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: 8387483
• 负责人: Nicole Seiberlich
• 金额: $ 24.86万
• 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 2014-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8387483
• 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; abstracting; base; computerized data processing; data acquisition; experience; flexibility; image reconstruction; imaging modality; improved; interest; meetings; novel; radiofrequency; radiologist; reconstruction; simulation; success; tool

Abstract 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 breathholding 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.

抽象的 该研究项目的目的是开发新的超快速方法来动态 成像应用，以使未来更大的临床实用性。我们打算实现这个目标 通过结合几种现有图像重建方法，即并行成像和 非现行轨迹，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，而不是标准直线轨迹的使用 在很短的时间内获取高度加速的数据集。这些数据可以是 使用平行成像方法的特殊公式重建，称为grappa 为了重建无错误的图像。使用此技术，我们获得了用 时间分辨率为60ms。我们计划将这个概念扩展到具有 即使是快速数据获取的潜力，即螺旋和各向异性视野。 轨迹。使用这些方法，我们认为可以在 小于40毫秒，这将允许实时获取，自由呼吸的心脏图像， 对心脏功能检查不必要，使心电的门控和呼吸不必要。为了 在临床上可接受的时间范围内使这些重建成为可能 在GPU平台上实施，该平台将将重建时间从分钟减少到 秒。 在项目的独立阶段，GPU平台将被利用 研究MRI数据的不同约束重建方法。除了平行 成像和非 - 牙犯的收购，包括压缩的这些技术 感知也已成为可能快速成像的新重要类别 方法。早期工作表明数据最多减少了20倍，因此时间，因此 图像需要。这些方法的力量是显而易见的，尽管目前尚不清楚是否存在 由于计算时间非常长，因此它们在临床环境中将是可行的 （有时最多几天）。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索这些受约束的潜力 重建方法并检查了将它们与非 - 笛卡尔并行成像方法在早期阶段开发。快速计算 平台，以GPU实现的形式，将允许这些新颖的图像重建 要大力测试的技术，为这些方法铺平了道路 广泛的临床用途。