Novel Fast Imaging and Reconstruction Strategies for Dynamic MRI

动态 MRI 的新型快速成像和重建策略

• 批准号: 8035353
• 负责人: Nicole Seiberlich
• 金额: $ 2.89万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8035353
• 关键词: Acceleration; Angiography; Area; Biomedical Engineering; Blood Vessels; Breathing; Cardiac; Categories; Cephalic; Clinical; Complement; Computers; Computing Methodologies; Data; Data Set; Development; Disease; Drug Formulations; Electrocardiogram; Engineering; Foundations; Freedom; Future; Goals; Gold; Grant; Head; Image; Joints; Magnetic Resonance Imaging; Measures; Methods; Pathology; Patients; Pattern; Phase; Physicians; Positioning Attribute; Process; Protocols documentation; Radial; Radiology Specialty; Research; Research Project Grants; Resolution; Sampling; Scientist; Solid; Speed; Staging; Techniques; Technology; Testing; Time; Ultrasonography; Universities; University Hospitals; Work; X-Ray Computed Tomography; base; computerized data processing; data acquisition; experience; flexibility; image reconstruction; imaging modality; improved; interest; meetings; novel; public health relevance; radiofrequency; radiologist; reconstruction; simulation; success; tool

DESCRIPTION (provided by applicant): The goal of this research project is to develop new, ultra-fast methods for dynamic imaging applications to enable greater clinical utility in the future. We intend to meet this goal by combining several existing image reconstruction methods, namely parallel imaging and non-Cartesian trajectories, to generate novel fast acquisition methods. Our current research involves the use of radial trajectories, as opposed to the standard, rectilinear trajectory, to acquire highly accelerated datasets in a very short time. These data can then be reconstructed using a special formulation of a parallel imaging method known as GRAPPA in order to reconstruct error-free images. Using this technique, we have acquired images with a temporal resolution of 60ms. We plan to expand this concept to trajectories which have the potential for even fast data acquisition, namely spiral and anisotropic field-of-view trajectories. Using these methods, we believe that it will be possible to generate images in less than 40ms, which will allow the acquisition real-time, free-breathing cardiac images, making EKG gating and breath holding unnecessary for cardiac function exams. In order to make these reconstructions possible in a clinically acceptable timeframe, they will be implemented on a GPU platform, which will reduce the reconstruction time from minutes to seconds. In the independent phase of the project, the GPU platform will be exploited in order to investigate different constrained reconstruction methods for MRI data. In addition to parallel imaging and non-Cartesian acquisitions, these techniques which include compressed sensing have also emerged as a new and important category of possible fast imaging methods. Early work has demonstrated an up to 20-fold reduction in data, and thus time, needed for an image. The power of these methods is obvious, although it is not yet clear if they will be viable in a clinical setting, due to, for instance, incredibly long computation times (sometimes up to days). Thus based on our experience in the first stage of this proposal, the independent portion of this project will explore the potential of these constrained reconstruction methods and examines the possibility of combining them with the non- Cartesian parallel imaging methods developed in the earlier phase. The rapid computational platform, in the form of the GPU implementations, will allow these novel image reconstruction techniques to be vigorously tested, paving the way for these methods to become practical for widespread clinical use. PUBLIC HEALTH RELEVANCE: While magnetic resonance imaging (MRI) is in widespread clinical use because of its sensitivity to a broad range of diseases, the relatively slow acquisition of MRI data limits its applicability to many dynamic imaging situations such as cardiac imaging or MR angiography. The goal of this project is to develop image reconstruction techniques for ultra-fast MRI imaging using a combination of novel acquisition and signal processing methods. Rapid computing using GPU implementations of these techniques will allow the reconstructions to take place in a matter of seconds, allowing this technology to be implemented in a clinical setting. These methods will revolutionize the acquisition and reconstruction of dynamic MRI data.

描述（由申请人提供）：该研究项目的目的是开发用于动态成像应用的新的，超快速的方法，以便将来实现更大的临床实用性。我们打算通过结合几种现有的图像重建方法，即并行成像和非 - 牙龈轨迹来实现这一目标，以生成新颖的快速获取方法。我们目前的研究涉及使用径向轨迹，而不是标准的直线轨迹，以在很短的时间内获取高加速的数据集。然后可以使用称为Grappa的并行成像方法的特殊公式重建这些数据，以重建无错误的图像。使用此技术，我们获得了时间分辨率为60ms的图像。我们计划将这一概念扩展到具有即使是快速数据获取的潜力，即螺旋和各向异性视野轨迹的潜力。使用这些方法，我们认为可以在少于40毫米的情况下生成图像，这将允许实时获取，自由呼吸的心脏图像，从而使Ekg的门控和呼吸对心脏功能检查不必要。为了使这些重建在临床上可接受的时间范围内成为可能，它们将在GPU平台上实施，这将使重建时间从几分钟减少到几秒钟。 在项目的独立阶段，将利用GPU平台来研究MRI数据的不同约束重建方法。除了并行成像和非 - 卡特斯式采集外，包括压缩感应的这些技术还成为可能的快速成像方法的新的重要类别。早期的工作表明，图像最多减少了20倍的数据，因此需要时间。这些方法的功能是显而易见的，尽管尚不清楚它们是否在临床环境中可行，例如，由于计算时间（有时长达几天），因此它们是否会在临床环境中可行。因此，基于我们在该提案的第一阶段的经验，该项目的独立部分将探讨这些约束重建方法的潜力，并研究它们与早期阶段开发的非笛卡尔平行成像方法相结合的可能性。快速计算平台以GPU实施的形式，将允许对这些新型的图像重建技术进行大力测试，从而为这些方法铺平了道路，以便于广泛的临床使用。 公共卫生相关性：虽然磁共振成像（MRI）由于对广泛疾病的敏感性而广泛使用，但MRI数据的获取相对缓慢地限制了其适用于许多动态成像情况，例如心脏成像或MR血管造影。该项目的目的是使用新颖的采集和信号处理方法的组合开发用于超快速MRI成像的图像重建技术。使用这些技术的GPU实现的快速计算将使重建可以在几秒钟内进行，从而可以在临床环境中实施该技术。这些方法将彻底改变动态MRI数据的获取和重建。

项目成果

Improved radial GRAPPA calibration for real-time free-breathing cardiac imaging.

• DOI: 10.1002/mrm.22618
• 发表时间: 2011-02
• 期刊: MAGNETIC RESONANCE IN MEDICINE
• 影响因子: 3.3
• 作者: Seiberlich, Nicole;Ehses, Philipp;Duerk, Jeff;Gilkeson, Robert;Griswold, Mark
• 通讯作者: Griswold, Mark