizing real-time motion and field measurements to produce artifact-free images; and 4) apply and evaluate these highly innovative motion compensation techniques for imaging 0–8 year old patients without the use of sedation. The motion-robust imaging technologies proposed in this application can be easily deployed in clinical settings with widely-available, standard MRI hardware, and are therefore expected to have rapid translational impact for the countless pediatric diseases and disorders presently evaluated by MRI. The ability to image young children without the use of sedation and anesthesia will dramatically decrease the time, cost and risk involved in generating diagnostically useful images with MRI.
项目摘要 磁共振成像(MRI)是至关重要的儿科护理。然而,耐心的动议 极大地限制了我们在幼儿身上产生高质量图像的能力,这些幼儿可能无法做出反应 好的,口头指示和那些在扫描仪内保持不动的人。磁共振成像过程中的头部运动 扰乱空间编码并导致数据丢失,从而在图像中生成一系列伪像,这阻碍了 诊断实用程序。因此,镇静和麻醉在儿科人群中是常规使用的;然而,这些 实践与严重的不良事件相关,并且极其耗时且代价高昂 管理。不幸的是,当前最先进的运动补偿技术既不快也不准确 足以充分补偿不合作儿童的大而频繁的头部运动,或者 需要外部硬件,这远远不是临床工作流程的理想选择。在上一个授权期内,我们 取得了重大进展,我们的总体目标,改善运动健壮的儿科核磁共振 成功地开发了一种新的利用自由感应衰减(FID)的无标记运动跟踪方法 导航器和新的算法,可从较小的非运动时间段生成诊断图像。这个 根据这一新的申请,NIH提出的研究目标有两个:1)继续开发 并改进用于运动测量和校正的新型无标记技术,以实现高质量的MRI 存在大的、频繁的运动,以及2)评估这些技术以提高质量和 不使用镇静剂和麻醉剂的儿童MRI成功率。我们假设,改善 FID导航仪运动测量的准确性,以及我们校正算法的范围和速度,将 成功补偿图像中持久伪影的来源。为了实现这些雄心勃勃的目标, 我们建议在请求支持的5年期间实现以下具体目标:1)开发 并首次评估了一种扩展模型,该模型可以同时测量头部运动和诱导 使用FID导航仪的磁场变化;2)开发和评估一种新型的自导航3D径向 具有增强重建的采集,用于运动和感应磁场的回溯校正 和线圈灵敏度变化;3)开发和评估预期的运动校正和动态垫片 利用实时运动和现场测量来产生无伪影图像;以及4)应用和评估 这些高度创新的运动补偿技术为0-8岁的患者提供了无需使用 镇静剂。此应用程序中建议的运动稳健成像技术可以轻松部署在 具有广泛可用的标准MRI硬件的临床环境,因此预计将具有快速 目前通过核磁共振对无数儿科疾病和障碍的翻译影响进行评估。一种能力 在不使用镇静和麻醉的情况下想象幼儿将极大地减少时间、成本 以及使用MRI生成诊断有用图像所涉及的风险。

项目成果

期刊论文数量(34)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(1)
Gradient-Guided Isotropic MRI Reconstruction from Anisotropic Acquisitions.
Deep learning-based parameter estimation in fetal diffusion-weighted MRI.
  • DOI:
    10.1016/j.neuroimage.2021.118482
  • 发表时间:
    2021-11
  • 期刊:
  • 影响因子:
    5.7
  • 作者:
    Karimi D;Jaimes C;Machado-Rivas F;Vasung L;Khan S;Warfield SK;Gholipour A
  • 通讯作者:
    Gholipour A
Analytic quantification of bias and variance of coil sensitivity profile estimators for improved image reconstruction in MRI.
对线圈灵敏度分布估计器的偏差和方差进行分析量化,以改进 MRI 中的图像重建。
Fetal Echoplanar Imaging: Promises and Challenges.
Head motion measurement and correction using FID navigators.
  • DOI:
    10.1002/mrm.27381
  • 发表时间:
    2019-01
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Wallace TE;Afacan O;Waszak M;Kober T;Warfield SK
  • 通讯作者:
    Warfield SK
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SIMON K WARFIELD其他文献

SIMON K WARFIELD的其他文献

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{{ truncateString('SIMON K WARFIELD', 18)}}的其他基金

Motion Compensated fMRI for Pre-Surgical Planning in Epilepsy
用于癫痫手术前规划的运动补偿功能磁共振成像
  • 批准号:
    10659634
  • 财政年份:
    2023
  • 资助金额:
    $ 57.65万
  • 项目类别:
Machine learning algorithms to analyze large medical image datasets
用于分析大型医学图像数据集的机器学习算法
  • 批准号:
    10434022
  • 财政年份:
    2021
  • 资助金额:
    $ 57.65万
  • 项目类别:
Machine learning algorithms to analyze large medical image datasets
用于分析大型医学图像数据集的机器学习算法
  • 批准号:
    10182522
  • 财政年份:
    2021
  • 资助金额:
    $ 57.65万
  • 项目类别:
Machine learning algorithms to analyze large medical image datasets
用于分析大型医学图像数据集的机器学习算法
  • 批准号:
    10584569
  • 财政年份:
    2021
  • 资助金额:
    $ 57.65万
  • 项目类别:
Novel MRI Imaging Tools and Software for Assessing Pediatric Crohn's Disease
用于评估儿童克罗恩病的新型 MRI 成像工具和软件
  • 批准号:
    8997501
  • 财政年份:
    2014
  • 资助金额:
    $ 57.65万
  • 项目类别:
Novel MRI Imaging Tools and Software for Assessing Pediatric Crohn's Disease
用于评估儿童克罗恩病的新型 MRI 成像工具和软件
  • 批准号:
    9212806
  • 财政年份:
    2014
  • 资助金额:
    $ 57.65万
  • 项目类别:
MRI Biomarkers of Patients with Tuberous Sclerosis Complex and Autism
结节性硬化症和自闭症患者的 MRI 生物标志物
  • 批准号:
    9315944
  • 财政年份:
    2013
  • 资助金额:
    $ 57.65万
  • 项目类别:
MRI Biomarkers of Patients with Tuberous Sclerosis Complex and Autism
结节性硬化症和自闭症患者的 MRI 生物标志物
  • 批准号:
    9112028
  • 财政年份:
    2013
  • 资助金额:
    $ 57.65万
  • 项目类别:
MRI Biomarkers of Patients with Tuberous Sclerosis Complex and Autism
结节性硬化症和自闭症患者的 MRI 生物标志物
  • 批准号:
    8896887
  • 财政年份:
    2013
  • 资助金额:
    $ 57.65万
  • 项目类别:
MRI Biomarkers of Patients with Tuberous Sclerosis Complex and Autism
结节性硬化症和自闭症患者的 MRI 生物标志物
  • 批准号:
    8705058
  • 财政年份:
    2013
  • 资助金额:
    $ 57.65万
  • 项目类别:

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